Fluid monitoring system, device, and method

Abstract

To provide a technique of predicting infection of a patient.SOLUTION: A system and a method may include illuminating patient body fluid inside a fluid conduit from a plurality of illumination directions; measuring an optical characteristic of the illuminated patient body fluid by using one or a plurality of sensors; and predicting an infection state of the patient on the basis of at least partially the measured optical characteristic.SELECTED DRAWING: Figure 3A

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Patent Application No. 62 / 867,157, filed June 26, 2019, the contents of which are incorporated herein by reference in their entirety.

[0002] Field FIELD OF THE INVENTION

[0002] The devices, systems and methods herein relate to fluid monitoring that can be used for diagnostic and / or therapeutic applications, including but not limited to, infectious disease prediction. [Background technology]

[0003] background

[0003] Some chronic diseases rely on patient self-administration or home caregiver administration of treatment in an outpatient setting, including the infusion and / or drainage of fluids into and / or from the body via catheters or tubes. Some patients attend dialysis clinics weekly or monthly to perform visual examinations for the development of infections, review patient data (e.g., manual records, overnight cycler data) for patient compliance, and monitor treatment effectiveness by drawing blood. However, patients are typically expected to self-diagnose based on obvious signs of infection and report potential complications to healthcare professionals in a timely manner. Therefore, additional devices, systems, and methods for monitoring patient complications, such as the development of infections, may be desirable. Summary of the Invention [Means for solving the problem]

[0004] overview Described herein are patient monitoring systems, devices, and methods for detecting infections in patients. These systems and methods can, for example, monitor patient fluids and analyze their characteristics to generate patient data that can be presented to the patient and / or healthcare professionals and used to predict infection status. This allows healthcare professionals to prescribe a treatment plan at the onset of an infection to quickly resolve the infection and reduce the need for costly hospitalization. Furthermore, a patient's response to treatment (e.g., an antibiotic regimen) can be remotely monitored over time, thereby updating the treatment plan in real time. The systems and devices described herein are configured to be retrofitted onto a variety of existing dialysis catheters and dialysate infusion systems, including continuous cycling peritoneal dialysis (CCPD) systems and continuous ambulatory peritoneal dialysis (CAPD) systems.

[0005] Generally, a method for predicting an infection in a patient can include illuminating a patient's bodily fluid in a fluid conduit from a plurality of illumination directions. One or more sensors can be used to measure optical properties of the illuminated patient's bodily fluid. Based at least in part on the measured optical properties, the infection status of the patient can be predicted.

[0006] In some variations, the multiple illumination directions can include a first illumination direction and a second illumination direction orthogonal to the first illumination direction. In some of these variations, the predicted infection state of the patient can be based at least in part on one or more 90-degree scattering angle light intensity measurements from one or more sensors. In some of these variations, the predicted infection state of the patient can be further based at least in part on one or more 180-degree attenuation angle light intensity measurements from one or more sensors.

[0007] In some variations, the plurality of illumination directions may include a first illumination direction and a second illumination direction that is offset by 180 degrees from the first illumination direction.

[0008] In some variations, illuminating the patient's body fluid can include illuminating the patient's body fluid at a first wavelength from a first illumination direction and at a first wavelength from a second illumination direction. The first illumination direction and the second illumination direction can extend along a first plane. In some variations, illuminating the patient's body fluid can include illuminating the patient's body fluid at least along the first plane and along a second plane that is substantially parallel to the first plane.

[0009] In some variations, the multiple wavelengths can include a first wavelength between about 800 nm and about 900 nm. In some of these variations, illuminating the patient's body fluid can include sequentially illuminating the patient's body fluid with multiple wavelengths including the first wavelength. In some of these variations, the multiple wavelengths can include a second wavelength between about 400 nm and about 450 nm and a third wavelength between about 500 nm and about 550 nm. In some of these variations, illuminating the patient's body fluid can include sequentially illuminating the patient's body fluid with the third wavelength, the first wavelength, and then the second wavelength. In some of these variations, the multiple wavelengths can include a fourth wavelength between about 230 nm and about 290 nm.

[0010] In some variations, the optical property may include one or more of a light scattering angle and an attenuation detection angle. In some variations, predicting the infection status may include generating an infection score and / or a probability of infection. In some of these variations, estimating the turbidity of the patient's bodily fluid may be based at least in part on the measured optical property. The infection score may be based at least in part on the estimated turbidity. In some of these variations, predicting the infection status may include predicting the infection in response to the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods. In some of these variations, predicting the infection status may include predicting the infection in response to the infection score increasing from a patient baseline value over time. In some of these variations, predicting the infection status may include predicting the infection based on a rate of change of the infection score over time.

[0011] In some variations, predicting the infection status can include predicting infection in response to any one or more of the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods, the infection score increasing from a patient baseline over time, and the infection score having an increasing rate of change over time. In some variations, predicting the infection status can include predicting a probability of infection.

[0012]

[0012] In some variations, the fluid conduit can be coupled to a peritoneal dialysis machine flow path. In some variations, the fluid conduit can be coupled to a peritoneal dialysis machine tubing set. In some variations, the fluid conduit can be coupled to an inlet of a peritoneal dialysis machine tubing set. In some variations, the fluid conduit can be coupled to an outlet of a peritoneal dialysis machine tubing set. In some variations, the fluid conduit can be coupled to a drain line of a peritoneal dialysis cycler tubing set. In some variations, the fluid conduit can be coupled to a drain line extension configured to be coupled to a drain line of a peritoneal dialysis cycler tubing set. In some variations, the fluid conduit can be coupled to a peritoneal dialysis cycler tubing set patient line. In some variations, the fluid conduit can be coupled to a peritoneal dialysis machine tubing set.

[0013] In some variations, a fluid flow rate in the fluid conduit can be estimated based at least in part on the measured optical properties. Illuminating the patient fluid can include activating the illumination based on the estimated fluid flow rate. In some of these variations, determining the fluid flow state can include detecting at least one of an on state and an off state based on the estimated fluid flow rate. Illuminating the patient fluid can include activating the illumination in response to detecting the on state and terminating the illumination in response to detecting the off state.

[0014] In some variations, identifying a false positive fluid flow condition can be based on an estimated fluid flow rate. In some variations, identifying a false positive fluid flow condition can include detecting a predetermined number of pulses in less than each of one or more consecutive measurement periods. In some variations, detecting an ON state can include detecting a predetermined number of pulses in each of one or more consecutive measurement periods. In some variations, the one or more consecutive measurement periods can be separated by a predetermined delay period. In some variations, estimating the fluid flow rate can be based at least in part on applying one or more of a low-pass filter and a high-pass filter to the measured optical property. In some variations, initiating the illuminating of the patient body fluid and measuring the optical property can be based on user input.

[0015]

[0015] In some variations, detecting air bubbles in the fluid conduit may be based at least in part on the optical measurements. In some variations, an indication of a predicted infection status may be provided to a user. In some variations, a particle concentration in the patient's bodily fluid may be predicted based at least in part on the measured optical properties. In some variations, bleeding in the patient may be predicted based at least in part on the measured optical properties. In some variations, an immune response in the patient may be predicted based at least in part on the measured optical properties. In some variations, infection development in patients with ascites drainage may be predicted based at least in part on the measured optical properties. In some variations, fibrin content in the patient's bodily fluid may be predicted based at least in part on the measured optical properties.

[0016]

[0016] Also described herein is a container for use in a fluid conduit. The container can include an inlet portion, an outlet portion, and a generally optically transparent measurement portion between the inlet and outlet portions. The measurement portion can include at least two substantially planar surfaces and a depth registration feature.

[0017] In some variations, the measurement portion can include an interior volume configured to receive a fluid. The interior volume can include rounded corners. In some of these variations, the at least two substantially planar surfaces can include a first plane generally orthogonal to a second plane. In some of these variations, the at least two substantially planar surfaces can include a first plane opposing the second plane. In some of these variations, the measurement portion can include a substantially square cross-section.

[0018] In some variations, at least a portion of the measuring portion may be tapered. In some variations, the measuring portion may comprise one or more of copolyester, acrylonitrile butadiene styrene, polycarbonate, acrylic, cyclic olefin copolymer, cyclic olefin polymer, polyester, polystyrene, Ultem, polyethylene glycol coated silicone, zwitterion coated polyurethane, polyethylene oxide coated polyvinyl chloride, and polyamphiphilic silicone.

[0019] In some variations, an opaque connector may be coupleable to the inlet or outlet. In some of these variations, at least one of the inlet and outlet may be coupleable to a fluid conduit. In some of these variations, one or more of a vent cap, a clamp, and a connector may be coupled to the fluid conduit. In some variations, the container may be coupled to a peritoneal dialysis drain set extension tube.

[0020]

[0020] In some variations, the container can be coupled to a peritoneal dialysis cycler tubing cassette. In some variations, the container can be coupled to an inlet of a peritoneal dialysis cycler tubing cassette. In some variations, the container can be coupled to a peritoneal dialysis drain bag connector. In some variations, the container can be coupled to the proximal end of a peritoneal dialysis drain bag connector. In some variations, the container can be coupled to a drain bag of a urinary catheter or a Foley catheter. In some variations, the container can be coupled to a central venous drain line. In some variations, the container can be coupled to a hemodialysis blood circulation tubing set. In some variations, the container can be coupled to an indwelling catheter. In some variations, the container can be coupled to the proximal end of an indwelling catheter.

[0021] Also described herein is a patient monitoring device that includes a housing. The housing can include a holder configured to releasably receive a portion of a fluid conduit. The at least one illumination source can be configured to illuminate the received portion of the fluid conduit. The at least one optical sensor can be configured to generate a signal. The holder can include engagement features configured to orient the received portion of the fluid conduit at a predetermined rotational and vertical orientation relative to the at least one illumination source and the at least one optical sensor.

[0022] In some variations, the housing can include a light seal. In some variations, the one or more engagement features can be configured to mate with alignment features on the received portion of the fluid conduit to orient the received portion of the fluid conduit. In some variations, the one or more engagement features can include an open slot.

[0023] In some variations, the at least one illumination source can include multiple illumination sources. In some of these variations, the illumination sources can be configured to illuminate in a first illumination direction and a second illumination direction orthogonal to the first illumination direction.

[0024] In some variations, at least two of the illumination sources can be configured to illuminate along a first plane at a first wavelength. In some variations, at least another two of the illumination sources can be configured to illuminate along a second plane that is substantially parallel to the first plane. In some variations, the illumination sources can be configured to illuminate in a first illumination direction and a second illumination direction opposite the first illumination direction.

[0025] In some of these variations, the illumination source can be configured to illuminate in a first illumination direction and a second illumination direction offset by 180 degrees from the first illumination direction. In some of these variations, the illumination source can include a first illumination source configured to emit light at a first wavelength of about 800 nm to about 900 nm. In some of these variations, the illumination source can include a second illumination source configured to emit light at a second wavelength of about 400 nm to about 450 nm. In some of these variations, the illumination source can include a third illumination source configured to emit light at a third wavelength of about 500 nm to about 550 nm. In some of these variations, the illumination source can include a fourth illumination source configured to emit light at a third wavelength of about 230 nm to about 290 nm.

[0026] In some variations, the at least one optical sensor can include multiple optical sensors. In some variations, one or more of the at least one illumination source and the at least one optical sensor can include an anti-reflective coating. In some of these variations, the holder can define a longitudinal axis, and the optical sensors can be spaced apart parallel to the longitudinal axis.

[0027] In some variations, the controller can be configured to generate patient data based at least in part on the signal. In some variations, the patient data can include infection status. In some variations, the device can further comprise a display. In some variations, the device can further comprise a communication device. In some variations, the device can comprise a base. The housing can be offset and spaced from the base. In some variations, the housing can comprise a peritoneal dialysis cycler. In some variations, the housing can comprise a hemodialysis machine. In some variations, the housing can be configured to couple to one or more of a patient platform and a medical cart.

[0028]

[0028] In some variations, the housing can include a peritoneal dialysis machine fluid path. In some variations, the fluid conduit can be coupled to a peritoneal dialysis tubing set. In some variations, the fluid conduit can be coupled to a peritoneal dialysis cycler tubing set. In some variations, the fluid conduit can be coupled to a peritoneal dialysis drain bag connector. In some variations, the fluid conduit can include an inlet portion, an outlet portion, and an optically transparent measuring portion between the inlet and outlet portions, the measuring portion including at least two substantially planar surfaces, a rotational alignment feature, and a depth alignment feature. Equipped with

[0029] In some variations, at least one of the rotational alignment feature and the depth alignment feature can be configured to mate with one or more engagement features of the holder. In some variations, the controller can be configured to generate patient data based at least in part on the signal. In some variations, the controller can be located remotely from the housing. The device can further include a communication device configured to transmit data representing the signal to the controller. In some variations, the controller can be configured to predict an infection score for the patient based at least in part on the signal. In some variations, the controller can be configured to predict an infection status for the patient in response to any one or more of the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods, the infection score increasing from a patient baseline value over time, or the infection score having an increasing rate of change over time. In some variations, the infection status can include a probability of infection. In some variations, the fluid conduit can be configured to receive a patient bodily fluid, and the controller can be configured to estimate a turbidity of the patient bodily fluid based at least in part on the signal, and the infection score is based at least in part on the estimated turbidity.

[0030] In some variations, the controller can be configured to monitor trends in the infection score that predict infection resolution for the patient. In some variations, the controller can be configured to monitor trends in the infection score that predict infection resolution for the patient by predicting infection resolution in response to any one or more of the infection score falling below a predetermined threshold in each of one or more consecutive measurement periods, the infection score decreasing from the patient baseline over time, and the infection score having a decreasing rate of change over time.

[0031] Also described are methods for remotely monitoring a patient, the method may include receiving, at one or more processors, optical property measurements of a patient fluid associated with the patient over a remote communications link. An infection score may be determined to predict infection in the patient. The infection score may be based at least in part on the received optical property measurements. In some variations, the patient may be associated with one of a plurality of patient infection states based at least in part on the determined infection score. In some variations, a user may be notified of the associated patient infection state. In some variations, the user may be prompted to perform one or more predetermined patient treatment actions based on the associated patient infection state. In some variations, the one or more predetermined patient treatment actions may include administering a broad-spectrum antimicrobial to the patient. In some of these variations, the one or more predetermined patient treatment actions may include administering a pathogen-specific antimicrobial (e.g., an antibiotic, an antifungal, an antiviral) to the patient. In some of these variations, one or more predetermined patient care actions may include remotely monitoring trends in an infection score that predicts resolution of the patient's infection (based on the resulting effectiveness of antibiotic treatment).

[0032] In some variations, remotely monitoring the trend of the infection score to predict infection resolution may include predicting infection resolution in response to the infection score declining from a patient baseline over time. In some variations, remotely monitoring the trend of the infection score to predict infection resolution may include predicting infection resolution based on a rate of change of the infection score over time. In some variations, remotely monitoring the trend of the infection score to predict infection resolution may include predicting infection resolution in response to any one or more of the infection score falling below a predetermined threshold in each of one or more consecutive measurement periods, the infection score declining from a patient baseline over time, and the infection score having a declining rate of change over time.

[0033] In some variations, the plurality of patient infection states can include a first patient infection state corresponding to a healthy patient. In some variations, the plurality of patient infection states can include a second patient infection state corresponding to a patient presented to a healthcare provider. In some variations, the plurality of patient infection states can include a third patient infection state corresponding to a patient receiving broad-spectrum antibiotic treatment. In some variations, the plurality of patient infection states can include a third patient infection state corresponding to a patient receiving pathogen-specific antimicrobial treatment. In some variations, the plurality of patient infection states can include a fourth patient infection state corresponding to a hospitalized patient. In some variations, the plurality of patient infection states can include a fifth patient infection state corresponding to a patient transitioned to hemodialysis. In some variations, the predicted infection can be peritonitis. [Brief explanation of the drawings]

[0034] BRIEF DESCRIPTION OF THE DRAWINGS [Figure 1]

[0034] A block diagram of an exemplary variation of a patient monitoring system is shown. [Figure 2]

[0035] 1 shows a schematic diagram of an exemplary variation of a patient monitoring system. [Figure 3A]

[0036] 1 shows a right perspective view of an exemplary variation of a patient monitoring device. [Figure 3B]

[0036] A left perspective view of an exemplary variation of a patient monitoring device is shown. [Figure 4A]

[0037] 1 shows a block diagram of another exemplary variation of a patient monitoring system. [Figure 4B]

[0037] A block diagram of another exemplary variation of a patient monitoring system is shown. [Figure 4C]

[0037] A block diagram of another exemplary variation of a patient monitoring system is shown. [Figure 5A]

[0038] 1 shows a schematic diagram of another exemplary variation of a patient monitoring system. [Figure 5B]

[0038] A schematic diagram of another exemplary variation of a patient monitoring system is shown. [Figure 5C]

[0038] A schematic diagram of another exemplary variation of a patient monitoring system is shown. [Figure 5D]

[0038] A schematic diagram of another exemplary variation of a patient monitoring system is shown. [Figure 6]

[0039] 1 shows a block diagram of an exemplary variation of a patient monitoring device. [Figure 7A]

[0040] 1 shows a perspective view of an exemplary variation of a patient monitoring device. [Figure 7B] FIG. 7B shows an exploded schematic view of the patient monitoring device shown in FIG. 7A. [Figure 7C]

[0040] A perspective view of an exemplary variation of a patient monitoring device in an open configuration coupled to a container is shown. [Figure 7D]

[0040] Figure 1 shows a perspective view of an exemplary variation of a patient monitoring device, also in an open configuration, where the patient monitoring device is coupled to a container attached to a fluid conduit. [Figure 8A]

[0041] 1 shows a perspective view of an exemplary variation of a patient monitoring device in a closed configuration. [Figure 8B]

[0041] A perspective view of an exemplary variation of a patient monitoring device in an open configuration is shown. [Figure 8C]

[0041] A side view of an exemplary variation of a patient monitoring device in an open configuration is shown. [Figure 8D]

[0041] A perspective view of an exemplary variation of a patient monitoring device in a closed configuration is shown. [Figure 9A]

[0042] 1 shows a perspective view of an exemplary variation of a patient monitoring device in an open configuration. [Figure 9B]

[0042] A perspective view of an exemplary variation of a fluid conduit and patient monitoring device in an open configuration is shown. [Figure 9C]

[0042] A perspective view is shown. [Figure 10A]

[0043] 1 is an exploded perspective view of an exemplary variation of a holder for a patient monitoring device. [Figure 10B]

[0043] FIG. 1 is an exploded perspective view of an exemplary variation of an optical sensor configuration of a patient monitoring device. [Figure 10C]

[0043] FIG. 1 is a cross-sectional schematic diagram of an exemplary variation of an optical sensor configuration of a patient monitoring device. [Figure 10D]

[0043] FIG. 10 is a plan view of an exemplary variation of a holder for a patient monitoring device. [Figure 10E]

[0043] FIG. 1 is a perspective view of an exemplary variation of a holder for a patient monitoring device. [Figure 10F]

[0043] FIG. 1 is an exploded perspective view of an exemplary variation of an optical sensor configuration of a patient monitoring device. [Figure 11A]

[0044] 1A-1C are side views of exemplary variations of optical sensor configurations for patient monitoring devices. [Figure 11B]

[0044] FIG. 11B is a cross-sectional view of the optical sensor configuration shown in FIG. 11A along line A:A. [Figure 12A]

[0045] 1 is a schematic perspective view of an exemplary variation of an optical sensor configuration of a container and a patient monitoring device. [Figure 12B]

[0045] FIG. 1 is a schematic perspective view of an exemplary variation of an optical sensor configuration of a container and a patient monitoring device. [Figure 13]

[0046] 1A-1C are schematic diagrams of exemplary variations of optical sensor configurations of patient monitoring devices. [Figure 14A]

[0047] 1A and 1B are schematic diagrams of exemplary variations of optical sensor configurations. [Figure 14B]

[0047] FIG. 1 is a schematic diagram of an exemplary variation of an optical sensor configuration. [Figure 15]

[0048] 1 illustrates an exemplary variation of a graphical user interface of a patient monitoring device. [Figure 16A]

[0049] 10A-10C are perspective views of exemplary variations of drain line extensions. [Figure 16B] FIG. 16B is an exploded perspective view of the drain line extension shown in FIG. 16A. [Figure 17A]

[0050] FIG. 10 is a perspective view of another exemplary variation of a drain line extension. [Figure 17B] FIG. 17B is an exploded perspective view of the drain line extension shown in FIG. 17A. [Figure 17C]

[0050] FIG. 10 is a perspective view of another exemplary variation of the drain line. [Figure 18A]

[0051] 1 is a cross-sectional side view of an exemplary variation of a container. [Figure 18B]

[0051] A side cross-sectional view of an exemplary variation of the container. [Figure 18C]

[0051] A perspective view of an exemplary variation of the container. [Figure 18D]

[0051] A perspective view of an exemplary variation of the container. [Figure 18E]

[0051] A perspective view of an exemplary variation of the container. [Figure 18F]

[0051] A side cross-sectional view of an exemplary variation of the container. [Figure 18G]

[0051] A bottom view of an exemplary variation of the container. [Figure 18H]

[0051] A perspective view of an exemplary variation of the container. [Figure 18I] FIG. 18B is a detailed view of subregion B of FIG. 18H. [Figure 19A]

[0052] 10A and 10B are perspective views of exemplary variations of the cap. [Figure 19B]

[0052] A perspective view of an exemplary variation of the cap. [Figure 19C]

[0052] A side cross-sectional view of an exemplary variation of the cap. [Figure 19D] FIG. 19D is a cross-sectional perspective view of the cap shown in FIG. 19C. [Figure 20]

[0053] 1 is an exemplary graph of estimated turbidity plotted over time. [Figure 21A]

[0054] 1 shows an exemplary infection detection graph of infection scores plotted over time. [Figure 21B]

[0054] An exemplary infection detection graph of cell concentration and infection score plotted over time. [Figure 22A]

[0055] 1 is an exemplary fluid flow graph and corresponding frequency response plot of optical sensor measurements plotted over time. [Figure 22B]

[0055] An exemplary fluid flow graph and corresponding frequency response plot of optical sensor measurements plotted over time. [Figure 23A]

[0056] 1 is an exemplary error measurement graph for white blood cells; [Figure 23B] 10 is an exemplary error measurement graph for red blood cells. [Figure 23C]

[0056] An exemplary error measurement graph for a protein. [Figure 23D]

[0056] An exemplary error measurement graph for triglycerides. [Figure 24]

[0057] 1 is an exemplary graph of optical sensor measurements plotted over time to show an air bubble. [Figure 25A]

[0058] 1 is a schematic side view of an exemplary variation of a cassette for use with a peritoneal dialysis cycler having an optical measurement region. FIG. [Figure 25B]

[0058] A schematic top view of an exemplary variation of a cassette having an optical measurement area interface for an optical sensor of a peritoneal dialysis cycler. [Figure 26]

[0059] 10 is an exploded perspective view of an exemplary variation of a container disposed within a holder of a patient monitoring device. FIG. [Figure 27A]

[0060] FIG. 1 is a schematic diagram of an exemplary clinical workflow in a conventional standard of care. [Figure 27B]

[0060] FIG. 1 is a schematic diagram of an exemplary clinical workflow using the systems and methods described herein. [Figure 28]

[0061] 1 is a schematic diagram of a system for patient monitoring including one or more patient monitoring devices such as those described herein. [Figure 29]

[0062] FIG. 1 is a schematic diagram of patient stages in an exemplary variation of a patient state diagram. [Figure 30]

[0063] 1 is an exemplary graphical user interface (GUI) for use in a system for patient monitoring. [Figure 31] 1 is an exemplary graphical user interface (GUI) for use in a system for patient monitoring. [Figure 32] 1 is an exemplary graphical user interface (GUI) for use in a system for patient monitoring. [Figure 33] 1 is an exemplary graphical user interface (GUI) for use in a system for patient monitoring. [Figure 34] 1 is an exemplary graphical user interface (GUI) for use in a system for patient monitoring. [Figure 35] 1 is an exemplary graphical user interface (GUI) for use in a system for patient monitoring. DETAILED DESCRIPTION OF THE INVENTION

[0035] Detailed Description

[0064] Described herein are methods, systems, and devices for monitoring patient fluids. The methods described herein can predict infection in a patient. In some variations, the systems and devices can monitor patients with end-stage renal disease who are prescribed peritoneal dialysis. For example, the systems described herein can include a patient monitoring device and a fluid conduit (e.g., a disposable drain line extension) coupled between a drain line tubing of a peritoneal dialysis overnight cycler and a drain container, such as a toilet. In some variations, the fluid conduit can include a container configured to be releasably received within the housing of the patient monitoring device. The fluid conduit can be separate from or integrated with another fluid conduit (e.g., a drain line of a tubing set, another drain line extension, an indwelling catheter, a cassette). The patient monitoring device can include an optical sensor configured to measure the patient fluid passing through the container and generate a signal corresponding to one or more properties of the patient fluid flowing through the container. For example, the measured characteristics can be used to predict a patient's infection state (e.g., probability of infection), estimate particle concentration in the patient's bodily fluid, determine the operating state of a cycler (e.g., flow on, flow off), fluid flow through a fluid conduit, and / or detect noise components (e.g., air bubbles) in the patient's bodily fluid.

[0036]

[0065] These systems and devices can be used in outpatient or home settings for continuous monitoring of complications, including, but not limited to, infections, catheter leaks, and catheter blockages. Patient compliance with prescribed treatment can be monitored and communicated to the patient and / or healthcare provider. Treatment effectiveness can also be monitored remotely over time to indicate the patient's response to the prescribed treatment. Thus, healthcare providers can monitor patients more frequently than may be practical with in-person visits alone. Infections can be predicted and quantified in real time, allowing healthcare providers to address complications before the problem worsens and becomes more difficult to resolve. For example, if infections are detected and treated early, they can be treated with an antibiotic regimen that can prevent patient hospitalization. Resolution of infections can be monitored at the initiation of antibiotic treatment and updated at predetermined intervals. For example, if treatment effectiveness is positive, the prescribed medical therapy (e.g., drug, dosage, frequency) can be immediately updated to limit the patient's antibiotic intake to the minimum required to resolve the infection. In some variations, the systems, devices, and methods disclosed herein can include one or more of the systems, devices, and methods of treatment administration and sample collection described in International Patent Application No. PCT / US2018 / 065853, filed December 14, 2018, the contents of which are incorporated herein by reference in their entirety. For example, tools can automate antimicrobial administration and / or culture sample collection (e.g., based on an algorithmic determination of an infection score, as described below), which can shorten the time to response from the patient and / or healthcare provider, thereby improving patient outcomes.

[0037]

[0066] In some variations, the patient monitoring system may include a sensor configured to monitor fluid flowing from a peritoneal dialysis machine ("cycler") to a drain container. FIG. 1 shows a block diagram of a patient monitoring system (100) including a cycler, a drain line (120), a sensor (130), a fluid conduit (140), and a drain container (150). In some variations, the cycler (110) may be configured to pump patient fluid (e.g., dialysate) to the drain line (120). The drain line (120) may be fluidly coupled to the fluid conduit (140), and the drain container (150) (e.g., a toilet bowl, drain pan, washbasin, waste bucket, waste bag, bathtub, sink, etc.) may be configured to receive the patient fluid. A portion of the fluid conduit (140) can be received by and aligned with the sensor (130), as described in more detail herein, to measure the optical properties of the patient's bodily fluid passing through the fluid conduit (140).

[0038]

[0067] FIG. 2 shows a schematic diagram of a patient monitoring system (200) that can be used, for example, in a patient's home or in a clinic environment. The patient monitoring system (200) can include a cycler (210), a drain line (220), a patient monitoring device (230), a fluid conduit (240), and drain containers (250, 260). In some variations, the cycler (210) can be configured to pump patient fluid (e.g., dialysate) into the drain line (220). The drain line (220) can be fluidly coupled to the fluid conduit (240), and a drain container, such as a toilet bowl (250) or bag (260), can be configured to receive the patient fluid. A portion of the fluid conduit (140) can be received by and aligned with the patient monitoring device (230). For example, the patient monitoring device 230 may include an optical sensor configured to measure optical properties of the patient's bodily fluid passing through the fluid conduit 240. In some variations, an optically transparent container may be received and aligned with the patient monitoring device 230. The patient monitoring device 230 may be a durable component including a sensor configured to measure and analyze the patient's bodily fluid in a contactless manner and notify one or more of the patient and a healthcare provider of the analysis. At least in part, because the fluid conduit 240 and patient monitoring device 230 are retrofitted to conventional dialysis equipment, use of the fluid conduit 240 and patient monitoring device 230 in conjunction with the cycler 210 system may add a relatively small amount of time and number of steps to the patient's dialysis setup and maintenance routine while providing real-time patient monitoring of the patient's bodily fluid for infection detection and fluid properties.

[0039]

[0068] In some variations, the fluid conduits and / or containers may be disposable components that can be replaced at predetermined intervals (e.g., after a dialysis session, daily, weekly, etc.). The fluid conduits and / or containers may serve as drain line extensions of a predetermined length and may include one or more connectors configured to fluidly couple to conventional tubing connectors. For example, the fluid conduits may extend the drain line to a predetermined length to provide a fluid connection between a cycler (210) located in a bedroom and a toilet (250) or other drainage container located in a bathroom. In some variations, the patient monitoring device (230) may be configured to be attached to one or more of a patient platform, a medical cart, and medical equipment (e.g., an IV pole). The patient platform may include, for example, a surface for a patient (e.g., a bed, a chair, a table, a hospital bed, an intensive care unit bed, etc.).

[0040]

[0069] Methods that can be implemented using the systems and devices described herein are also described. In some variations, a method for predicting infection in a patient can predict the infection status of a patient based on estimated turbidity of the patient's bodily fluid. For example, infection may generally be correlated to the concentration of one or more particle types, such as white blood cells, in the patient's bodily fluid. The concentration of white blood cells and / or other particle types can be estimated based on various optical parameters (e.g., turbidity) of the patient's bodily fluid, estimated using methods and devices such as those described herein. The estimated turbidity can be estimated based on measured optical properties of the patient's bodily fluid. For example, the optical properties can include one or more of optical scattering light intensity measurements and obscuration light intensity measurements.

[0041]

[0070] In some variations, the composition of the patient's body fluid can be estimated based on the measured optical properties of the patient's body fluid. In particular, the type and concentration of particles in the patient's body fluid can be estimated based on the optical measurements. The particles may include, for example, white blood cells, red blood cells, proteins, and triglycerides. For example, the optical properties can be measured at multiple wavelengths. In another example, the composition can be estimated based on the optical properties of a static patient's body fluid measured over a period of time.

[0042]

[0071] In some variations, a patient's infection score can be predicted based on a set of measured optical properties generated over time. For example, the infection score can be compared to a predetermined threshold or patient baseline to predict the state of the infection, such as onset and resolution. Analyzing the set of infection scores over time (as a proxy for the rate of change of the measured optical properties) can reduce false positives, thereby improving the sensitivity and specificity of patient diagnosis and enabling prediction of the patient's infection state (e.g., probability of infection).

[0043]

[0072] In some variations, the patient infection status can include a first infection status corresponding to an infected patient and a second infection status corresponding to a non-infected patient. In some variations, the patient infection status can correspond to a probability that the patient is infected. In some variations, the infection probability can correspond to an infection score. For example, the patient infection status can correspond to a first infection status when the infection probability is at or above a predetermined threshold (e.g., 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, etc.) and can correspond to a second infection status when the infection probability is below the predetermined threshold or another suitable different threshold (e.g., a first threshold of infection probability can be used to determine the infection status and a second threshold of infection probability can be used to determine the non-infectious status).

[0044]

[0073] In some variations, the patient monitoring device can measure the optical properties of the fluid based on the operating state of the cycler. For example, a cycler in a patient monitoring system can perform a step of pumping patient fluid into a drain line (drain cycle) and then stop the pump so that the fluid is stationary in the drain line during a step in which the cycler is either pumping the fluid into the patient line (infuse cycle) or the cycler is stopped while the fluid dwells in the patient (dwell cycle). In some variations, the patient monitoring device can obtain sensor measurements and analyze the measurements according to the operating state of the cycler. For example, sensor measurements can be performed during the drain cycle of the cycler and turned off during the infuse and / or dwell cycles. Additionally or alternatively, optical properties of fluid flow in a continuous ambulatory peritoneal dialysis (CAPD) system can be measured. Additionally or alternatively, different turbidity algorithms can be applied to one or more of the drain cycle, infuse cycle, and dwell cycle. As described in more detail herein, a method for estimating the fluid flow rate (e.g., pump on / off) of a patient's bodily fluid can correspond to the operating state of the cycler. The estimated fluid flow rate can be used to ensure accurate fluid sensing, identify fluid characteristics for each drainage (if a treatment cycle has more than one drainage), reduce energy consumption, and extend the life of the patient monitoring device. In some variations, the fluid flow rate can include a set of fluid flow states. For example, a first fluid flow state can include continuous fluid flow through the fluid conduit (e.g., continuous fluid pumping through a drain line), and a second fluid flow state can include discontinuous fluid flow through the fluid conduit (e.g., no fluid pumping through a drain line). In some variations, the fluid flow rate can include a volume of fluid passing through a given cross-sectional area per unit time.

[0045]

[0074] Optical measurements of fluids can be affected by discrete noise sources, such as air bubbles or large particulate matter. In some variations, methods can be implemented to detect air bubbles, which can then be used to eliminate such signal data to increase the signal-to-noise ratio of the optical measurements. Other noise sources, such as fibrin particles, patient bleeding, and ascites fluid drainage, can be detected and eliminated from the optical measurements used for fluid analysis.

[0046]

[0075] The systems, devices, and methods described herein can be used in a variety of different dialysis therapies to treat renal failure. For example, dialysis therapies can include any and all therapies that utilize fluids (e.g., a patient's blood, dialysate) to remove waste, toxins, and excess water from a patient's body. Such therapies can include hemodialysis, hemofiltration, hemodiafiltration (HDF), and peritoneal dialysis, including automated peritoneal dialysis, continuous ambulatory peritoneal dialysis, and continuous flow peritoneal dialysis. Such therapies can also include, where applicable, both intermittent therapies and continuous therapies used for continuous renal replacement therapy. Patients treated with dialysis therapies can include patients with acute renal failure as well as patients with chronic renal failure, whether due to renal or non-renal disease.

[0047]

[0076] The terms "transparent" and "clear," as well as variations thereof, are used throughout this specification, however, it should be understood that these terms do not require complete or 100% transmission of light.

[0048] Patient Monitoring Systems

[0077] The patient monitoring systems described herein can be configured to monitor patient fluids and predict patient infections and / or other patient fluid characteristics. In some variations, the patient monitoring systems can be configured to provide additional functionality to current peritoneal dialysis systems. For example, the patient monitoring system can include a fluid conduit configured to extend the length of one or more of a drain line, tubing, and catheter. The patient monitoring device can be configured to analyze the patient fluid in the fluid conduit to monitor infections, measure turbidity, estimate fluid composition, and / or detect fluid flow, etc. The patient monitoring device can also output the results of the fluid analysis to the patient and / or healthcare provider, allowing for monitoring the onset and resolution of infections.

[0049]

[0078] In further variations, the patient monitoring systems described herein can include a patient monitoring device (e.g., a durable electromechanical system) configured to engage with a fluid component (e.g., a container, a fluid conduit). For example, the fluid component can include a disposable container (e.g., a fluid conduit, a cartridge, a drain line, a tubing, an indwelling catheter) and can be configured to removably engage with a patient monitoring device (e.g., a housing, a holder, an optical sensor arrangement, a display screen, a wireless transmitter, etc.). In some variations, the patient monitoring device can include at least one sensor and a processor that measures the patient's bodily fluid and predicts patient infection. The fluid component can include fluid-contacting components, and the patient monitoring device can include a set of non-fluid-contacting components. The fluid component can be disposable. For example, the fluid component can be replaced at predetermined intervals (e.g., daily, weekly) and / or on a predetermined basis (e.g., patient infection event). Disposable fluidic components may be useful for short-term use, for example, because biofouling within the fluid conduit over time can obscure (e.g., cloud) the optical measurement area, resulting in inaccurate measurements and an unacceptable number of false-positive and / or false-negative patient infection outputs. Durable components can provide long-term functionality when properly maintained (e.g., cleaned). In some variations, fluid properties such as light scattering, light absorption, attenuation detection angle, and / or fluid flow rate can be measured in a non-fluid-contact manner using durable components without separate sensors in the fluidic components. As a result, manufacturing of fluidic components can be simplified and provided at reduced cost for mass production. Durable components can include a set of structures, materials, and techniques configured to provide high optical quality for optical sensor measurements. For example, durable components can include structures configured to reduce ambient light leakage and refraction while being suitable for the draft angle requirements and high manufacturing tolerances associated with injection molding.In some variations, the fluidic components can be formed by one or more of, for example, injection molding, machining, solvent bonding, interference / press-fit assembly, ultrasonic welding, and 3D printing techniques. For example, separate portions of the fluidic components can be injection molded and attached using a solvent to further reduce manufacturing costs. In some variations, the fluidic components can be incorporated into the drain line set by solvent bonding and / or adhesives to further reduce system complexity. Furthermore, the fluidic components can be configured to attach to an existing drain line set to provide additional functionality to an existing peritoneal dialysis system. Additionally or alternatively, disposable containers, such as cartridges, tubing, catheters, drain lines, etc., can be equipped with an optically transparent measurement portion as described herein.

[0050]

[0079] 3A and 3B are perspective views of a patient monitoring system (300) including a first fluid conduit (310), a second fluid conduit (320), and a patient monitoring device (330). As described in further detail herein, the fluid conduits can be releasably coupled to the patient monitoring device, and the fluid conduits can be disposable components that are replaced at predetermined intervals. Use of the patient monitoring device can add only a few additional steps to the setup procedure of a conventional peritoneal dialysis cycler system for administering continuous cyclic peritoneal dialysis (CCPD). For example, the fluid conduits can be coupled and uncoupled from a drain line and waste container (not shown in FIG. 3) similar to a conventional drain line extension, thus adding no additional setup time for the patient. Furthermore, one or more engagement features of the patient monitoring device can guide assembly of the fluid conduit through interaction with one or more alignment features (e.g., rotational and / or depth alignment features) of the fluid conduit to prevent misalignment, thus reducing patient error and compliance issues. Once the fluid conduit is coupled to the patient monitoring device, measurements and analyses of the patient's bodily fluid can be performed and output to the patient's healthcare provider without further patient action. Removal of the fluid conduit simply involves reversing the assembly steps. Thus, the patient monitoring device adds numerous quantitative patient monitoring capabilities while being simple and efficient to set up, operate, and maintain.

[0051]

[0080] In some variations, the patient monitoring system (300) can include an input device (e.g., a switch, a push button, a voice command) configured to activate the optical sensor and / or predict the patient's infection status. The patient can initiate an optical sensor measurement in conjunction with fluid drainage. The patient monitoring device (300) can be attached to or integrated with, for example, one or more of an IV pole or a medical cart. For example, the patient monitoring system (300) can be used to administer continuous ambulatory peritoneal dialysis (CAPD).

[0052]

[0081] Additionally or alternatively, one or more components of the patient monitoring devices described herein may be incorporated into other devices. FIG. 4A shows a block diagram of a patient monitoring system (400) including a cycler (410), a cycler tubing set drain line (430), and a drain container (440). The cycler (410) may include a sensor (420) as described herein. In some variations, the cycler (410) may be configured to pump patient fluid (e.g., dialysate effluent) into the drain line (430). The drain line (420) may be fluidly coupled to the drain container (440). The sensor (420) may measure optical properties of the patient fluid flowing through the cycler (410). For example, the sensor (420) may be configured to measure the optical properties of an optically transparent measuring portion of a disposable cycler cassette.

[0053]

[0082] In some variations, a cassette for a peritoneal dialysis cycler can be configured to enable measurement of optical properties of a patient's body fluid (e.g., dialysate effluent) flowing therethrough. FIG. 25A is a schematic diagram of a tubing set cassette (2500) for use with a peritoneal dialysis cycler. Additional fluid channels are typically required to inject and evacuate fluids from multiple fluid sources into and from the patient's body, but for clarity, only a subset of the fluid channels are shown. The cassette (2500) can include an inlet (2510), an optical measurement region (2512), a first reservoir (2520), a second reservoir (2522), and an outlet (2530). The inlet (2510) can be configured to connect directly to an indwelling patient catheter and receive the patient's body fluid (e.g., dialysate effluent) and infuse fluid (e.g., fresh dialysate) into the indwelling catheter, and can be fluidly coupled to the first reservoir (2520). The inlet (2510) can include a generally optically transparent measurement portion (2512) having one or more optical properties and / or structural features similar to the optical measurement portion of the containers described herein. In addition to measuring patient output fluid, the optical measurement portion (2512) can be configured to measure properties of the infusion fluid (e.g., fresh dialysate) as a means of verifying fluid quality (e.g., cleanliness). In another variation, the infusion fluid measurements can be used to calibrate the optical measurements with a reference measurement. Thus, measuring optical properties of the patient fluid can include subtracting the reference measurement from the measured optical signal. This calculation can reduce one or more sources of measurement variability, including optical variations in the infusion fluid, optical variations in the optical measurement portion (including deposition over time), and variations in the illumination source (e.g., light intensity) and / or optical sensor (e.g., electrical noise).

[0054]

[0083] FIG. 25B is a schematic cross-sectional top view of the cassette 2500 shown in FIG. 25A , including an optical measurement unit 2512 interface to an optical sensor arrangement 2550 of a peritoneal dialysis cycler. The optical sensor arrangement 2550 can include a pair of illumination sources 2560, 2562 and optical sensors 2570, 2572. The optical sensor arrangement 2550 can be configured to measure one or more optical properties of a patient's bodily fluid and to provide illumination from multiple illumination directions. A first illumination source 2560 can illuminate the optical measurement unit 2512 in a first illumination direction, and a second illumination source 2562 can illuminate the optical measurement unit 2512 in a second illumination direction orthogonal to the first illumination direction. Alternatively, the first illumination source can have a first illumination direction that is offset 180 degrees from the second illumination direction such that the illumination sources can direct light in opposite directions. In some variations, the patient fluid can be illuminated from multiple non-parallel illumination directions. For example, a first illumination direction can have an offset from a second illumination direction of greater than about 0 degrees to about 180 degrees. In some variations, the first illumination source (2560) and the second illumination source (2562) can be configured to provide illumination at the same wavelength.

[0055]

[0084] In FIG. 25B, a first optical sensor (2570) and a second optical sensor (2572) can be configured to generate signals corresponding to measurements of optical properties of the illuminated patient's body fluid. The first optical sensor and the second optical sensor can be, for example, photodiodes. The optical sensors can be configured to measure one or more of light scattering and attenuation detection angles (e.g., absorption, shielding). For example, the optical sensors can be configured to measure properties of the illuminated patient's body fluid at an attenuation / absorption / shield angle (approximately 180 degrees), a forward scattering angle (greater than about 90 degrees, less than 180 degrees), a side scattering angle (approximately 90 degrees), and a back scattering angle (less than about 90 degrees, greater than or equal to about 0 degrees). In Figure 25B, the first optical sensor (2570) faces the first illumination source (2560) (the first optical sensor and first illumination source are on opposite sides of the optical measurement portion (2512)), and the second optical sensor (2572) faces the second illumination source (2562) (the second optical sensor and second illumination source are on opposite sides of the optical measurement portion (2512)). Alternatively, the first optical sensor (2570) may be generally orthogonal to the first illumination source (2560), and the second optical sensor (2572) may be generally orthogonal to the second illumination source (2562). The turbidity of the patient's bodily fluid can be estimated based on the measured optical properties and turbidity equations described in more detail herein.

[0056]

[0085] The cassette may include one or more ambient light blocking features configured to enhance optical measurement of the patient's bodily fluid. Figure 5A shows a schematic diagram of a patient monitoring system (500) that may be used, for example, in a patient's home. The patient monitoring system (500) may include a cycler (510), a drain line (530), a drain line extension (540), and a drain container (550, 560). The cycler (510) may include a sensor (520). In some variations, the cycler (510) may be configured to pump the patient's bodily fluid into the drain line (530). The drain line (530) may be fluidly coupled to the drain line extension (540) and a drain container, such as a toilet bowl (550) or bag (560), configured to receive the patient's bodily fluid.

[0057]

[0086] In some variations, the sensor (420) can be coupled to a drain line extending from the cycler (e.g., coupled to a drain prong of the cycler's cassette). For example, FIG. 4B shows an exemplary configuration of a patient monitoring system (400) including an optically transparent measuring portion (450), a sensor (420), a cycler (410), a cycler tubing set drain line (430), and a drain container (440). For example, an indwelling catheter or tubing set can include the optically transparent measuring portion (450), which can be releasably coupled to one or more of the sensor (420) and the disposable cycler cassette of the cycler (410). For example, the optically transparent measuring portion (450) can be positioned along the proximal end of the indwelling catheter. The optical properties of the patient's bodily fluid flowing through the measuring portion (450) can be measured by the sensor (420). In some variations, the patient's body fluid can flow through a measurement portion (450) and then through a cycler (410). The cycler (410) can be configured to receive and pump the patient's body fluid (e.g., dialysate effluent) into a drain line (430). The drain line (420) can be fluidly coupled to a drain container (440).

[0058]

[0087] 4C shows an exemplary configuration of a patient monitoring system (400) including an optically transparent measuring portion (450), a sensor (420), a cycler (410), a cycler tubing set drain line (430), and a drain container (440). For example, the tubing set can include the optically transparent measuring portion (450), which can be releasably coupled to one or more of the sensor (420) and the disposable cycler cassette of the cycler (410). Optical properties of the patient's bodily fluid flowing through the measuring portion (450) can be measured by the sensor (420). In some variations, the patient's bodily fluid can flow through the cycler (410) and then through the measuring portion (450), which is coupled in-line to the drain line (430). The drain line (430) can be fluidly coupled to the drain container (440).

[0059]

[0088] FIG. 5B shows a schematic diagram of a patient monitoring system (500) that can be used, for example, in a patient's home. The patient monitoring system (500) can include a catheter or tubing set (570), a sensor (520), a cycler (510), a drain line (530), a drain line extension (540), and a drain container (550, 560). The sensor (520) can be releasably coupled to the tubing set (570) upstream of the cycler (510). In some variations, the cycler (510) can be configured to pump patient fluid into the drain line (530). The drain line (530) can be fluidly coupled to the drain line extension (540) and a drain container, such as a toilet bowl (550) or bag (560), configured to receive the patient fluid.

[0060]

[0089] Figure 5C shows a schematic diagram of a patient monitoring system (500) that can be used, for example, in a patient's home. The patient monitoring system (500) can include a cycler (510), a sensor (520), an optically transparent measuring portion (450), a drain line (530), a drain line extension (540), and a waste container (550, 560). The sensor (520) can be releasably coupled to the optically transparent measuring portion (450) downstream of the cycler (510). In some variations, the optically transparent measuring portion (450) can be coupled to the drain line extension (540) as a continuous fluid path, as shown in Figure 5D.

[0061] Patient Monitoring Devices

[0090] The patient monitoring devices described herein can be configured to monitor patient fluids and predict patient infections and / or other characteristics of the patient fluids. For example, the patient monitoring devices can be configured to optically measure one or more characteristics of the patient fluid flowing through a fluid conduit coupled to the patient monitoring device. Additionally, the patient fluid in the fluid conduit can be analyzed to monitor infections, measure turbidity, estimate fluid composition, and detect fluid flow. The patient monitoring devices can also output fluid analysis results to the patient and / or healthcare provider, allowing for monitoring the onset and resolution of infections. In some variations, the patient monitoring devices described herein can be configured for use in a dialysis fluid infusion system or can comprise a stand-alone point-of-care fluid sample analyzer. For example, in some variations, the fluid container can be configured as a vial to hold a static, predetermined volume of fluid for analysis using the patient monitoring device. Furthermore, in some variations, the patient monitoring device can be configured to fit compactly on a surface (e.g., a table, a desk) and can be used to analyze patient fluids using any of the methods described herein. For example, the patient monitoring device need not include a base (eg, a stand) to reduce the volume of the device.

[0062]

[0091] FIG. 6 shows a block diagram of a patient monitoring device (600) including a sensor arrangement (610), a display (620), a controller (630), a communication device (640), and a power source (650). The optical arrangement (610) can include an optical source (612) (e.g., an illumination source) and an optical sensor (614). The optical source (612) can be configured to illuminate the patient fluid in the container and / or fluid conduit. The optical sensor (614) can be configured to measure optical properties of the illuminated patient fluid. The controller (630) can include a processor (632) and memory (634) configured to process, analyze, and / or store measured signal data and to determine when flow indicates a drainage cycle and to further determine when the patient fluid should be measured. For example, the controller (630) can be configured to generate patient data based at least in part on the signal measured by the optical sensor (614). The patient data can include, for example, infection status (eg, probability of infection).

[0063]

[0092] FIG. 7A shows a semi-transparent perspective view of a patient monitoring device 700. FIG. 7B shows an exploded schematic view of the patient monitoring device 700, including a housing 702 (e.g., enclosure), a base 704 (e.g., stand), an optical sensor arrangement 710, a display 720, a controller 730, a communication device 740 (e.g., antenna, LTE or other cellular modem), and a holder 750 (e.g., fluid conduit interface). The patient monitoring device 700 may be small enough to fit on a table or nightstand. In some variations, the base 704 may elevate the housing 702 above a resting surface. That is, the housing 702 may be offset and spaced from the base 704. The spacing between the housing (702) and the base (704) can allow sufficient space to allow, for example, one or more of a fluid conduit (e.g., a drain line) and a disposable container (e.g., a drain bag) to be positioned directly below the housing (702) as shown in Figures 8A, 8B, and 9B. The offset can be, for example, from about 5 cm to about 30 cm.

[0064]

[0093] Figures 7C and 7D show perspective views of the patient monitoring device 700 with the housing 702 in an open configuration. A container 750 is removably held within the housing 702 and aligned with the optical sensor arrangement 710. Figure 7D shows the container 750 coupled to a first fluid conduit 760 and a second fluid conduit 762, while Figure 7C shows the container 750 without the fluid conduits 760 for clarity. As described in more detail herein, the container 750 and the housing 702 can include a set of mating features configured to direct the relative orientation and / or depth of the container 750 and the housing 702 relative to one another so that the container 750 can be inserted into the housing 702 in a single direction, depth, and orientation.

[0065]

[0094] 8A-8D show various views of a variation of a patient monitoring device (800). The patient monitoring device (800) may include a housing (810), a holder (820), a display (850), and a stand (860). A fluid conduit (830) may be fluidly coupled to the outlet of the cycler tube set drain line (840). As described in more detail herein, the fluid conduit (830) may be engaged with the holder (820). As shown in FIG. 8B, the base (860) may be offset and spaced from the housing (810) to elevate the fluid conduit (830) relative to the drain line (840). For example, the fluid conduit (830) may be held substantially vertical during one or more of priming and fluid flow to facilitate degassing of the fluid conduit (830), thereby reducing the presence of air bubbles in the optical measurement portion of the fluid conduit (830) during measurement. In particular, the fluid conduits can be routed so that the fluid is configured to flow in a low-to-high direction (i.e., generally upward) following the direction of air buoyancy, which promotes degassing of the fluid conduits (830).

[0066]

[0095] Figures 8A and 8D show the patient monitoring device 800 in a light-tight door-closed configuration, and Figures 8B and 8C show the patient monitoring device 800 in a light-tight door-open configuration. The housing 810 can be configured to transition between the door-closed configuration (Figures 8A, 8D) and the door-open configuration (Figures 8B, 8C). In the door-closed configuration, the housing 810 and door 811 can form an ambient light seal configured to reduce ambient light penetration into the optical measurement region of the fluid conduit 830. In some variations, the housing 810 can further include a door 811 and hinge 812 configured to open and close the housing 810. The door 811 in the closed configuration can form the top, bottom, and sidewalls of the light seal. For example, the door 811 can form the bottom of a light seal that seals the outlet of the drain line 840 and reduces ambient light penetration through the drain line 840. FIG. 8C is a side view of the patient monitoring device 800 in a door-open configuration. The door 811 can be configured to seal against a portion of the cap 834 to form the top of the light seal. The door 811 can include alignment features that can be configured to ensure that the door 811 is fully closed only when the cap 834 is fully inserted into and engaged with the holder 820. For example, in some variations, one or more alignment features on the door 811 and / or the container 832 or cap 834 can be positioned such that the door can be fully closed only when the container 832 and cap 834 are correctly oriented in a single, predetermined orientation, thereby providing confirmation that the container and cap are correctly oriented. When the container (832) is engaged with the holder (820) in a predetermined orientation relative to the holder (820), the closed door (811) can prevent the cap (834) and container (832) from moving vertically (or being lifted out of the housing (810)), and the alignment features of the holder (820) prevent the container (832) from rotating, tilting, being displaced laterally, or being pushed downward.

[0067]

[0096] As shown in FIG. 8D, the door (811) can include a switch (e.g., latch, handle) (813) configured to allow the patient to open and securely close the door (811). For example, the switch (813) can include a spring-loaded mechanism and / or a magnet. In some variations, the door (811) and / or other portions of the housing can include a sensor (e.g., a Hall effect sensor, a switch, a contact sensor, an optical sensor, etc.) configured to generate a door signal indicating the open or closed state of the housing (810).

[0068]

[0097] Figures 9A-9C show various views of a patient monitoring device 900. The patient monitoring device 900 may include a housing 910, a door 911, a hinge 912, a holder 920, a slot 924, an optical sensor 926, a display 950, and a stand 960. As shown in Figure 9B, a fluid conduit 930 may be fluidly coupled to the outlet of the drain line 940. The fluid conduit 930 may include a container 932 and a cap 934. Figures 9A and 9B show the patient monitoring device 900 in an open configuration. Figure 9C shows a patient monitoring device 900' similar to the device shown in Figures 9A and 9B, but with a different location for the tubing routing section 922'. The patient monitoring device 900' is shown in a closed configuration.

[0069]

[0098] 10A and 10E are perspective views of a holder 1010 of a patient monitoring device 1000 configured to receive and engage a portion of a fluid conduit (e.g., a container) (not shown for clarity) in a predetermined orientation relative to at least one set of illumination sources 1040 and at least one set of optical sensors 1050. The illumination sources 1040 can be configured to illuminate the received portion of the fluid conduit, and the optical sensors 1050 can be configured to generate a signal, such as an optical property measurement, based on the illuminated patient fluid. FIGS. 10B and 10C show an optical sensor configuration including an illumination housing 1011, a collimator 1032, a lens 1030 (e.g., an aspheric lens), a lens placement O-ring 1033, and illumination sources 1042, 1044, and 1046. The illumination housing 1011 can define a set of apertures 1013.

[0070]

[0099] The holder (1010) can define a cavity (1002) having a generally rectangular (e.g., square) cross-sectional shape configured to receive a portion of a fluid conduit having a generally rectangular (e.g., square) cross-sectional shape. The holder (1010) can further define an engagement feature (1012) (e.g., a slot, a slit) configured to orient the received portion of the fluid conduit at a predetermined rotational orientation relative to the illumination source (1040) and the optical sensor (1050). For example, the engagement feature (1012) can extend along the longitudinal axis of the holder (1010) (see FIG. 10E) and can define an open slot disposed at an edge of the generally rectangular cross-sectional shape. The slot allows one or more of the container, the fluid conduit, and the drain line to be assembled and removed from the holder (1010) without separating any of the drain line components. The engagement feature (1012) can facilitate or ensure one-way insertion of the fluid conduit into the holder (1010). In some variations, as described further herein, the holder (1010) can additionally or alternatively include a second engagement feature (e.g., a shoulder, lip, protrusion, etc.) configured to orient the received portion of the fluid conduit at a predetermined depth relative to the illumination source (1040) and the optical sensor (1050).

[0071]

[0100] 26 is an exploded perspective view of a container 2610 positioned within a holder 2620 of a patient monitoring device 2600. The holder 2620 can include an engagement portion 2622, such as a slot, extending along the longitudinal axis of the holder 2620. The holder 2620 can be configured to couple to one or more portions of a housing 2630 of the patient monitoring device 2600. An optical sensor arrangement 2640 can be coupled to the holder 2620. To remove the container 2610 from the holder 2620, a CCPD tubing set, including drain lines and / or fluid conduits (not shown) coupled to the container 2610, can be lifted out of the holder 2620 and moved laterally through the slot 2622 without separating any components of the tubing set.

[0072]

[0101] As shown in the perspective views of FIGS. 12A and 12B , the holder 1200 can be configured to releasably receive a portion of the container 1250. The container 1250 can include a rotational alignment feature 1252 configured to engage with an engagement feature 1230 (e.g., a slot, a slit) of the holder 1200 so that the container 1250 is secured to the holder 1200 in a single position and rotationally aligned. For example, the engagement feature 1230 can be configured to orient the received portion of the fluid conduit 1250 by mating with the alignment feature 1252 of the received portion of the fluid conduit 1250. Additionally or alternatively, as described in more detail below, the container 1250 can include a depth alignment feature configured to engage with a second engagement feature to position the container 1250 at a predetermined depth.

[0073]

[0102] For example, in some variations, the alignment feature 1252 can comprise a protrusion having a shape configured to form an interference fit with the engagement feature 1230 of the holder 1200. The alignment feature 1252 can include a taper that allows the container 1250 to slide and / or self-align within the engagement feature 1230. Figure 12B is a perspective view of the holder 1200 and container 1250 from a perspective opposite that of Figure 12A. The sidewall of the holder 1200, shown in the foreground of Figure 12B, does not include a corresponding engagement feature 1230. Thus, the shape of the container (1250), alignment feature (1252), holder (1200), and engagement feature (1230) encourages the patient to insert the container (1250) in a single orientation and align it rotationally so that the container (1250) can be aligned with the illumination source (1210) and optical sensor (1220).

[0074]

[0103] In some variations, the alignment feature 1252 may further comprise a depth alignment feature, such as a set of one or more shoulders 1253 (e.g., lips, protrusions) configured to contact the sidewalls of the holder 1200 and aid in depth alignment of the container 1250 relative to the holder 1200. The shoulders 1253 may be disposed at least laterally along one or more sidewalls of the container 1250. The holder 1200 may be configured to provide a light seal around the periphery of the container 1250, except for the open top, open bottom, and openings in the engagement feature 1230. For example, the holder 1200 may include an opaque gasket or other seal that substantially blocks ambient light. Light seal features on the patient monitoring device door and the container 1253 may further contribute to sealing the container 1250 from ambient light.

[0075]

[0104] In some variations, the patient monitoring device may include a set of one or more fluid conduit routing features configured to facilitate optical measurement of the fluid conduit. As shown in FIG. 8A, the outlet of the drain line (840) may be routed below the housing (810) such that a portion of the fluid conduit (830) is held substantially perpendicular to the base (860). In some variations, the portion of the fluid conduit (830) distal to the container (832) may form a loop above or around the housing (810) and may be releasably coupled to a routing feature (822) configured to provide a strain relief, reduce downstream kinking of the fluid conduit (830), and / or reduce occlusion within the fluid conduit (830).

[0076]

[0105] In Figures 8B and 8C, the routing portion 822 can include a channel in the housing 810 and can hold the fluid conduit 830 therethrough. In Figures 9B and 9C, the routing portion 922 can define an external slot configured to releasably couple to the fluid conduit 930. For example, a portion of the fluid conduit 930 can slide or clip into the routing portion 922. The routing portion 922 can be provided on any suitable side of the housing 910. For example, as shown in Figure 9B, the routing portion 922 can be along the back side of the housing, or as shown in Figure 9C, the routing portion 922' can be along the side of the housing.

[0077]

[0106] In some variations, the routing configuration may further comprise one or more fastening features that laterally, axially, and / or rotationally attach (or otherwise secure) the fluid conduit within the routing configuration. For example, the routing configuration may include a channel sized to receive the fluid conduit with an interference fit (e.g., a snap fit). As another example, the routing configuration may include one or more fastening devices (e.g., clips, snaps, bands, etc.) that secure the fluid conduit within the channel. Similarly, the routing configuration may include a channel having one or more loops or other structures (or other lattices) spanning slots through which the fluid conduit may be routed into the channel. As another example, the routing configuration may include a channel having texturing (e.g., ridges, rings) along its surface to increase friction between the channel and the fluid conduit. As another example, the fluid conduit may be attached within the channel using an adhesive on the channel and / or fluid conduit. Any of the examples of fastening features described above may be combined in any suitable manner.

[0078]

[0107] In some variations, the patient monitoring device can include an optical sensor arrangement configured to illuminate the patient's bodily fluid and measure optical properties of the patient's bodily fluid. For example, the optical sensor arrangement can include an illumination source and an optical sensor. In some variations, a set of illumination sources and optical sensors can be arranged in parallel and configured to measure optical properties of different regions of the container. Non-limiting examples of illumination sources (e.g., light sources) include incandescent lamps, discharge lamps (e.g., excimer lamps, fluorescent lamps, gas discharge lamps, plasma lamps, etc.), electroluminescence (e.g., light emitting diodes, organic light emitting diodes, lasers, etc.), induction lamps, and fiber optics. In some variations, the optical sensor can include a photodiode, a charge-coupled device (CCD), or a complementary metal-oxide semiconductor (CMOS) optical sensor.

[0079]

[0108] 14A and 14B are schematic diagrams of cross sections (e.g., single-plane configurations) of optical sensor configurations. The optical sensor configurations can provide illumination from multiple illumination directions. As shown in FIG. 14A, a first illumination source (1410) can illuminate a container (1430) in a first illumination direction, and a second illumination source (1412) can illuminate the container (1430) in a second illumination direction that is orthogonal to the first illumination direction. In another example, shown in FIG. 14B, the first illumination source (1410) can have a first illumination direction that is offset 180 degrees from the second illumination direction such that each illumination source can direct light in opposite directions. In some variations, the patient fluid can be illuminated from multiple non-parallel illumination directions. For example, the first illumination direction can have an offset from the second illumination direction of between about 0 degrees and 180 degrees. In some variations, the first illumination source (1410) and the second illumination source (1412) can be configured to provide illumination at the same wavelength.

[0080]

[0109] 14A and 14B, a first optical sensor (1420) and a second optical sensor (1422) can be configured to generate signals corresponding to measurements of optical properties of the illuminated patient's body fluid. The first optical sensor and the second optical sensor can be, for example, photodiodes. The optical sensors can be configured to measure one or more of light scattering and attenuation detection angles (e.g., absorption, obscuration). For example, the optical sensors can be configured to measure properties of the illuminated patient's body fluid at an attenuation / obscuration angle (approximately 180 degrees), a forward scattering angle (approximately greater than 90 degrees and less than 180 degrees), a side scattering angle (approximately 90 degrees), and a back scattering angle (approximately less than 90 degrees and greater than or equal to 0 degrees). In Figure 14A, the first optical sensor (1420) faces the first illumination source (1410) (the first optical sensor and first illumination source are on opposite sides of the container (1430)), and the second optical sensor (1422) faces the second illumination source (1412) (the second optical sensor and second illumination source are on opposite sides of the container (1430)). In Figure 14B, the first optical sensor (1420) is generally orthogonal to the first illumination source (1410), and the second optical sensor (1422) is generally orthogonal to the second illumination source (1412).

[0081]

[0110] In some variations, the optical sensor configuration can include multiple planar configurations, such as those shown in FIGS. 14A and 14B. For example, as shown in FIGS. 10D and 10E, multiple illumination sources 1040 and optical sensors 1050 can be coupled to the holder 1010. The holder 1010 can be coupled to three planar configurations of illumination sources and optical sensors. In some variations, the planar sets can be spaced apart and parallel to the longitudinal direction of the holder 1010. In some variations, the illumination sources 1040 can be configured to output the same or different wavelengths. For example, two or more illumination sources 1040 can be configured to output the same wavelength to provide redundancy and improve the accuracy of the optical measurements. As another example, two or more illumination sources 1040 can be configured to output different wavelengths, in which case measurements associated with the different wavelengths can provide different information (e.g., potentially indicating different particle types associated with each respective wavelength).

[0082]

[0111] 10F shows an optical sensor configuration comprising a collimator (1032), at least one lens (1030) (e.g., an aspheric lens), and illumination sources (1042, 1044, 1046). In some variations, the illumination sources (1042, 1044, 1046) and / or the collimator (1032) can be configured to minimize stray light received by the optical sensor configuration. For example, one or more of the illumination source and the optical sensor configuration (e.g., the collimator) can comprise one or more of an anti-reflective coating and a light trap. For any of the optical sensor configurations described herein, an aperture can additionally or alternatively be configured to allow a predetermined range of viewing angles for the optical sensor configuration.

[0083]

[0112] As shown in FIG. 10C , the first illumination source (1042) can be configured to emit light at a first wavelength of about 800 nm to about 900 nm (e.g., about 860 nm). The second illumination source (1044) can be configured to emit light at a second wavelength of about 400 nm to about 450 nm (e.g., about 405 nm). The third illumination source (1046) can be configured to emit light at a third wavelength of about 500 nm to about 550 nm (e.g., about 525 nm). The first illumination source (1042) can be positioned in a generally central location, farthest from any possible source of ambient light leakage (e.g., from the inlet and outlet of the container). The second illumination source (1044) can be positioned closest to the outlet of the container to minimize alteration to the patient's bodily fluid due to illumination at the second wavelength (e.g., UV light). Additionally or alternatively, two of the illumination sources can be configured to output illumination at the same wavelength. In some variations, a fourth illumination source (not shown) can be configured to emit light at a fourth wavelength in the range of about 230 nm to about 290 nm.

[0084]

[0113] In some variations, the illumination source may include one or more of a light-emitting diode (and / or laser, scintillator, or other light source), a collimator, and a lens. In some variations, the illumination source may further include one or more filters. In some variations, one or more components, such as the collimator, may include an anti-reflective coating and / or other suitable features to minimize stray light output from the illumination source. At least some of these components may be positioned relative to one another via a mounting block or other fixture. For example, the illumination source may include a plano-convex lens configured to collimate the illumination and a set of filters configured to narrow the wavelength range. Figures 10B and 10C show an illumination housing (1011) including a lens (1030) and a collimator (1032).

[0085]

[0114] In some variations, the lens (1030) may include a plano-convex or aspheric lens. In some variations, each illumination source in each planar configuration may have at least a respective set of a collimator and a lens.

[0086]

[0115] FIG. 11A is a side view of an optical sensor configuration (1100) of a patient monitoring device including a pair of substantially orthogonal illumination sources (1110) and corresponding optical sensors (1120). The illumination sources (1110) are orthogonal to the optical sensors (1120). FIG. 11A illustrates the pair of orthogonal illumination sources (1110) and the pair of orthogonal optical sensors (1120) in each of three substantially parallel cross sections. The optical sensor configuration (1100) may include a lens (1112). A container (1150) may be aligned with the optical sensor configuration (1100) to receive illumination from the illumination sources (1110). FIG. 11B is a plane cross-sectional view of the optical sensor configuration (1100) shown in FIG. 11A, with exemplary dimensions taken along line AA. For example, the illumination sources (1110) may have a width of approximately 5 mm. The lenses (1112) may have a thickness of approximately 10 mm. The optical sensor (1120) may have an aperture of about 5 mm and an aperture distance of about 4 mm (e.g., 4.11 mm). However, the optical sensor configuration may include other suitable dimensions.

[0087]

[0116] In some variations, the optical sensor configuration can include at least one illumination source configured to emit broad-spectrum white light (e.g., from about 200 nm to about 1400 nm) and / or emit light in different wavelength ranges. For example, the illumination source can include RGB light-emitting diodes. The optical sensor configuration can further include at least one optical sensor configured to measure optical properties of the illuminated patient fluid. For example, the optical sensor can include a spectrophotometer that measures absorption or scattering over a wide range of wavelengths.

[0088]

[0117] In some variations, the optical sensor configuration can be configured to at least partially compensate for refraction of an optical measurement region, such as a container. FIG. 13 is a schematic diagram of the optical refraction of illumination 1302 through a container 1310. As described in more detail herein, the container 1310 can include an optically transparent measurement portion and a set of substantially planar surfaces (e.g., sidewalls). The container 1310 can include a taper (e.g., a draft angle), such as to help facilitate an injection molding or similar manufacturing process or to help self-align the container 1310 in a mating tapered shape of a holder. In FIG. 13, illumination 1302 generated by illumination source 1320 is refracted at angles θ1, θ2, θ3, and θ4 as it travels through the container 1310 and patient fluid 1312. Thus, illumination (1302) does not propagate in a straight line from illumination source (1320) through container (1310). As shown in FIG. 13, optical sensor (1330) can be positioned to compensate for this refraction to maximize received illumination (1302) and thus improve the signal-to-noise ratio. For example, the axial position of optical sensor (1330) substantially opposite illumination source (1320) across container (1310) can be slightly offset from the axial position of illumination source (1320) by a distance (D) in the direction of refraction. In some variations, offset distance (D) can be, for example, about 0.1 mm to about 1 cm. Additionally, optical sensor (1330) can be slightly tilted from the plane of illumination source (1320) by a predetermined tilt angle. In some variations, the tilt angle can be, for example, about 0.1 degrees to about 5 degrees.

[0089]

[0118] In some variations, the thickness of the optical measurement region of the container can be varied to reduce refraction and / or its effects. For example, the thickness of at least a portion of the optical measurement region can be thinner than the inlet and outlet of the container. As another example, the thickness of at least a portion of the optical measurement gradually decreases in the direction of the expected refraction to prevent or compensate for the expected refraction.

[0090]

[0119] In some variations, the reduction in measured light intensity due to refraction can be determined (e.g., empirically) for each optical sensor and expressed as a refractive constant and / or coefficient. For example, known refractive coefficients can be used to calibrate estimated turbidity based on measured optical properties.

[0091]

[0120] In some variations, the patient monitoring device may include an ambient light sensor configured to measure ambient light in an environment external to the housing. For example, the ambient light sensor may be located on an exterior surface of the housing (e.g., adjacent to the display or on top of the housing).

[0092]

[0121] In some variations, the patient monitoring device can include a tilt sensor configured to measure the angle of the patient monitoring device relative to the ground. Operation of the patient monitoring device can be interrupted in response to the detection of tilt due to the possibility of trapping air bubbles when tilted excessively, resulting in inaccurate sensor measurements. Additionally, the patient can be instructed to orient the patient monitoring device in an upright position. The tilt sensor can include an accelerometer, a gyroscope, an IMU, etc.

[0093]

[0122] In some variations, the patient monitoring device may include a fluid conduit sensor configured to detect the presence of a fluid conduit and / or container in a holder of the patient monitoring device. The fluid conduit sensor may include an optical sensor.

[0094]

[0123] In some variations, the patient monitoring device may include one or more optical sensors used to determine when the optical sensor configuration should be cleaned, repaired, and / or replaced. For example, the optical sensor may be configured to measure the light intensity of the illumination source when the holder is empty (e.g., there is no container or fluid conduit between the optical sensor and the illumination source) as a baseline optical measurement. If the measured light intensity is below a predetermined threshold, the patient may be notified to clean the optical sensor configuration. If the measured light intensity is still below a predetermined threshold after cleaning (e.g., wiping) the illumination source and optical sensor, the patient may be notified (e.g., on a display) that the patient monitoring device should be repaired and / or replaced. In some variations, the one or more optical sensors may be the same or different from the optical sensors used to measure the optical properties of the patient's bodily fluid.

[0095] Output Device

[0124] As described above, the patient monitoring device may include one or more output devices, such as a display. In some variations, the display may include a graphical user interface configured to allow the patient to view information and / or control the patient monitoring device. In some variations, the display may be angled upward toward the patient to aid in usability and visualization. In some variations, the display may include at least one of a light-emitting diode (LED), a liquid crystal display (LCD), an electroluminescent display (ELD), a plasma display panel (PDP), a thin film transistor (TFT), an organic light-emitting diode (OLED), an e-paper / e-ink display, a laser display, and / or a holographic display.

[0096]

[0125] FIG. 15 illustrates a set of exemplary variations of graphical user interfaces (GUIs) that may be displayed on a patient monitoring device. The GUIs allow the patient to view one or more of setup messages, device status, patient status, patient instructions, error messages, etc. The set of one or more setup GUIs may instruct the patient on how to operate the patient monitoring device. A first GUI (1500) may include an initialization message, such as a start-up message. A second GUI (1502) may include a connection message. For example, the patient may be instructed to engage a container with the patient monitoring device. A third GUI (1504) may include a seal message. For example, the patient may be instructed to close a door to form a light seal around the container. A fourth GUI (1506) may include a cleaning message. For example, the patient may be instructed to clean the patient monitoring device at periodic intervals.

[0097]

[0126] A set of one or more patient status GUIs can inform the patient of the infection status. The fifth GUI (1508) can include a positive infection message. For example, the patient can be notified of the infection and instructed to call their healthcare provider. In some variations, the positive infection message can be displayed in a different color (e.g., orange, red, yellow). For example, the positive infection message can be color-coded based on the severity of the infection score (as described in more detail below). In some variations, the patient monitoring device can send the positive infection message to the healthcare provider. The positive infection message can include, for example, an infection score determined by the system (as described in more detail below). The sixth GUI (1510) can include a negative infection message. For example, the patient can be informed that the patient monitoring device is monitoring the patient's body fluids and is otherwise operating normally.

[0098]

[0127] A set of one or more device status GUIs can inform the patient of the status of the patient monitoring device. The seventh GUI (1512) can include a communication message. For example, the patient can be notified that the patient monitoring device has not formed a network connection (e.g., to transmit patient data). The eighth GUI (1514) can include a tilt message. For example, the patient can be instructed to orient the patient monitoring device in an upright position. The ninth GUI (1516) can include an error message. For example, the patient can be notified of a failure of at least one component of the patient monitoring device, such as that the device should be replaced. A failure can include, for example, a degradation in performance below a predetermined threshold of the illumination source and / or optical sensor.

[0099]

[0128] In some variations, data can be processed and analyzed on a remote computing device (e.g., a remote server) and results can be output to the patient's smartphone via a set of GUIs. Additionally or alternatively, the patient monitoring device can include light guides (e.g., light pipes, light distribution guides, etc.) to allow the patient to visualize the infection status. One or more light guides can receive light from a light source (e.g., illumination source) using a predetermined combination of light output parameters (e.g., wavelength, frequency, intensity, pattern, duration) and output the infection status. In some variations, the light guides can be formed integrally with the housing of the patient monitoring device, which can simplify manufacturing and enable a compact design and minimal power usage.

[0100]

[0129] A light guide can refer to a physical structure that guides electromagnetic waves, such as visible light spectrum waves, passively propagating and dispersing the received electromagnetic waves. Non-limiting examples of light guides include optical fibers, rectangular waveguides, light tubes, light pipes, combinations thereof, and the like. For example, a light pipe can include a hollow structure with a reflective lining or a transparent solid configured to propagate light through total internal reflection. The light guides described herein can be made from any suitable material or combination of materials. For example, in some variations, the light guide can be made from optical-grade polycarbonate. In some variations, the housing described herein can be co-injection molded to form the light guide. In other variations, the light guide can be formed separately and coupled to the housing. In some variations, the light guides described herein can include one or more portions configured to emit light. For example, at least one of the portions can include one or more shapes. For example, the light guide can follow the edge of the housing and / or form the shape of a logo. In some variations, the light guides described herein may include surface contours, including, for example, faceted surfaces configured to enhance visibility from a given viewpoint.

[0101]

[0130] The light patterns described herein can include, for example, one or more of a flashing light, a dim light, an equal phase light, etc., and / or any suitable light / dark pattern of light. For example, a flashing light can correspond to a pulsating light where the total duration of light in each period is shorter than the total duration of darkness, and the durations of the flashing lights are equal. A dim light can correspond to a pulsating light where the duration of light in each period is longer than the duration of darkness. An equal phase light can correspond to a light having equal lengths of dark and light periods. A light pulse pattern can include one or more colors (e.g., different color outputs for each pulse), light intensity, and frequency.

[0102]

[0131] In some variations, the patient monitoring device may include an input device (e.g., a touchscreen). Some variations of the input device may include at least one switch configured to generate a control signal. For example, the input device may include a touch surface to which a user provides input corresponding to the control signal (e.g., the input being a finger touch on the touch surface). Input devices with a touch surface may be configured to detect contact and movement on the touch surface using any of a number of touch sensitivity technologies, including capacitive, resistive, infrared, optical imaging, dispersive signal, acoustic pulse recognition, and surface acoustic wave technologies. In variations of the input device that include at least one switch, the switch may include, for example, at least one of a button (e.g., hard key, soft key), touch surface, keyboard, analog stick (e.g., joystick), directional pad, mouse, trackball, jog dial, step switch, rocker switch, pointer device (e.g., stylus), motion sensor, image sensor, and microphone. The motion sensor may receive user movement data from an optical sensor and classify the user's gesture as the control signal. The microphone may receive audio data and recognize the user's voice as the control signal.

[0103]

[0132] In some variations, the patient monitoring device may include output devices such as audio and / or haptic devices. For example, the audio device may output patient data, fluid data, infection data, system data, alarms, and / or notifications audibly. For example, the audio device may output an audible alarm when an infection is predicted and / or when a drain line blockage is detected. In some variations, the audio device may include at least one of a speaker, a piezoelectric audio device, a magnetostrictive speaker, and / or a digital speaker. In some variations, the patient may communicate with other users using the audio device and the communication channel. For example, the user may form an audio communication channel (e.g., a cell phone, a VoIP call) with a remote healthcare provider.

[0104]

[0133] In some variations, a patient monitoring device can incorporate a haptic device to provide additional sensory output (e.g., force feedback) to the patient. For example, the haptic device can generate a tactile response (e.g., vibration) to confirm a user input to an input device (e.g., a touch surface).

[0105] network

[0134] In some variations, the systems and methods described herein may communicate with other computing devices, for example, via one or more networks, each of which may be any type of network (e.g., wired network, wireless network). Communications may be encrypted or unencrypted. A wireless network may refer to any type of digital network that is not connected by any type of cable. Examples of wireless communications in a wireless network include, but are not limited to, cellular, radio, satellite, and microwave communications. However, wireless networks may be connected to wired networks to interface with the Internet, other carrier voice and data networks, business networks, and personal networks. Wired networks are typically carried by copper twisted pair, coaxial cable, and / or fiber optic cable. There are many different types of wired networks, including wide area networks (WANs), metropolitan area networks (MANs), local area networks (LANs), Internet area networks (IANs), campus area networks (CANs), global area networks (GANs) such as the Internet, and virtual private networks (VPNs). Hereinafter, a network refers to any combination of wireless, wired, public and private data networks, typically interconnected through the Internet, that provide an integrated networking and information access system.

[0106]

[0135] Cellular communications can encompass technologies such as GSM, PCS, CDMA or GPRS, W-CDMA, EDGE or CDMA2000, LTE, WiMAX, and 3G, 4G, and / or 5G networking standards. Some wireless network deployments combine networks from multiple cellular networks or use a mixture of cellular, Wi-Fi, and satellite communications.

[0107] controller

[0136] Generally, the patient monitoring devices described herein may include a controller including a processor (e.g., a CPU) and a memory (which may include one or more non-transitory computer-readable storage media). The processor may integrate data received from the memory and data received via a communication channel to control one or more components of the system. The memory may further store instructions that cause the processor to execute modules, processes, and / or functions related to the methods described herein. In some variations, the memory and processor may be implemented on a single chip. In other variations, they may be implemented on separate chips. Additionally or alternatively, one or more controllers (e.g., one or more processors and memory) may be located separately from the patient monitoring devices described herein. For example, a patient monitoring device including a first controller may be configured to wirelessly transmit and receive data (using a communication device) to and from a server including a second controller. Any of the data processing methods described herein may be implemented by one or more of the controllers described herein.

[0108]

[0137] The controller can be configured to receive and process signal data from the optical sensor and other data (e.g., patient data, fluid data) from other sources (e.g., computing devices, databases, servers, providers, user input). The patient monitoring device can be configured to receive, process, compile, store, and access data. In some variations, the patient monitoring device can be configured to access and / or receive data from different sources. The patient monitoring device can be configured to receive data entered and / or measured directly from the patient. Additionally or alternatively, the patient monitoring device can be configured to receive data from a separate device (e.g., smartphone, tablet, computer) and / or from a storage medium (e.g., flash drive, memory card). The patient monitoring device can receive data via a network connection or via a physical connection to the device or storage medium (e.g., via a universal serial bus (USB) or any other type of port), as discussed in more detail herein. The patient monitoring device may communicate with a computing device, which may include any of a variety of devices, such as a mobile phone (e.g., a smartphone), a tablet computer, a laptop computer, a desktop computer, a portable media player, a wearable digital device (e.g., digital glasses, wristbands, wristwatches, brooches, armbands, virtual reality / augmented reality headsets), a television, a set-top box (e.g., a cable box, a video player, a video streaming device), a gaming system, etc.

[0109]

[0138] Patient monitoring devices can be configured to receive various types of data. For example, a patient monitoring device can be configured to receive a patient's personal data (e.g., gender, weight, birth date, age, height, date of diagnosis, anniversary of device use, etc.), a patient's bodily fluid data, general health information for other similarly situated patients, or any other relevant information. In some variations, a patient monitoring device can be configured to create, receive, and / or store a patient profile (and / or communicate with one or more suitable memory devices to create, receive, and / or store a patient profile). A patient profile can include any of the patient-specific information described above. While the information described above can be received by the patient monitoring device, in some variations, the patient monitoring device can be configured to process any data from the received information using software stored on or externally to the device. In another variation, a patient monitoring device can be paired (wired or wirelessly) with another patient monitoring device (e.g., pulse oximeter, blood pressure monitor) configured to measure one or more patient parameters.

[0110]

[0139] A processor may be any suitable processing device configured to run and / or execute a set of instructions or code and may include one or more data processors, image processors, graphics processing units, physical processing units, digital signal processors, and / or central processing units. A processor may be, for example, a general-purpose processor, a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), etc. The processor may be configured to run and / or execute application processes and / or other modules, processes, and / or functions associated with the system and / or networks associated with the system. The underlying device technology may be provided in a variety of component types (metal-oxide-semiconductor field-effect transistor (MOSFET) technology such as complementary metal-oxide-semiconductor (CMOS), bipolar technology such as emitter-coupled logic (ECL), polymer technology (e.g., silicon-conjugated polymer or metal-conjugated polymer-metal structures), mixed analog and digital, etc.

[0111]

[0140] In some variations, the memory may include a database (not shown) and may be, for example, random access memory (RAM), a memory buffer, a hard drive, erasable programmable read-only memory (EPROM), electrically erasable read-only memory (EEPROM), read-only memory (ROM), flash memory, etc. The memory may store instructions that cause the processor to execute modules, processes, and / or functions related to signal processing and the like, communication devices, infection prediction, turbidity estimation, particle estimation, flow detection, bubble detection, patient monitoring device control, and / or communications. Some variations described herein relate to computer storage products having non-transitory computer-readable media (which may also be referred to as non-transitory processor-readable media) having instructions or computer code for performing various computer-implemented operations. The computer-readable media (or processor-readable media) are non-transitory in the sense that they do not inherently include transient propagating signals (e.g., propagating electromagnetic waves that carry information in a transmission medium such as space or a cable). The media and computer code (which may also be referred to as code or algorithms) may be designed and constructed for a given purpose or multiple purposes.

[0112]

[0141] Examples of non-transitory computer-readable media include, but are not limited to, magnetic storage media such as hard disks, floppy disks, and magnetic tape, optical storage media such as compact discs / digital video discs (CD / DVD), compact disc-read only memory (CD-ROM) and holographic devices, magneto-optical storage media such as optical discs, solid-state storage devices such as solid-state drives (SSD) and solid-state hybrid drives (SSHD), carrier wave signal processing modules, and hardware devices specially configured to store and execute program code, such as application specific integrated circuits (ASICs), programmable logic devices (PLDs), read-only memory (ROM), and random access memory (RAM) devices. Another variation described herein relates to computer program products, which may include, for example, the instructions and / or computer code disclosed herein.

[0113]

[0142] The systems, devices, and / or methods described herein may be implemented by software (executed in hardware), hardware, or a combination thereof. Hardware modules may include, for example, general-purpose processors (or microprocessors or microcontrollers), field-programmable gate arrays (FPGAs), and / or application-specific integrated circuits (ASICs). Software modules (executed in hardware) may be expressed in various software languages (e.g., computer code), including C, C++, Java, Python, Ruby, Visual Basic, and / or other object-oriented, procedural, or other programming languages and development tools. Examples of computer code include, but are not limited to, microcode or microinstructions, machine instructions such as those produced by a compiler, code used to create web services, and files containing higher-level instructions executed by a computer using an interpreter. Further examples of computer code include, but are not limited to, control signals, encryption code, and compression code.

[0114]

[0143] In various variations, the patient monitoring device may further comprise a communications device configured to enable the patient and / or control one or more of the devices of the system. The communications device may comprise a network interface configured to connect the computing device to another system (e.g., the Internet, a remote server, a database) via a wired or wireless connection. In some variations, the patient monitoring device may communicate with other devices over one or more wired and / or wireless networks. In some variations, the network interface may include a radio frequency receiver, transmitter, and / or optical (e.g., infrared) receiver and transmitter configured to communicate with one or more devices and / or networks. The network interface may communicate wired and / or wirelessly.

[0115]

[0144] The network interface may include RF circuitry configured to receive and transmit RF signals. The RF circuitry may convert electrical signals to and from electromagnetic signals and communicate with communication networks and other communication devices via electromagnetic signals. The RF circuitry may include well-known circuits that implement these functions, including, but not limited to, an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a CODEC chipset, a subscriber identity module (SIM) card, memory, etc.

[0116]

[0145] Wireless communication via any of the computing devices and measurement devices may include, but is not limited to, Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), high-speed downlink packet access (HSDPA), high-speed uplink packet access (HSUPA), Evolution, Data-Only (EV-DO), HSPA, HSPA+, Dual-Cell HSPA (DC-HSPA), Long Term Evolution (LTE), Near Field Communication (NFC), Wideband Code Division Multiple Access (W-CDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Bluetooth, Wireless Any of a number of communication standards, protocols, and technologies may be used, including Wireless Fidelity (WiFi) (e.g., IEEE 802.11a, IEEE 802.11b, IEEE 802.11n, etc.), Voice over Internet Protocol (VoIP), Wi-MAX, protocols for email (e.g., Internet Message Access Protocol (IMAP) and / or Post Office Protocol (POP)), instant messaging (e.g., extensible messaging and presence protocol (XMPP), Session Initiation Protocol for Instant Messaging and Presence Leveraging Extensions (SIMPLE), Instant Messaging and Presence Service (IMPS)), and / or Short Message Service (SMS), or any other suitable communication protocol.In some variations, devices herein may communicate directly with each other without transmitting data over a network (e.g., via NFC, Bluetooth, WiFi, RFID, etc.).

[0117] power supply

[0146] In some variations, the patient monitoring device may receive power from an external power source (e.g., wall outlet, generator). The patient monitoring device may receive power via a wired and / or wireless connection (e.g., induction, RF coupling, etc.). Additionally or alternatively, the patient monitoring device may include a portable power source, such as a battery. As described in more detail herein, the patient monitoring device may include one or more power algorithms configured to conserve energy and extend the life of the patient monitoring device.

[0118] Drain line extension

[0147] The fluid conduits described herein can be configured to allow patient fluid to flow through an optical measurement portion for patient infection prediction and / or other characteristics of the patient fluid. In some variations, the fluid conduit can be configured to extend the length of a drain line. Additionally, the fluid conduit can be a disposable component. In some variations, the fluid conduit can be fluidly coupled to an optically transparent container configured for illumination and optical measurement. The container can include one or more alignment features configured to align (e.g., rotationally and / or in depth) the container with a patient monitoring device described herein.

[0119]

[0148] Figure 16A is a perspective view of the drain line extension (1600), and Figure 16B is an exploded perspective view of the drain line extension (1600). In some variations, the drain line extension (1600) can include one or more of a container (1610), a cap (1620), a fluid conduit (1630), a first connector (1640), a second connector (1642), a first vent cap (1650), a second vent cap (1652), a container extension (1660), a shut-off clamp (1670), and a packaging holder (1680) (e.g., tape, strip, band). An inlet of the container (1610) can be coupled to the vent extension (1660), and an outlet of the container (1610) can be coupled to the cap (1620). The vent extension 1660 can have a sufficient length so that the first connector 1640 is external to the housing of the patient monitoring device when the drain line extension 1600 is coupled to the patient monitoring device. An inlet of the vent extension 1660 can be coupled to the first connector 1640 (e.g., a male dialysis connector). A first vent cap 1650 can be coupled to the first connector 1640. An outlet of the cap 1620 can be coupled to the inlet of the fluid conduit 1630. The outlet of the fluid conduit 1630 can be coupled to a second connector 1642 (e.g., a female dialysis connector) and a second vent cap 1652. In some variations, at least a portion of the fluid conduit 1630, the container extension 1660, and / or other vent caps, connectors, etc. can be opaque to further block or otherwise control ambient light from entering the drain line extension.

[0120]

[0149] FIG. 17A is a perspective view of the drain line extension (1700), and FIG. 17B is an exploded perspective view of the drain line extension (1700). In some variations, the drain line extension (1700) can include one or more of a container (1710), a cap (1720), a fluid conduit (1730), a connector (1740) (e.g., a bushing), a first vent cap (1750), a second vent cap (1752), a shut-off clamp (1760), and a packaging holder (1770) (e.g., tape). An inlet of the container (1710) can be coupled to the first vent cap (1750) (e.g., a spike vent cap), and an outlet of the container (1710) can be connected to the cap (1720). The outlet of the cap (1720) can be coupled to the inlet of the fluid conduit (1730). The outlet of the fluid conduit (1730) can be coupled to a connector (1740) and a second vent cap (1752). In some variations, at least a portion of the fluid conduit (1730) and / or other vent caps, connectors, etc. can be non-transparent to further block or otherwise control ambient light from entering the drain line extension.

[0121]

[0150] While Figures 17A and 17B show a drain line extension including an optically transparent container configured for illumination and optical measurement, it should be understood that in other variations, an optically transparent container can additionally or alternatively be disposed along any portion of the fluid conduit that is in fluid communication with the waste discharge of the cycler. For example, in some variations, a drain line that is part of a base tubing set (rather than a drain line extension) can include an optically transparent container or an optically transparent measurement portion. For example, Figure 17C is a perspective view of an exemplary variation of a cycler drain line (1701) assembled with a container (1711). The cycler drain line (1701) can include a first portion (1734) (e.g., an inlet) and a second portion (1732) (e.g., an outlet). For example, a container (1711) including an optically transparent measurement portion as described herein can be assembled in-line with the drain line (e.g., a tubing set) (1701). In some variations, the container 1711 can be configured to be attached to the drain line 1701 using solvent bonding and / or adhesives, as described herein. The integrated drain line 1701 shown in Figure 17C can, for example, reduce the number of assembly steps in CCPD treatment, thus improving patient compliance and sterility.

[0122]

[0151] In some variations, a fluid container (e.g., an optically transparent measuring portion) can be located within one or more portions (e.g., proximal, distal, intermediate) of the drain line or drain line extension. In some variations, the optically transparent measuring portion can be located within the end (e.g., proximal, distal) of the drain line. For example, a CAPD system can include a drain line coupled between a Y-connector and a drainage container, where the proximal portion of the drain line can include an optically transparent measuring portion adjacent to the Y-connector (e.g., downstream of the Y-connector). As another example, the proximal end of an indwelling catheter can include a fluid container as described herein. In a CCPD system, an optically transparent measuring portion of the indwelling catheter can be coupled adjacent to the drain line of the cycler tubing set. An optically transparent measuring portion located at the end of the drain line can reduce manufacturing complexity and, therefore, associated costs.

[0123]

[0152] The drain line extensions described herein may be compatible with standard connectors and / or adapters. The vent caps may be configured to protect the fluid conduit and the container lumen from contamination. For example, a spike vent cap may be configured to protect the packaging of the drain line extension from being punctured by sharp edges on the container. One or more of the vent caps may additionally or alternatively include a contamination prevention feature, such as a serpentine channel, to help prevent contaminants from entering the drain line fluid conduit. In some variations, one or more outer surfaces of the drain line extension, excluding the optical measurement area of the container, may be textured to prevent sticking and / or reduce leakage of ambient light into the container. In some variations, one or more portions of the drain line extension, excluding the optical measurement area of the container, may be opaque to reduce leakage of ambient light into the container. For example, the cap may be opaque and the fluid conduit may be translucent. The inlet and outlet portions of the container may similarly be opaque.

[0124]

[0153] The drain line extension can further include a measurement reservoir, which can define a volume for receiving a patient's bodily fluid to be measured by the patient monitoring device. Conventional cuvettes used in fluid analysis generally have precise dimensions and must meet strict manufacturing tolerances that injection molding and similar cost-effective techniques do not allow. In contrast, however, the reservoirs described herein, as further described below, can include multiple structural features that allow them to be formed utilizing high-yield, low-cost manufacturing techniques, such as injection molding and solvent bonding, while still enabling high-quality optical measurements.

[0125]

[0154] 18A-18I illustrate various views of a container 1800 for use in a fluid conduit, the container 1800 including an inlet 1810 (e.g., a spike), an outlet 1830, and an optically transparent measuring portion 1820 between the inlet 1810 and the outlet 1830. The measuring portion 1820 may include an interior volume configured to receive a fluid, such as a patient's bodily fluid. During use of the container 1800, the patient's bodily fluid may enter the measuring portion 1820 through the inlet 1810 and exit the measuring portion 1820 through the outlet 1830. For example, the patient's bodily fluid may be continuously pumped through the container 1800 during a measurement period. At least one cap 1870 may be coupled to the outlet 1830 and / or the inlet of the container. A fluid conduit 1880 may be coupled to the outlet of the cap 1870. A drain line or other pipe may be coupled to the inlet (1820).

[0126]

[0155] In some variations, the container 1800 can include one or more optical features configured to facilitate optical measurement of the patient's bodily fluid passing through the container 1800. The measuring portion 1820 can include at least two substantially planar surfaces, which can be perpendicular to one another or opposite one another. Such planar or flat surfaces can be advantageous for the devices and methods described herein due to the reduced bending of light caused by flat surfaces (compared to traditional cuvettes with round surfaces). As shown in FIG. 18G, the measuring portion 1820 can include a square cross-section. The substantially planar surface and square cross-section can reduce refraction relative to a cylindrical conduit, improving the consistency and quality of optical measurements through the container 1800. The square cross-section can also aid in aligning the container 1800 with an optical sensor configuration of a patient monitoring device.

[0127]

[0156] In some variations, the interior volume of measurement portion 1820 can include one or more bubble mitigation features that reduce the occurrence and presence of air bubbles in container 1800, thus improving the signal-to-noise ratio of optical measurements using container 1800. For example, the interior volume can include bubble mitigation features such as rounded corners 1860 and tapers 1822. The rounded corners can reduce the number of sharp transitions and edges where air bubbles can form and accumulate (e.g., during initial fluid fill, during continuous flow, etc.).

[0128]

[0157] In some variations, the container 1800 can include one or more ambient light-reducing features that reduce leakage of ambient light into the measuring portion 1820 of the container. For example, one or more of the inlet 1810 and the outlet 1830 can include a non-transparent (e.g., opaque, translucent) material and / or coating. One or more of the inlet 1810 and the outlet 1830 can include texturing to provide a gripping interface for the patient and / or form a light seal. Additionally, a non-transparent connector can be coupled to the inlet 1810 and / or the outlet 1830.

[0129]

[0158] In some variations, the container (1800) may include one or more alignment features configured to aid in engaging and positioning the container (1800) relative to the optical sensor arrangement of the patient monitoring device. For example, the container (1800) may include a depth alignment feature (1840) and / or a rotational alignment feature (1850). In some variations, the depth alignment feature (1840) may be disposed around the outer periphery of the container (1840). The depth alignment feature (1840) may engage with a shoulder or other mating or interference feature of a holder in the patient monitoring device (e.g., shoulder (1253) of the patient monitoring device (1200) shown in FIG. 12A). The rotational alignment feature (1850) may engage with a slot or recess in a holder in the patient monitoring device (e.g., engagement feature (1012) of the holder shown in FIG. 10A). In some variations, the rotational alignment feature (1850) can be formed so as not to overlap an area of the measuring portion (1820) that is aligned with the illumination source and optical sensor in the patient monitoring device when the container is placed in the patient monitoring device. Thus, in these variations, the placement of the rotational alignment feature (1850) is selected to avoid interference with the optical measuring portion. For example, as shown in FIGS. 18C-18F , the rotational alignment feature (1850) can be positioned on a corner of the measuring portion (1820) rather than on one of its planar surfaces. The depth alignment feature (1840) and / or the rotational alignment feature (1850) can include a protrusion.

[0130]

[0159] In some variations, the container (1800) can include one or more features configured to aid in the manufacture of the container (1800). In some variations, at least a portion of the measuring portion (1820) can be tapered. For example, the measuring portion (1820) can include a draft angle of approximately 0.5 to 2 degrees. Additionally, injection-molded parting lines can be located above and below the optical measuring portion (e.g., along the depth registration features). In some variations, the container (1800) can be bonded to the cap (1870) (such as those described below) by solvent bonding. Solvent bonding can be a cost-effective and efficient manufacturing technique. For example, the solvent can include cyclohexanone and / or methyl ethyl ketone.

[0131]

[0160] In some variations, the container (1800) can be constructed from a material that has good optical clarity and high transmission of light of the desired wavelengths. For example, the container can include one or more of copolyester, acrylonitrile butadiene styrene, polycarbonate, acrylic, cyclic olefin copolymer, cyclic olefin polymer, polyester, polystyrene, Ultem, polyethylene glycol coated silicone, zwitterionic coated polyurethane, polyethylene oxide coated polyvinyl chloride, and amphiphilic polysilicone. For example, the container (1800) can be constructed from VLD-100 acrylic, Cyro H15-011 acrylic, Acritherm HS acrylic HS3125, acrylic V825, Acritherm HS3, cycloolefin polymer Zeonex E48R, cycloolefin polymer Zeonex 1020R, cycloolefin polymer 1060R, cycloolefin polymer TPX RT-18, COC Topas, polycarbonate LExan 1130-112, Lexan HSP6-1125, polyester OKP4, Dow 685D polystyrene, and Ultem 1010-1000.

[0132]

[0161] In some variations, a cap can be coupled to an end of the container (e.g., inlet, outlet), and the cap can function as a connector for the fluid conduit. For example, the cap can provide a transition between the container cross-section and the remainder of the fluid conduit cross-section (e.g., from a square cross-section of the container to a circular cross-section of the fluid conduit). FIGS. 19A-19D show various views of a cap (1900) for a container including an outlet (1910), an inlet (1920), and a grip (1930). In some variations, the cap (1900) can include one or more ambient light-reducing features that reduce the transmission of ambient light from the lumen of the fluid conduit into the container. For example, the cap (1900) can include a non-transparent material and / or coating (e.g., opaque, translucent). Additionally, the outer surface of the grip (1930) can include texture to provide a grip interface for the patient and / or form an ambient light seal. For example, a grip (1930) on the cap (when the cap is coupled to the container) allows a patient to handle the container without touching and contaminating the optically sensitive clear sidewall. In some variations, the grip can include one or more recesses configured to accommodate fingers, while in other variations, the grip can additionally or alternatively include outwardly protruding texture, such as ribs.

[0133]

[0162] In some variations, the cap (1900) can be coupled to the container via an interference fit. In some variations, the cap (1900) can be configured to fit over the end (outlet or inlet) of the container and have a container-contacting surface that is undersized relative to the end of the container to facilitate the interference fit. Alternatively, in other variations, the cap (1900) can be configured to fit within the end (outlet or inlet) of the container and have a container-contacting surface that is oversized relative to the end of the container to facilitate the interference fit. Furthermore, in these variations, the cap (1900) can include a material that is less rigid (e.g., semi-rigid) than the container to further enable an interference fit between the cap (1900) and the container. Additionally or alternatively, the cap can be coupled to the container via solvent bonding. In some variations, the cap (1900) can comprise a semi-rigid material such as PVC (e.g., Shore hardness 90A), the container can comprise a rigid material such as a copolyester (e.g., Tritan MX731), and the cap (1900) can be further solvent bonded to the container with solvents - cyclohexanone and / or methyl ethyl ketone.

[0134]

[0163] 19C and 19D, in some variations, the interior volume of the cap (1900) can include one or more contact surfaces (1960, 1962) configured to provide an internal stop that engages with the outlet of a container or fluid conduit. For example, the cap (1900) can include a container-contact stop (1960) configured to engage or mate with the end of a container and / or a conduit-contact stop (1962) configured to engage or mate with the end of a fluid conduit. In some variations, the cap can be coupled to the end of the fluid conduit by solvent bonding, similar to that described above.

[0135]

[0164] In some variations, the interior volume may further comprise one or more bubble mitigation features similar to those described above with respect to the container, such as rounded corners (1940) and / or tapered transitions.

[0136] Patient Monitoring Methods

[0165] Also described herein are methods for monitoring patient bodily fluids using the systems and devices described herein. For example, the methods may include one or more of predicting a patient's infection, estimating fluid particle concentration, estimating fluid flow, and air bubble detection. These methods may be useful for monitoring peritoneal dialysis patients with indwelling catheters, who are susceptible to infectious complications. It should be understood that any of the systems and devices described herein may be used in the methods described herein.

[0137] Infectious disease forecast

[0166] Generally, methods for predicting infection can be based on optical measurements of a patient's bodily fluid. For example, light scattering and / or obscuration of the patient's bodily fluid can be measured through an optically transparent container. These optical measurements can be used to estimate a turbidity value of the patient's bodily fluid. Furthermore, the concentration of a predetermined particle can be estimated based on the light absorption pattern across predetermined wavelengths and the resulting variation in the light scattering sensor output. An infection score can be generated based on the estimated optical properties (e.g., turbidity) and / or changes in the optical properties over time. The prediction that a patient is infected can be based on one or more of the infection score and a set of predetermined criteria.

[0138]

[0167] As discussed above, infectious diseases may generally be correlated with the concentration of one or more particle types, such as white blood cells, in a patient's bodily fluid. The concentration of white blood cells and / or other particle types can be estimated or measured based on the turbidity of the patient's bodily fluid, as estimated or measured using methods and devices such as those described herein.

[0139]

[0168] In some variations, the method for predicting infection can include illuminating the patient's bodily fluid in the fluid conduit from multiple illumination directions, for example, the illumination directions can be generally orthogonal to each other or approximately 180 degrees from each other.

[0140]

[0169] In some variations, the illumination output from a single illumination source enables both scattering angle light intensity measurements (e.g., 90 degrees) and absorption / obstruction / attenuation angle light intensity measurements (e.g., 180 degrees). For example, in FIG. 14A , a first optical sensor (1420) can be configured to measure a 180-degree scattering angle (e.g., attenuation) light intensity measurement (T1) of the patient's bodily fluid based on the illumination output from the first illumination source (1410). The first optical sensor (1420) can further measure a 90-degree scattering angle light intensity measurement (N2) of the patient's bodily fluid based on the illumination output from the second illumination source (1412). Similarly, a second optical sensor (1422) can then be configured to measure a 180-degree scattering angle light intensity measurement (T2) of the patient's bodily fluid based on the illumination output from the second illumination source (1412). The second optical sensor (1422) can further measure a 90 degree scattering angle light intensity measurement (N1) of the patient's bodily fluid based on the illumination output from the first illumination source (1410). The light intensity measurement (T) is set so that the optical sensor measures light intensity from a single illumination source rather than from multiple illumination sources simultaneously. n , N n ) can be measured separately (e.g., sequentially).

[0141]

[0170] In some variations, the first illumination source (1410) and the second illumination source (1412) can illuminate the patient body fluid in a first plane such that a first illumination direction of the first illumination source (1410) and a second illumination direction of the second illumination source (1412) are substantially coplanar. In some variations, the patient body fluid can be illuminated through multiple parallel illumination planes (e.g., a first plane, a second plane, a third plane) that are substantially orthogonal to the fluid conduit.

[0142]

[0171] In some variations, each illumination source in an illumination plane (e.g., first plane, second plane, third plane) can illuminate the patient fluid at the same wavelength, such that the illumination sources in the illumination plane output redundant wavelengths. Illuminating the patient fluid with multiple illumination sources at the same wavelength can improve optical sensor measurements, for example, by canceling erroneous signals.

[0143]

[0172] In some variations, sensor measurement error detection can be performed to eliminate unreliable light intensity measurements that may result from error sources such as broken, malfunctioning, or dirty optical components in the optical system (e.g., illumination source, optical sensor). In some variations, paired light intensity measurements can also be used to validate the light intensity measurements. For example, light intensity measurements N1 and N2 of the patient's body fluid can be used to calculate a percentage difference (e.g.,

number

[0144]

[0173] In some variations, an illumination source, such as an LED, can emit light based on pulse-width modulation (PWM). In some variations, a first illumination source using PWM can emit multiple light pulses (pulse "on" phases), during which a first optical sensor can simultaneously measure the light intensity during the pulse "on" phase, followed by measurements using a second optical sensor. The first illumination source can be turned off, and a second illumination source using PWM can emit multiple light pulses (pulse "on" phases), during which a second optical sensor can simultaneously measure the light intensity during the pulse "on" phase, followed by measurements using the first optical sensor. During each PWM-on sequence, the optical sensor can take a single measurement or multiple measurements. Multiple measurements allow for statistical processing of the measurements, such as deriving the mean, median, standard deviation, minimum, and maximum of the measurements, or more complex statistical modeling, such as outlier analysis and removal. During the PWM-on sequence, the optical sensor can be configured to add a delay before measuring within each pulse "on" phase to allow the illumination source to warm up and stabilize to provide more accurate optical measurements. The delay for warm-up stabilization may comprise a single pulse or a portion of multiple pulses.

[0145]

[0174] Generally, the measured optical properties can be used to estimate the turbidity of the patient's body fluid, which can be correlated (e.g., based on empirical correlations) to particle (e.g., white blood cell) concentration to provide an indication of infection status. The 180-degree scattering angle light intensity measurements (T1, T2) are more sensitive to changes in illumination intensity than the 90-degree scattering angle light intensity measurements (N1, N2). In some variations, a first illumination source (1410) can illuminate the patient's body fluid, a first optical sensor (1420) can measure T1, and a second optical sensor (1422) can measure N1. Then, a second illumination source (1412) can illuminate the patient's body fluid, the first optical sensor (1420) can measure N2, and the second optical sensor (1422) can measure T2. The period between successive optical measurements using the first and second illumination sources should be minimized to ensure measurement of the same portion of the patient's body fluid. Based on these measurements, the turbidity of the patient's body fluid can be estimated based on the following equations: Turbidity1 and Turbidity2.

number

[0146]

[0175] The Turbidity 1 formula can provide high accuracy, while the Turbidity 2 formula can be robust to changes in light intensity due to light source and / or container variations (e.g., manufacturing variations). In some variations, the turbidity formula used to estimate the turbidity of a patient's bodily fluid can be selected based on the measured light intensity variation between optical sensors. For example, if the measured T1 and T2 are within a predetermined range of each other (e.g., 75%, 80%, 85%, 90%, 95%, 98%, etc.), the Turbidity 1 formula can be used to estimate turbidity. Otherwise, the Turbidity 2 formula can be used to estimate turbidity. In some variations, both formulas can be used to estimate turbidity, or some combination of estimated turbidity can be used. For example, the estimated turbidity can be averaged and / or weighted. Additionally, the estimated turbidity can be sampled over a predetermined period of time, and the set of samples can be averaged and / or weighted. For example, a single turbidity value used to predict infection can be generated for each drain cycle based on an average of multiple estimated turbidities during the drain cycle. In some variations, the sampling frequency of the patient's bodily fluid can be increased based on a predicted positive infection status.

[0147]

[0176] In some variations, the measured optical properties of the patient's body fluid illuminated from multiple illumination directions can be used to calibrate the patient monitoring device. For example, a significant difference between the measured T1 and T2 can indicate that at least one of the illumination sources may be faulty and should be replaced. In response, one or more of the patient, healthcare provider, and manufacturer can be notified that the patient monitoring device needs repair and / or replacement. For example, the patient monitoring device can notify the patient to "call their healthcare provider" or "replace the device." In some of these variations, the patient monitoring device can suspend patient monitoring functions until the calibration and / or repair is performed.

[0148]

[0177] In some variations, the illumination output from a single illumination source allows for multiple scattering angle light intensity measurements (e.g., 90 degrees). The optical sensor in this configuration does not provide 180 degree scattering angle light intensity measurements, but is configured to capture side scattered illumination from different illumination sources. For example, in FIG. 14B, the first optical sensor (1420) generates 90 degree scattering angle light intensity measurements (N ) based on the respective illumination outputs from the first illumination source (1410) and the second illumination source (1412). 1.1 and N 2.1 Similarly, the second optical sensor (1422) can be configured to separately measure 90 degree scattering angle light intensity measurements (N) based on the illumination outputs from the first illumination source (1410) and the second illumination source (1412), respectively. 1.2 and N 2.2 ) can be configured to measure them separately.

number

[0149]

[0178] The Turbidity3 formula may be more robust to changes in light intensity compared to the Turbidity1 formula.

[0150]

[0179] In some variations, the turbidity (as determined by one or more of the turbidity equations described above) can be correlated to an infection status (e.g., based on an empirical correlation), and the infection status can be quantified using an infection score. The infection score can be expressed, for example, in terms of nephelometric turbidity units (NTU). In some variations, the estimated turbidity can be scaled (e.g., normalized) to an infection score scale, such as from 0 to 100. In another variation, the infection score can be based on the rate of change of the measured turbidity of successive samples over a predetermined period of time (e.g., 24 hours).

[0151]

[0180] Additionally or alternatively, any one or more of the above turbidity equations may be used to determine one or more other patient fluid characteristics, such as particle composition estimation, fluid flow estimation (e.g., detecting whether the cycler is on or off), detecting air bubbles in the patient fluid, etc., as further described below.

[0152] Ambient Light Subtraction

[0181] Due to factors such as manufacturing tolerances, wear, and environmental conditions, ambient light leakage or propagation through one or more of the patient monitoring device's housing, fluid conduits, and vessels can alter optical measurements. In some variations, the optical sensor can be calibrated at predetermined intervals to compensate for ambient light leakage. Thus, ambient light (e.g., not generated by the illumination source) can be removed from the measured signal to improve estimated turbidity, infection prediction, and other analyses performed on the measured signal.

[0153]

[0182] In some variations, ambient light noise can be measured and removed from subsequent optical measurements and signal processing. For example, a baseline optical measurement corresponding to ambient light levels can be performed. This baseline value can be subtracted from subsequent optical measurements to improve, for example, estimated turbidity and infection predictions. In some variations, the baseline optical measurement can be performed when empty fluid conduits and containers are first installed and sealed within the patient monitoring device and when the illumination source is turned off. Any signal measured by the optical sensor during this baseline measurement (the “dark” signal) may be due to ambient light leakage and / or electrical noise. Subsequent optical measurements can be calibrated against this baseline measurement, where the baseline measurement is subtracted from each subsequent optical measurement (the “optical signal”). In other words, a “true” measurement that may be specifically attributable to the characteristics of the patient fluid can be determined as the difference between the “light” and “dark” signals. In another variation, the optical measurements of the patient fluid can include a baseline measurement. For example, the following sequence can be used: That is, while the first and second illumination sources are off, a dark signal is measured at the first and second optical sensors. The first illumination source is turned on and light intensity is measured at the first and second optical sensors. The first illumination source is turned off and a dark signal is measured at the first and second optical sensors. The second illumination source is turned on and light intensity is measured at the first and second optical sensors. This sequence can be repeated at predetermined intervals (for every optical measurement of the patient's body fluid). In some variations, an optical sensor located on the exterior of the housing of the patient monitoring device can also or alternatively be used to generate or contribute to a baseline measurement.

[0154]

[0183] In some variations, the baseline optical measurement can be performed any time the illumination source is turned off and the patient's bodily fluid is stationary or flowing through the container. For example, such a calibration can be performed at the beginning of every cycle using the PD device or each time the housing door is closed. If at any time the baseline optical measurement exceeds a predetermined threshold, one or more of the patient, healthcare provider, and manufacturer can be notified to repair and / or replace the patient monitoring device and / or fluid conduit, potentially indicating a calibration or device failure. Additionally or alternatively, the patient can be instructed to reduce the intensity of ambient light sources in the patient monitoring device's environment.

[0155]

[0184] In some variations, the baseline optical measurement can be performed when an empty container is first placed in the patient monitoring device. In other variations, the baseline optical measurement can be performed when the cycler is first set up and irrigation fluid is primed through the drain line. In some variations, the baseline optical measurement can be used to calibrate the patient monitoring device before measuring patient effluent.

[0156] Particle composition estimation

[0185] In some variations, the particle composition of the patient's body fluid can be estimated based on the measured optical properties of the patient's body fluid. For example, the type and / or concentration of particles (e.g., red blood cells, white blood cells, triglycerides, proteins, fibrin, etc.) in the patient's body fluid can be estimated based on optical measurements of particle sedimentation properties of the static patient's body fluid and / or optical measurements at a set of predetermined wavelength ranges.

[0157]

[0186] In some variations, estimated particle compensation can be used to improve the accuracy of detecting a patient's infectious status. For example, characterization of particle composition using the methods described below can be used to distinguish between "true positives" and "false positives" for infectious status determination (e.g., to identify and eliminate false positives). For example, if the estimated turbidity calculated using one of the turbidity equations described above exceeds a predetermined threshold corresponding to an infectious disease, but the estimated particle composition of the patient's bodily fluid is determined to be mostly red blood cells, the prediction of an infectious disease can be considered a false positive.

[0158]

[0187] Additionally or alternatively, estimated particle compensation can be used to characterize the patient fluid and / or patient status in other ways. For example, if the patient fluid is determined to contain a high concentration of red blood cells, the estimated turbidity of the patient fluid may be due to bleeding rather than white blood cells, rather than infection.

[0159]

[0188] Additionally or alternatively, particle type and / or concentration of particles in a patient's bodily fluid can be estimated by changes over time in successive sample measurements. For example, a patient may have five drainage sessions over a 24-hour period. In the event of an infection, white blood cell counts may rapidly increase in concentration as part of an innate immune response. Thus, by measuring successive samples, a rate of change in optical measurements can be determined, characterized by a unique profile of increased white blood cells corresponding to an infection. In another example, an infusion of triglycerides may correspond to a sudden, single measurement spike. Subsequent optical measurements may be characterized by a return to a lower, normal baseline value. In yet another example, bleeding typically results in an immediate spike in measured fluid turbidity, which quickly decreases as the biological mechanism of blood clotting takes over.

[0160] Particle Settling

[0189] In some variations, the composition of the patient's body fluid can be estimated based on the measured optical properties over time. For example, these optical properties of the drained dialysate can be measured during a CCPD exchange. A typical CCPD exchange has three phases of operation: (1) filling the patient with dialysate by pumping dialysate into the patient entry line; (2) allowing the dialysate to dwell within the patient's body while the pump is off; and (3) draining the drained dialysate from the patient's body by pumping the drained dialysate into the drain line during a drain cycle. The drain cycle typically includes several steps, including: (3a) flushing previous fluid from the drain line (the previous fluid may be drain fluid, wash fluid from a previous priming and / or purging step, and / or any incidental new patient fluid); (3b) pumping new patient fluid into the drain line; and (3c) terminating the pumping and allowing the new patient fluid to settle in the drain line.

[0161]

[0190] In some variations, one or more optical measurements can be taken while the patient's body fluid is being pumped through the drain line during step (3b). For example, optical measurements can be taken during step (3b) at the beginning, middle, and end of this pumping cycle, which can indicate how homogeneous the new patient's body fluid is. Homogeneity can be estimated, for example, based on the temporal uniformity of the estimated turbidity as described above. Generally, larger particles and clumps (e.g., fibrin) may appear less homogeneous than smaller particles such as white blood cells. Thus, a higher measured homogeneity can suggest a higher concentration of relatively large particles such as fibrin.

[0162]

[0191] Additionally or alternatively, during step (3c), one or more optical measurements can be taken when the fluid flow of the new patient fluid has terminated (e.g., the pump has been turned off) and the new patient fluid has settled in the drain line. Starting from the time the pump has stopped (time=0), the optical properties of the patient fluid can be measured at predetermined intervals as the patient fluid settles. In some variations, the patient fluid can be measured at time=30 seconds, 1 minute, 2 minutes, 5 minutes, 15 minutes, 30 minutes, 60 minutes, etc. At each predetermined interval, the measured signal data (as described above) can be used to estimate turbidity. Particle properties, including mass, buoyancy, density, size, and shape, affect the consistency and / or variability of turbidity measurements over time across these time series of measurements. That is, particle types exhibit unique settling characteristics. Therefore, the predominant particle types in the patient fluid can be estimated based on the settling characteristics of the patient fluid. For example, triglyceride fractions, which have a lower density than bodily cells, may remain suspended for a relatively long period of time. Alternatively, white blood cells, which are larger and have a different shape than red blood cells, may sediment at a relatively high rate. For example, FIG. 20 is a graph (2000) of the turbidity of a set of exemplary settling patient fluids over time. In graph (2000), the difference in measured turbidity over time (which is a reflection of sedimentation characteristics) of a first patient fluid (2010) and a second patient fluid (2020) suggests that the first patient fluid (2010) and the second patient fluid (2020) have different particle compositions.

[0163] Simultaneous Equations

[0192] In some variations, the particle composition (e.g., particle concentration) of the patient's bodily fluid can be estimated based at least in part on a system of equations using inputs including a set of optical measurements at multiple wavelength ranges. For example, the optical characteristics (e.g., attenuation or scattering angle A) of the patient's bodily fluid measured at four wavelength ranges (λ1, λ2, λ3, λ4) can be estimated. λn ) to calculate the particle concentrations (ε) of white blood cells, red blood cells, proteins (e.g., fibrin), and triglycerides using the following equations: l , ε e , ε p , ε t) can be estimated.

number

[0164]

[0193] Optical properties A λn can be measured at each of a set of wavelengths λ1, λ2, λ3 and λ4. l , C e , C p and C t can be empirically derived through data models. Thus, for any given patient fluid (or other fluid), the particle concentration (ε l , ε e , ε p , ε t ) can be solved as a system of equations.

[0165]

[0194] In some variations, the set of wavelengths includes a first wavelength of about 400 nm to about 450 nm (e.g., 415 nm), a second wavelength of about 500 nm to about 550 nm (e.g., 525 nm), a third wavelength of about 230 nm to about 290 nm (e.g., 260 nm), and a fourth wavelength of about 860 nm to about 890 nm (e.g., 870 nm). In some variations, the patient's body fluid can be sequentially illuminated with the four wavelength ranges in any predetermined order. Furthermore, illumination at these wavelengths can be provided by the same illumination source that provides turbidity measurements as described above, or can be provided, at least in part, by a separate and distinct set of illumination sources.

[0166]

[0195] 23A-23D show histograms (2300, 2310, 2320, 2330) of particle concentration estimation errors for four particle types for a set of patient body fluid samples using the simultaneous equations approach described above. Particle concentrations can be estimated based on the simultaneous equations for four particles (white blood cells, red blood cells, proteins, and triglycerides) measured at corresponding wavelengths (415 nm, 525 nm, 575 nm, and 870 nm). Estimation errors can be calculated by comparing the predicted particle concentrations to the actual particle concentrations determined using spectroscopy. As shown in FIGS. 23A-23D, the distribution of particle concentration estimation errors for the four particle types is generally near zero or a similarly low number, suggesting that the simultaneous equations approach may be an accurate and feasible method for estimating the particle composition of patient body fluids.

[0167] Machine Learning

[0196] Additionally or alternatively, one or more trained machine learning models (or deep learning models, etc.) can be used to determine the particle composition of a patient's bodily fluid based at least in part on one or more measured optical properties, such as light absorption patterns. For example, one or more suitable machine learning models can be trained on a suitable training data set containing known particle concentrations, and the trained machine learning models may be able to identify "signatures" in the light absorption patterns that are indicative of particle composition. Such optical properties can be measured at a single time point or dynamically to generate time-series data. It should also be understood that any of the above-described variations of determining particle composition can be supplemented with suitable machine learning methods.

[0168] Onset and resolution of patient infections

[0197] In some variations, the method for predicting infection can include tracking a set of infection scores over time. Based on the measured optical properties, the turbidity of the patient's bodily fluid can be estimated, and an infection score can be generated based on the estimated turbidity (e.g., expressed in terms of NTU or similar units). In some variations, the estimated turbidity can be scaled to an infection score scale.

[0169]

[0198] In some variations, the infection score (which may be generated for each PD cycle or daily) can be compared to a set of predetermined infection development criteria to predict the onset of an infection state. For example, a positive infection state can be predicted in response to the infection score exceeding a predetermined threshold (e.g., exceeding a predetermined number of consecutive positive infection samples) and / or increasing over time relative to a patient-specific baseline. For example, an infection can be predicted in response to the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods. In contrast, in some variations, the absence of infection can be predicted when the number of positive infection scores falls below a predetermined threshold. In some variations, a false-positive infection state can be identified if the infection score does not exceed a predetermined threshold for one or more consecutive measurement periods. For example, a false-positive can be identified if the infection score threshold is not met for three consecutive sample measurements.

[0170]

[0199] Tracking infection scores over time instead of relying on a single, separate sample can improve the sensitivity and specificity of infectious disease diagnosis by reducing false positives. For example, FIG. 21A shows an infection detection graph of infection scores plotted over time. An infection score of 100 can correspond to the International Society for Peritoneal Dialysis (ISPD) threshold for infection in a positive patient. The first graph (2100) shows that only one sample out of 12 consecutive samples has an infection score above the ISPD threshold. However, a single sample above the ISPD threshold may represent a false positive.

[0171]

[0200] In contrast, in some variations of the methods and systems described herein, the infection development prediction criteria can include the number of infection scores above a predetermined threshold. Specifically, the onset of a positive infection state can be predicted when the number of consecutive positive infection scores exceeds a predetermined threshold (e.g., two samples). Additionally or alternatively, the infection development prediction criteria can include the sign and / or rate of change of the infection score. For example, the second graph (2110) shows multiple samples having infection scores above an ISPD threshold. Furthermore, the samples above the ISPD threshold are consecutive and have a positive slope, such that the onset of the patient's infection state is reliably predicted. In some variations, an indication of the predicted infection state can be output to the patient, for example, using a display of the patient monitoring device and / or a GUI display on a computing device.

[0172]

[0201] Additionally or alternatively, the infection score (which may be generated for each PD cycle or daily) can be tracked to predict resolution of the infection state. For example, FIG. 21B shows an infection detection graph (2120) of leukocyte concentration in a patient's bodily fluid (as measured conventionally ("leukocytes") and as estimated by the infection score described herein ("infection score")) plotted over time for a patient undergoing antibiotic treatment. The infection score closely tracks the downward trend in the measured leukocyte count, which helps demonstrate that the methods described herein can be used to predict resolution of a patient's infection. Specifically, as shown in FIG. 21B, the patient's actual leukocyte count initially exceeds the ISPD threshold in the case of peritonitis. Over time, the leukocyte count decreases with antibiotic treatment and remains around the ISPD threshold of approximately 100 cells / μL. Similarly, a set of generated infection scores initially exceeds a predetermined threshold and then declines until reaching an equilibrium state around a predetermined optical score threshold. Therefore, the correlation between infection score and white blood cell count suggests that infection score may be a proxy for white blood cell count.

[0173]

[0202] In some variations, the set of criteria (e.g., thresholds, parameters) used to predict infection can be generated based on one or more machine learning techniques, such as a random forest model. In some variations, the set of predetermined criteria can be generated based on a multi-target linear regression relating a set of inputs (e.g., 90-degree and 180-degree offset light intensity measurements at three wavelengths for a predetermined number of samples) to concentrations of white blood cells, red blood cells, triglycerides, proteins, etc. These continuous variable predictions can be converted to a binary outcome (negative infection, positive infection) based on a set infection threshold.

[0174]

[0203] In some variations, the set of predetermined criteria can be generated based on single-target random forest classification, which associates a set of inputs with a single binary target. The infection threshold can be initially defined by a white blood cell concentration of about 100 cells / μL and / or a polymorphonuclear cell family (PMN) neutrophil concentration of about 50%. Additionally or alternatively, the methods and apparatus described herein can be used with any data modeling and / or machine learning algorithms and / or models, including, but not limited to, multi-target regression and classification, decision tree models, deep neural network models, Bayesian networks, clustering models, and / or other algorithms and / or models.

[0175] Fluid flow estimation

[0204] In some variations, estimating the fluid flow rate (e.g., flow on, flow off) of the patient fluid through the fluid conduit can enable independent determination of the cycler's operating state (pumping state), such as to determine when a unique drain cycle begins and ends (and optically measures the fluid). Furthermore, the power consumption and optical sensor usage of the patient monitoring device can be optimized based on the patient fluid flow state. For example, the optical sensor can measure the patient fluid more frequently at night when the cycler is pumping new fluid through the fluid conduit, and reduce optical sensor usage when the patient fluid is stationary in the fluid conduit. This can extend the life of one or more components of the patient monitoring device, such as the illumination source. In some variations, one or more fluid flow estimation methods can be selected based on predetermined conditions (e.g., power status, schedule, processing load). As another example, knowledge of the fluid flow rate (on or off) can be used to adjust the process of estimating particle concentration in the patient fluid based on particle settling characteristics (when the cycler pump is off), as described above.

[0176]

[0205] In some variations, the fluid flow rate of the patient's body fluid can be estimated based on one or more optical measurements of the patient's body fluid using the optical sensors described herein. For example, when estimating the fluid flow rate, one or more 180-degree scattering angle light intensity measurements of the patient's body fluid can be measured because 180-degree measurements can have a relatively high signal-to-noise ratio when compared to scattering signals at other angles. In some variations, the patient's body fluid can be sampled at a rate of about 50 Hz to reduce aliasing.

[0177]

[0206] The frequency response of the optical measurements can then be generated and used to estimate fluid flow rate. For example, a fast Fourier transform (FFT) can be applied to a set of optical measurements to determine whether the frequency of the pulse signal in the optical measurements approximates the known pump frequency of the cycler. For example, a conventional cycler can pump fluid at a flow on / off cycle frequency of about 0.05 Hz to about 2 Hz. Figures 22A and 22B are fluid flow rate graphs (2200, 2202, 2210) of plotted optical sensor measurements of a fluid. The optical measurements include variable fluid flow rates (on, off) due to cycler pumping. For example, flow-on intervals are annotated in each of Figures 22A and 22B. Independently, a fast Fourier transform (FFT) can be applied to the set of optical measurements to determine whether, at any measurement time, the frequency of the optical measurement signal (voltage) is about 0.05 Hz to about 0.2 Hz, which can be used to indicate the occurrence of a flow-on interval. Conversely, the FFT can be used to determine if the frequency of the optical measurement signal is between about 0.05 Hz and about 0.2 Hz, which can be used to indicate the occurrence of a flow-off interval.

[0178]

[0207] In some variations, the fluid flow rate of the patient's body fluid can be estimated using one or more filters. For example, the fluid flow rate can be estimated using one or more low-pass and / or high-pass filters. Fluid flow estimation based on low-pass and / or high-pass filters can reduce the computational burden, for example, relative to an FFT-based fluid flow estimation algorithm. For example, the low-pass filter can include a frequency between about 75 Hz and about 90 Hz, and the high-pass filter can include a frequency between about 50 Hz and about 70 Hz. The optical measurement signal that has passed one or more of the filters can be analyzed to determine a fluid flow on / off state. For example, a filtered signal that includes a predetermined number of pulses (e.g., three pulses) above a predetermined threshold can correspond to a fluid flow on state.

[0179]

[0208] Thus, in some variations, an on or off fluid flow state can be determined based on the estimated fluid flow rate. In some variations, the patient's body fluid can be illuminated and measured in response to detecting an on state (such as to estimate turbidity), and illumination can be terminated in response to detecting an off state (to conserve energy). This can reduce power consumption and extend the life of the illumination source by reducing unnecessary and / or constant optical measurements.

[0180]

[0209] For example, optical measurements for fluid flow rate estimation can be performed at predetermined intervals. For example, these optical measurements can be performed in a "listening" state for approximately 30 seconds. If the flow is off, subsequent sets of optical measurements for fluid flow rate estimation can be repeated after another predetermined rest interval, such as 5 minutes. However, if the flow is on, optical measurements for turbidity estimation can be performed, such as by using the method described above.

[0181]

[0210] As another example, patient fluid can be measured at predetermined intervals throughout a drainage cycle, and fluid flow can be estimated. For example, the predetermined intervals can include the beginning, middle, and end of pumping new fluid through the fluid conduit during the drainage cycle. In some cases, the predetermined intervals can include a set of intervals (e.g., 1 minute, 2 minutes, 3 minutes, 4 minutes, 5 minutes, 10 minutes, etc.) when the new fluid is stationary within the fluid conduit. Additionally or alternatively, one or more non-optical sensors can be used to estimate fluid flow. For example, an accelerometer can be configured to measure vibrations of the fluid conduit corresponding to fluid flow. As another example, a pressure sensor can be configured to measure periodic or intermittent pressure cycles within the fluid conduit. As another example, a microphone can be configured to measure audible sounds corresponding to pumping.

[0182]

[0211] In some variations, the system can be configured to distinguish between true fluid flow on conditions and “false positive” fluid flow on conditions, such as during one or more cycler setup steps. For example, a false positive fluid flow on condition can occur due to the priming step of a CCPD exchange, during which fluid intermittently flows through the drain line. Because measuring and detecting during such a priming step (or after any other brief period of fluid flow that is not part of a drain cycle) unnecessarily utilizes the device, identifying such false positive fluid flow conditions can help optimize device resources and / or service life (e.g., reducing power consumption, reducing memory storage usage, reducing unnecessary consumption of optical sensor life, etc.). In some variations, a false positive fluid flow on condition can be identified based on detecting one or more of a predetermined number of measured pump pulses measured over a predetermined duration of fluid flow. Additionally or alternatively, in some variations, a false positive can be identified when a fluid flow on condition is not identified for two or more consecutive periods. For example, a measurement of three pump pulses within a first measurement period having a duration of approximately 30 seconds may correspond to a fluid flow on state. However, if a pump pulse threshold (e.g., three pulses) is not met within a second measurement period having a duration of approximately 30 seconds measured after the first period, a false positive may be identified. In some variations, a predetermined test delay period (e.g., 30 seconds) may be applied between the first and second period measurements. If a pulse is detected and a false positive fluid flow on state is not identified, the system may proceed assuming that the fluid flow is in fact on and subsequent optical properties of the fluid may be measured and analyzed as described herein.

[0183]

[0212] In some variations, the measurement periods (e.g., first measurement period, second measurement period) as described above can be from about 10 seconds to about 15 minutes, from about 20 seconds to about 5 minutes, from about 20 seconds to about 2 minutes, from about 20 seconds to about 1 minute, or from about 20 seconds to about 40 seconds, including all ranges and intermediate subvalues. In some variations, the test delay period can be from about 10 seconds to about 15 minutes, from about 20 seconds to about 5 minutes, from about 20 seconds to about 2 minutes, from about 20 seconds to about 1 minute, or from about 20 seconds to about 40 seconds, including all ranges and intermediate subvalues.

[0184] Air Bubble Detection

[0213] In some variations, the patient's body fluid may contain inhomogeneous objects, such as air bubbles, that add noise to the optical measurements and subsequent fluid analysis. In some variations, air bubbles in a fluid conduit can be detected based at least in part on optical measurements using the sensors described herein. FIG. 24 is an air bubble graph (2300) of optical sensor measurements plotted over time. For example, FIG. 24 is annotated with flow-on intervals and air bubbles. In some variations, the frequency response of the optical measurements can be used to detect air bubbles. For example, a fast Fourier transform (FFT) can be applied to the optical measurements to generate a corresponding frequency response plot (not shown). Additionally, a filter (e.g., a low-pass filter) can be applied to identify air bubbles from flow-on / off transitions. Patient body fluid containing any detected air bubbles can be excluded from analysis for infections, etc. In some variations, the patient can be notified and / or instructed to remove air bubbles in the fluid conduit.

[0185] Other Monitoring Applications

[0214] In some variations, a method for predicting a patient's immune response can be based at least in part on the measured optical measurements. For example, an elevated white blood cell count may indicate a comorbidity that results in a high immune response, such as that resulting from cancer, but not limited to infection. Immune responses resulting from different causes typically correspond to unique percentage profiles of one or more types of white blood cells. Infections, for example, have a higher percentage of polymorphonuclear cells. The optical properties of polymorphonuclear cells differ from other types of white blood cells, such as eosinophils and basophils, which have different sizes and / or shapes. Thus, the optical profile of a given white blood cell type can aid in diagnosing the underlying cause of elevated white blood cell levels.

[0186]

[0215] In some variations, a method for predicting bleeding in a patient can be based on the measured optical properties. For example, a measured overall turbidity of the patient's bodily fluid above a first predetermined threshold, combined with an estimated white blood cell count below a second predetermined value, can indicate bleeding. The overall turbidity can be measured at a non-cell-specific wavelength (e.g., 800-900 nm), and the estimated white blood cell count can be determined based on optical measurements taken in a white blood cell-specific wavelength range. In some variations, one or more of the patient and a healthcare provider can be notified of possible bleeding.

[0187]

[0216] In some variations, the method for predicting fibrin concentration can be based on measured optical measurements. For example, highly variable optical measurements may indicate the presence of large particulate matter (e.g., solids, clumps, chunks) in a patient's bodily fluid. High fibrin content may increase the risk of clogging fluid conduits.

[0188]

[0217] In some variations, a method for predicting infection development for patients with ascites drainage can be based on measured optical characteristics. Ascites drainage involves either a permanently attached device (e.g., a peritoneal port or catheter or a central venous catheter) or a temporarily invasive hospital procedure such as large-volume paracentesis. Catheter leaks or blockages can be detected by comparing the drainage flow rate or pressure to a baseline value. For patients with frequent ascites drainage (e.g., more than twice a week), patient-specific baseline values can be developed over approximately three months or after approximately 25 drainage sessions have been measured. For patients with less frequent drainage, such as monthly, it may be more practical to compare the patient's drainage characteristics to population baseline values. For those with less frequent drainage, data can still be collected to establish personalized baseline values. When a patient monitoring device is attached to the drainage line, infections can be monitored by measuring the patient's body fluids and comparing them to individual patient baseline values.

[0189] Remote Monitoring and Clinical Workflow

[0218] In some variations, healthcare providers can remotely monitor patients using methods and systems such as those described herein, which can enable early detection and treatment of patients (e.g., with antibiotics, other antimicrobial agents, etc. for treating infections). Such early detection and treatment can then help to avoid the progression of infections and / or other medical conditions, thereby reducing hospitalizations necessitated by infections. While the following description primarily refers to treatment regimens that include the administration of antibiotics, it should likewise be understood that such remote monitoring can be performed with respect to treatment regimens that include the administration of any suitable antimicrobial agent (e.g., antibiotics, antifungals, antivirals, etc.).

[0190]

[0219] For example, Figure 27A shows a typical timeline for the conventional standard of care for a patient with peritonitis. Typically, a patient contacts their healthcare provider upon noticing a visually cloudy sample of the effluent dialysate (e.g., as suspected as a result of a "newspaper" test, in which a written text sample is not readily visible throughout the volume of effluent dialysate). The time point at which the effluent becomes visually cloudy is usually 3-5 days after infection has developed, and in response, healthcare providers typically prescribe a single broad-spectrum antibiotic treatment to address the advanced infection. However, this approach has a limited success rate of approximately 72%, as approximately 28% of patients still ultimately are hospitalized as a result of antibiotic treatment failure. Furthermore, the hospital mortality rate among these hospitalized patients is approximately 3.5%. Therefore, not only does the conventional standard of care rely on patient compliance to actively monitor patient samples for visual cloudiness, but the conventional standard of care still results in a significant portion of the patient population experiencing adverse patient outcomes, such as hospitalization or even death.

[0191]

[0220] In contrast, remote patient monitoring using the methods and systems described herein can be used to effectively detect infections shortly after they occur and prompt a course of action to prevent the progression of infection and other disease conditions. For example, as shown in FIG. 27B, a healthcare provider can receive notification of a predicted patient infection status (e.g., probability of infection) approximately 8-12 hours after the onset of an infection. The patient is then prompted (or taken) to a clinic for culture sample collection and receives antibiotic treatment (e.g., broad-spectrum antibiotics) similar to what would typically occur after 3-5 days under conventional standard of care. After administration of the broad-spectrum antibiotics, the patient can continue dialysis at home, and the effectiveness of the antibiotics can be remotely monitored as described above. In other words, a healthcare provider may be able to remotely determine whether the broad-spectrum antibiotics were successful in treating the infection. The success rate of broad-spectrum antibiotics is generally higher when administered earlier than when administered later, so this early detection provided by the methods and systems described herein can aid in the effectiveness of the broad-spectrum antibiotics. A patient can be classified as healthy (e.g., case resolved) if they are successfully treated with a broad-spectrum antibiotic. If the patient's infection appears to continue progressing (e.g., as determined using the methods and systems described herein), a healthcare provider can use results from a culture sample (e.g., approximately 36-48 hours after the onset of infection) to shift treatment toward a more targeted or specific antibiotic. At this point in the clinical workflow, the patient can be targeted with a specific antibiotic more quickly after the onset of infection, compared to the traditional standard of care, where the first treatment step is delayed due to a delay in infection detection.

[0192]

[0221] During administration of the specific antibiotic, the patient can again continue dialysis at home, and the effectiveness of the antibiotic can continue to be monitored remotely as described above. In other words, the patient's healthcare provider can monitor the patient's infection status (e.g., based on a real-time device-generated infection score) to determine whether the infection has subsided. If the infection is bacterial, the patient's infection is expected to resolve given the specificity of the antibiotic (e.g., approximately 5 days after the onset of the infection, depending on the bacterial resistance). Only fungal infections that are unresponsive to antibiotics are expected to result in hospitalization. Therefore, using remote patient monitoring using the methods and systems described herein, a patient's bacterial infection can be addressed early and effectively, with only a small subset of fungal infection patients (approximately 3% of cases) requiring more intensive treatment, such as hospitalization.

[0193]

[0222] 28 illustrates a system implemented in a clinical workflow using the methods and systems described herein. Generally, a system 2800 for monitoring a patient 2810 can include a patient monitoring device 2820 that interfaces with the patient 2810 and can be configured to communicate with a network 2830 (e.g., a cloud-based network or other suitable network of computing devices) in a wireless or wired manner so that data received from the patient monitoring device 2820 can be analyzed remotely (non-locally) from the patient. Multiple patients 2810 can each have their own patient monitoring device 2820 that communicates in this manner. Alternatively, several patients can share a patient monitoring device 2820 (e.g., multiple patients in a single household), where data from different patients can be distinguished using patient identification information, etc. Alternatively, data from the patient monitoring devices (2820) may be communicated to one or more intervening computing devices (not shown), which may further communicate the data to the network (2830). Additionally, in some variations, the data may be analyzed locally by one or more processors of the intervening computing devices. Patient data (and / or information derived from the medical-related data) received over the network may be stored, for example, on one or more servers.

[0194]

[0223] In some variations, the patient data (and / or information derived from the patient data) may be accessible by one or more third-party computing devices. For example, as shown in FIG. 28 , such data or information may be accessible by a third-party computer device (e.g., a tablet (2840), a mobile phone (2842), a laptop computer (2833), a desktop computer (2846), etc.) in communication with the network (2830). It should also be understood that any other computing device operated by the patient may similarly access the information via the network (2830). For example, in some variations, a user (e.g., a healthcare provider, a patient, etc.) may access and / or be notified of the patient data via a portal or other suitable graphical user interface. Information (and its uses) that may be accessible to other computing devices is described further below.

[0195]

[0224] FIG. 29 illustrates in more detail a status-based clinical workflow using the methods and systems described herein. Patient status and other patient information can be tracked via a graphical user interface (GUI) to enable a user, such as a healthcare provider, to manage remotely monitored patients. For example, as shown in FIG. 29 , a user can access a patient database using a login (2910) (e.g., a user ID and password, other suitable authentication method, etc.). The user can be provided with a list of accessible patients (2012) from which to select or view information related to those patients (e.g., name, contact information, medical history, current medications, predicted infection status, etc.). The patients accessible to a user can be personalized or otherwise restricted. For example, a user who is a healthcare provider (e.g., a physician or clinic administrator) can be limited to accessing a patient list (2912) that includes only patients under their care. As another example, a user associated with a medical institution (e.g., a clinic) can be limited to accessing a patient list (2912) that includes patients under their care at that institution. The patient list (2912) can be filtered based on factors such as the patient's personal characteristics (e.g., age, sex, duration of PD treatment, frequency of infections, etc.) and / or patient condition (2920) or other patient status (e.g., as described in more detail below). Additionally, the GUI and / or other communication system can provide notifications and / or allow recording regarding patient status.

[0196]

[0225] 29 also illustrates an exemplary state diagram of multiple patient states, referred to herein as Stages S-0 through S-5. A patient may generally progress from Stage S-0 to Stage S-5 as their condition worsens (e.g., as the infection progresses).

[0197]

[0226] Stage S-0 corresponds to a healthy patient state (e.g., a state in which no infection is predicted). Infection in a patient can be predicted (e.g., using the devices and methods described herein), thereby progressing the patient from stage S-0 ("healthy state") to stage S-1 ("clinic first check"), which corresponds to a patient state requiring initial clinic checkup. In some variations, the transition (2930) between stage S-0 and stage S-1 can occur approximately 8-12 hours after the onset of infection.

[0198]

[0227] While in stage S-1, the patient may go to the clinic within approximately 12 hours for culture sampling. The patient can be tested for infection at the clinic. If there is no infection, the patient can return to stage S-0 (2940). If there is an infection, the patient can receive broad-spectrum antibiotics along with any other suitable initial treatments. After receiving the initial antibiotic treatment, the patient can proceed to stage S-3 ("Monitoring the effectiveness of the initial antibiotics").

[0199]

[0228] During stage S-2, the patient may spend a period (e.g., 48 hours) at home, dialyzing and using the patient monitoring devices and methods described herein. A healthcare provider may remotely determine whether the broad-spectrum antibiotic was successful in clearing the infection (e.g., by tracking the infection score). If the infection is cleared (e.g., based on a downward trend in the infection score), the patient may return to stage S-0 (2942). If the infection appears to be progressing (e.g., based on an upward trend in the infection score), the patient may receive a more targeted or specific antibiotic (e.g., after a 48-hour period). The specific antibiotic may be determined at least in part based on culture sample results for the patient. In some variations, if the culture sample results suggest a fungal infection, the patient may move directly to stage S-4 (described below), depending on the medical procedure. Otherwise, after receiving the specific antibiotic, the patient may move to stage S-3 ("Monitoring the effectiveness of the indicated antibiotic").

[0200]

[0229] During Stage S-3, the patient can dialyze at home and use the patient monitoring systems and methods described herein. During this time, similar to Stage S-2, a healthcare provider can remotely determine whether the specific antibiotic was successful in clearing the infection (e.g., by tracking the infection score). In many cases, the specificity of the administered antibiotic will result in the patient's infection being cleared (e.g., reflected by a downward trend in the infection score). If the infection is cleared, the patient can return to Stage S-0 (2944). However, if the infection continues to progress (e.g., based on an upward trend in the infection score), the patient may be hospitalized and move to Stage S-4 ("Hospitalization"). In many cases, a fungal infection alone may lead to the patient's hospitalization.

[0201]

[0230] While in stage S-4, the patient may receive appropriate hospital treatment. If the patient's infection resolves (e.g., as determined by a healthcare provider), the patient may return to stage S-0 (2046). However, if the infection continues to progress and it is determined (e.g., as determined by a healthcare provider) that catheter removal is necessary, the patient's catheter may be removed and the patient may be transferred to stage S-5 for hemodialysis ("transfer to hemodialysis") (2938). In some variations, the shift to stage S-5 for hemodialysis treatment may be permanent; a patient in stage S-5 may not return to peritoneal dialysis. For example, a patient permanently classified as stage S-5 may be classified as a former patient, etc., in the patient monitoring system.

[0202]

[0231] Thus, early identification or prediction of infection in a patient using the patient monitoring methods and systems described herein, alone or in combination with remote monitoring and clinical workflow as described above, can enable early intervention with appropriate treatment and help avoid advanced patient conditions, such as those requiring hospitalization or hemodialysis.

[0203]

[0232] As discussed above, remote monitoring can include an interface for a user, such as a healthcare provider, to monitor trends in infection scores, patient status, etc., and / or otherwise help manage patient care. For example, Figures 28-33 show exemplary variations of GUIs that provide patient information and aid in patient management.

[0204]

[0233] FIG. 30 shows an exemplary variation of a GUI (3000) showing a record for a patient subject in stage S-0 ("healthy state"). The record may include patient identification information (3010), such as a code, name, electronic medical record, etc., associated with the patient subject. A patient status bar (3012) may further identify the patient's state (here, stage S-0) and display historical values of the patient's infection score over time (3020). Overall, a patient in stage S-0 is in a healthy state, and the monitoring system is relatively passive or non-demanding from the user's perspective (e.g., a healthcare provider's perspective) in that the user is not prompted or notified to perform daily monitoring or testing for a healthy patient subject.

[0205]

[0234] FIG. 31 illustrates an exemplary variation of a GUI (3100) showing a record for a target patient in stage S-1 (“Clinic 1 Exam”). The GUI (3100) includes one or more fields configured to receive one or more user inputs (and / or retrieve from a database) to help manage treatment and / or administration tasks related to the patient during the clinic exam, such as whether a culture sample was taken (3110), whether an initial antibiotic was administered (3112), and / or what type of initial antibiotic, if any, was administered (3114). After this information is provided and stored, the patient can move to stage S-2 as described above. Additionally, like the GUI illustrated in FIG. 30, the GUI (3100) can include historical values of the patient's infection score displayed over time (3120).

[0206]

[0235] 32A and 32B show exemplary variations of GUIs (3200, 3200′) showing a record of a subject patient in stage S-2 (“Monitoring Effectiveness of Initial Antibiotics”). The GUI (3200) includes one or more fields configured to receive one or more user inputs useful for managing patient care. For example, the GUI (3200) may include fields for receiving one or more user inputs (and / or retrieving from a database), such as whether the culture sample was positive (3210), and if so, the type of pathogen in the culture sample, the type of specific (adjusted) antibiotic recommended or prescribed (3214), the white blood cell count (3216), and (PMN%) (3218). The systems and methods described herein can be used to remotely monitor a patient while they are dialysis at home to assess the effectiveness of broad-spectrum antibiotic treatment. Additionally, the GUI (3200) may include historical values of the patient's infection score displayed over time (3220). Here, GUI (3200) in Figure 32A displays a downward trend (3200) in infection scores for a patient who responded positively to the administered broad-spectrum antibiotic. GUI (3200') in Figure 32B may be similar to GUI (3200), except that GUI (3200') displays a patient trend (3220') in infection scores indicating that the patient's infection has worsened, thereby moving the patient to stage S-3.

[0207]

[0236] 33A and 33B show exemplary variations of GUIs (3300, 3300′) showing a record of a subject patient in stage S-3 (“Monitoring Effectiveness of Adjusted Antibiotics”). The GUI (3300) includes one or more fields configured to receive one or more user inputs useful for managing patient care. For example, the GUI (3300) may include a field for receiving one or more user inputs (and / or pulling from other databases), such as whether the patient should be escalated to hospitalization (3310). The systems and methods described herein can be used to remotely monitor patients while they are dialysis at home to assess the effectiveness of specific antibiotic treatment. Additionally, the GUI (3300) displays a downward trend in infection scores (3320) for patients who responded positively to the specific antibiotics administered. GUI (3300') can be similar to GUI (3200'), except that GUI (3300') shows a patient trend in infection scores (3320') indicating that the patient's infection has worsened, thereby moving the patient to stage S-4.

[0208]

[0237] 34 illustrates an exemplary variation of a GUI (3400) showing a record of a subject patient in stage S-4 ("admitted") receiving hospital treatment. The GUI (3400) may display various patient characteristics and / or medical treatment details, such as recording whether the patient's catheter was removed (3410) during the course of hospital treatment. Upon completion of hospital treatment, if the input to this question is "no," the patient may move to stage S-0. If the input to this question is "yes," the patient may move to stage S-5.

[0209]

[0238] 35 illustrates an exemplary variation of GUI (3500) showing a record of a subject patient in stage S-5 ("transfer to hemodialysis"). In this example, GUI (3500) shows the propensity of this subject patient in stage S-5 to permanently transfer to hemodialysis after his catheter is removed. In some variations, GUI (3500) can remain as a permanent record of the subject patient's status even if the subject patient is no longer being remotely monitored due to peritonitis. In other variations, the subject patient's record can be deleted after a predetermined period of time (e.g., six months, one year, five years, etc.) and / or as part of database cleanup and maintenance, etc.

[0210] Illustrative Embodiments

[0239] Embodiment A1. A method for predicting an infection in a patient, comprising: illuminating the patient's body fluid within the fluid conduit from a plurality of illumination directions; measuring optical properties of the illuminated patient fluid using one or more sensors; predicting an infection status of the patient based at least in part on the measured optical properties; A method comprising:

[0211]

[0240] Embodiment A2. The method of claim A1, wherein the plurality of illumination directions includes a first illumination direction and a second illumination direction orthogonal to the first illumination direction.

[0212]

[0241] Embodiment A3. The method of claim A2, wherein the patient's predicted infection status is based at least in part on one or more 90 degree scatter angle light intensity measurements from one or more sensors.

[0213]

[0242] Embodiment A4. The method of claim A3, wherein the patient's predicted infection status is based at least in part on one or more 180 degree attenuated angle light intensity measurements from one or more sensors.

[0214]

[0243] Embodiment A5. The method of claim A1, wherein the plurality of illumination directions includes a first illumination direction and a second illumination direction that is offset 180 degrees from the first illumination direction.

[0215]

[0244] Embodiment A6. The method of claim A1, wherein illuminating the patient's body fluid includes illuminating the patient's body fluid with a first wavelength from a first illumination direction and with a first wavelength from a second illumination direction, the first illumination direction and the second illumination direction extending along a first plane.

[0216]

[0245] Embodiment A7. The method of claim A6, wherein illuminating the patient's bodily fluid includes illuminating the patient's bodily fluid along at least a first plane and along a second plane that is substantially parallel to the first plane.

[0217]

[0246] Embodiment A8. The method of claim A1, wherein illuminating the patient's bodily fluid includes illuminating the patient's bodily fluid with a first wavelength of about 800 nm to about 900 nm.

[0218]

[0247] Embodiment A9. The method of claim A8, wherein illuminating the patient's body fluid includes sequentially illuminating the patient's body fluid with multiple wavelengths, including the first wavelength.

[0219]

[0248] Embodiment A10. The method of Claim A9, wherein the plurality of wavelengths includes a second wavelength from about 400 nm to about 450 nm and a third wavelength from about 500 nm to about 550 nm.

[0220]

[0249] Embodiment A11. The method of claim A10, wherein illuminating the patient's body fluid includes sequentially illuminating the patient's body fluid with the third wavelength, the first wavelength, and then the second wavelength.

[0221]

[0250] Embodiment A12. The method of claim A10, wherein the plurality of wavelengths includes a fourth wavelength from about 230 nm to about 290 nm.

[0222]

[0251] Embodiment A13. The method of claim A1, wherein the optical properties include one or more of a light scattering angle and an attenuation detection angle.

[0223]

[0252] Embodiment A14. The method of claim A1, wherein predicting infection status includes generating an infection score.

[0224]

[0253] Embodiment A15. The method of claim A14, further comprising estimating the turbidity of the patient's bodily fluid based at least in part on the measured optical properties, and wherein the infection score is based at least in part on the estimated turbidity.

[0225]

[0254] Embodiment A16. The method of claim A15, wherein predicting the infection status comprises predicting infection responsive to the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods.

[0226]

[0255] Embodiment A17. The method of claim A15, wherein predicting infection status comprises predicting infection according to an increase in infection score from a patient baseline over time.

[0227]

[0256] Embodiment A18. The method of claim A15, wherein predicting infection status includes predicting infection based on a rate of change of infection score over time.

[0228]

[0257] Embodiment A19. The method of claim A15, wherein predicting the infection status includes predicting infection according to any one or more of: the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods; the infection score increasing over time from a patient baseline; and the infection score having an increasing rate of change over time.

[0229]

[0258] Embodiment A20. The method of claim A1, wherein predicting infection status comprises predicting probability of infection.

[0230]

[0259] Embodiment A21. The method of claim A1, wherein the fluid conduit is coupled to a peritoneal dialysis device flow path.

[0231]

[0260] Embodiment A22. The method of claim A1, wherein the fluid conduit is coupled to a peritoneal dialysis machine tubing set.

[0232]

[0261] Embodiment A23. The method of claim A1, wherein the fluid conduit is coupled to an inlet of a peritoneal dialysis tubing set.

[0233]

[0262] Embodiment A24. The method of claim A1, wherein the fluid conduit is coupled to an outlet of a peritoneal dialysis tubing set.

[0234]

[0263] Embodiment A25. The method of claim A1, wherein the fluid conduit is coupled to a drain line of a peritoneal dialysis cycler tubing set.

[0235]

[0264] Embodiment A26. The method of claim A1, wherein the fluid conduit is coupled to a drain line extension configured to be coupled to a drain line of a peritoneal dialysis cycler tubing set.

[0236]

[0265] Embodiment A27. The method of claim A1, wherein the fluid conduit is coupled to a peritoneal dialysis cycler tubing set patient line.

[0237]

[0266] Embodiment A28. The method of claim A1, further comprising estimating a fluid flow rate in the fluid conduit based at least in part on the measured optical properties, and wherein illuminating the patient fluid comprises activating the illumination based on the estimated fluid flow rate.

[0238]

[0267] Embodiment A29. The method of claim A28, further comprising determining a fluid flow state based on the estimated fluid flow rate, including detecting at least one of an on state and an off state, and illuminating the patient body fluid includes activating illumination in response to detecting the on state and terminating illumination in response to detecting the off state.

[0239]

[0268] Embodiment A30. The method of claim A28, further comprising identifying a false positive fluid flow condition based on the estimated fluid flow rate.

[0240]

[0269] Embodiment A31. The method of claim A29, wherein identifying a false positive fluid flow condition includes detecting a predetermined number of pulses in less than each of two or more consecutive measurement periods.

[0241]

[0270] Embodiment A32. The method of claim A29, wherein detecting the on state includes detecting a predetermined number of pulses in each of two or more consecutive measurement periods.

[0242]

[0271] Embodiment A33. The method of claim A32, wherein two or more consecutive measurement periods are separated by a predetermined delay period.

[0243]

[0272] Embodiment A34. The method of claim A29, wherein estimating the fluid flow rate is based at least in part on applying one or more of a low-pass filter and a high-pass filter to the measured optical properties.

[0244]

[0273] Embodiment A35. The method of claim A1 further comprising initiating the illuminating and measuring optical properties of the patient's body fluid based on user input.

[0245]

[0274] Embodiment A36. The method of claim A1 further comprising detecting air bubbles in the fluid conduit based at least in part on the optical measurements.

[0246]

[0275] Embodiment A37. The method of claim A1 further including providing an indication of the predicted infection status to the user.

[0247]

[0276] Embodiment A38. The method of claim A1 further comprising predicting a particle concentration in the patient's bodily fluid based at least in part on the measured optical properties.

[0248]

[0277] Embodiment A39. The method of claim A1 further comprising predicting bleeding in the patient based at least in part on the measured optical properties.

[0249]

[0278] Embodiment A40. The method of claim A1 further comprising predicting an immune response of the patient based at least in part on the measured optical properties.

[0250]

[0279] Embodiment A41. The method of claim A1 further comprising predicting infection development for an ascites drainage patient based at least in part on the measured optical properties.

[0251]

[0280] Embodiment A42. The method of claim A1 further comprising predicting the fibrin content of the patient's bodily fluid based at least in part on the measured optical properties.

[0252]

[0281] Embodiment B1. A container for use in a fluid conduit, comprising: The entrance and The exit section, an optically transparent measurement section between the inlet section and the outlet section, the measurement section comprising at least two substantially planar surfaces, a rotational alignment feature, and a depth alignment feature; A container comprising:

[0253]

[0282] Embodiment B2. The vessel of claim B1, wherein the measuring portion includes an interior volume configured to receive a fluid, the interior volume including rounded corners.

[0254]

[0283] Embodiment B3. The container of claim B1, wherein the at least two substantially planar surfaces include a first plane generally perpendicular to a second plane.

[0255]

[0284] Embodiment B4. The container of claim B1, wherein the at least two substantially planar surfaces include a first planar surface opposed to a second planar surface.

[0256]

[0285] Embodiment B5. The container of claim B4, wherein the measuring portion includes a generally square cross-section.

[0257]

[0286] Embodiment B6. The container of claim B1, wherein at least a portion of the measuring portion is tapered.

[0258]

[0287] Embodiment B7. The container of claim B1, wherein the measuring portion comprises one or more of copolyester, acrylonitrile butadiene styrene, polycarbonate, acrylic, cyclic olefin copolymer, cyclic olefin polymer, polyester, polystyrene, Ultem, polyethylene glycol coated silicone, zwitterion coated polyurethane, polyethylene oxide coated polyvinyl chloride, amphiphilic polysilicone.

[0259]

[0288] Embodiment B8. The container of claim B1, further comprising an opaque connector connectable to the inlet or outlet port.

[0260]

[0289] Embodiment B9. The container of claim B8, wherein at least one of the inlet and outlet ports is connectable to a fluid conduit.

[0261]

[0290] Embodiment B10. The container of claim B9, further comprising one or more of a vent cap, a clamp, and a connector coupled to the fluid conduit.

[0262]

[0291] Embodiment B11. The container of claim B9, wherein the container is coupled to a peritoneal dialysis drain set extension tube.

[0263]

[0292] Embodiment B12. The container of claim B9, wherein the container is coupled to a peritoneal dialysis cycler tubing cassette.

[0264]

[0293] Embodiment B13. The container of claim B9, wherein the container is coupled to an inlet of a peritoneal dialysis cycler tubing cassette.

[0265]

[0294] Embodiment B14. The container of claim B9, wherein the container is coupled to a peritoneal dialysis drain bag connector.

[0266]

[0295] Embodiment B15. The container of claim B9, wherein the container is coupled to the proximal end of a peritoneal dialysis drain bag connector.

[0267]

[0296] Embodiment B16. The container of claim B9, wherein the container is attached to a drain bag of a urinary catheter or a Foley catheter.

[0268]

[0297] Embodiment B17. The container of claim B9, wherein the container is coupled to a central venous drain line.

[0269]

[0298] Embodiment B18. The container of claim B9, wherein the container is coupled to a hemodialysis blood circulation tubing set.

[0270]

[0299] Embodiment B19. The container of claim B9, wherein the container is coupled to an indwelling catheter.

[0271]

[0300] Embodiment B20. The container of claim B9 coupled to the proximal end of an indwelling catheter.

[0272]

[0301] Embodiment C1. A patient monitoring device comprising: The housing includes: a holder configured to releasably receive a portion of the fluid conduit; at least one illumination source configured to illuminate the received portion of the fluid conduit; at least one optical sensor configured to generate a signal; Equipped with the holder comprising one or more engagement features configured to orient the received portion of the fluid conduit at a predetermined rotational and vertical orientation relative to the at least one illumination source and the at least one optical sensor; Device.

[0273]

[0302] Embodiment C2. The device of claim C1, wherein the housing comprises a light seal.

[0274]

[0303] Embodiment C3. The device of claim C1, wherein the one or more engagement features are configured to orient the received portion of the fluid conduit by mating with alignment features of the received portion of the fluid conduit.

[0275]

[0304] Embodiment C4. The device of claim C1, wherein the one or more engagement features include an open slot.

[0276]

[0305] Embodiment C5. The apparatus of claim C1, wherein the at least one illumination source includes multiple illumination sources.

[0277]

[0306] Embodiment C6. The apparatus of claim C5, wherein the illumination source is configured to illuminate in a first illumination direction and a second illumination direction orthogonal to the first illumination direction.

[0278]

[0307] Embodiment C7. The apparatus of claim C5, wherein at least two of the illumination sources are configured to illuminate along a first plane at a first wavelength.

[0279]

[0308] Embodiment C8. The apparatus of claim C5, wherein at least two other of the illumination sources are configured to illuminate along a second plane substantially parallel to the first plane.

[0280]

[0309] Embodiment C9. The apparatus of claim C5, wherein the illumination source is configured to illuminate in a first illumination direction and a second illumination direction opposite the first illumination direction.

[0281]

[0310] Embodiment C10. The apparatus of claim C1, wherein the illumination source is configured to illuminate in a first illumination direction and a second illumination direction that is offset 180 degrees from the first illumination direction.

[0282]

[0311] Embodiment C11. The apparatus of claim C1, wherein the illumination source includes a first illumination source configured to emit light at a first wavelength between about 800 nm and about 900 nm.

[0283]

[0312] Embodiment C12. The apparatus of claim C1, wherein the illumination source includes a second illumination source configured to emit light at a second wavelength of about 400 nm to about 450 nm.

[0284]

[0313] Embodiment C13. The apparatus of claim C1, wherein the illumination source includes a third illumination source configured to emit light at a third wavelength between about 500 nm and about 550 nm.

[0285]

[0314] Embodiment C14. The apparatus of claim C1, wherein the illumination source includes a fourth illumination source configured to emit light at a third wavelength from about 230 nm to about 290 nm.

[0286]

[0315] Embodiment C15. The device of claim C1, wherein the at least one optical sensor includes multiple optical sensors.

[0287]

[0316] Embodiment C16. The apparatus of claim C1, wherein one or more of the at least one illumination source and the at least one optical sensor include an anti-reflective coating.

[0288]

[0317] Embodiment C17. The apparatus of claim C1, wherein the holder defines a longitudinal axis, and wherein the at least one optical sensor includes a plurality of optical sensors spaced apart parallel to the longitudinal axis.

[0289]

[0318] Embodiment C18. The device of claim C1, further comprising a controller configured to generate patient data based at least in part on said signal.

[0290]

[0319] Embodiment C19. The device of claim C1, wherein the patient data includes infection status.

[0291]

[0320] Embodiment C20. The device of claim C1 further comprising a display.

[0292]

[0321] Embodiment C21. The device of claim C1, further comprising a base, the housing being offset and spaced apart from the base.

[0293]

[0322] Embodiment C22. The device of claim C1, wherein the housing comprises a peritoneal dialysis cycler.

[0294]

[0323] Embodiment C23. The device of claim C1, wherein the housing comprises a hemodialysis machine.

[0295]

[0324] Embodiment C24. The device of claim C1, wherein the housing is configured to couple to one or more of a patient platform and a medical cart.

[0296]

[0325] Embodiment C25. The device of claim C1, wherein the housing comprises a peritoneal dialysis device fluid path.

[0297]

[0326] Embodiment C26. The device of claim C1, wherein the fluid conduit is coupled to a peritoneal dialysis tubing set.

[0298]

[0327] Embodiment C27. The device of claim C1, wherein the fluid conduit is coupled to a peritoneal dialysis cycler tubing set.

[0299]

[0328] Embodiment C28. The device of claim C1, wherein the fluid conduit is coupled to a peritoneal dialysis drain bag connector.

[0300]

[0329] Embodiment C29. The fluid conduit comprises: The entrance and The exit section, an optically transparent measurement section between the inlet section and the outlet section, the measurement section comprising at least two substantially planar surfaces, a rotational alignment feature, and a depth alignment feature; The apparatus of claim C1, comprising:

[0301]

[0330] Embodiment C30. The device of claim C29, wherein at least one of the rotational alignment feature and the depth alignment feature is configured to mate with one or more engagement features of the holder.

[0302]

[0331] Embodiment C31. The device of claim C1, further comprising a controller configured to generate patient data based at least in part on the signal.

[0303]

[0332] Embodiment C32. The device of claim C1, wherein the controller is located remotely from the housing, and the device further comprises a communications device configured to transmit data representing the signal to the controller.

[0304]

[0333] Embodiment C33. The device of claim C32, wherein the controller is configured to predict an infection score for the patient based at least in part on the signal.

[0305]

[0334] Embodiment C34. The device of claim C32, wherein the controller is configured to predict the patient's infection status in response to any one or more of: the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods; the infection score increasing over time from a patient baseline; and the infection score having an increasing rate of change over time.

[0306]

[0335] Embodiment C35. The device of claim C34, wherein the infection status comprises a probability of infection.

[0307]

[0336] Embodiment C36. The device of claim C32, wherein the fluid conduit is configured to receive a patient bodily fluid, and wherein the controller is configured to estimate a turbidity of the patient bodily fluid based at least in part on the signal, and wherein the infection score is based at least in part on the estimated turbidity.

[0308]

[0337] Embodiment C37. The device of claim C32, wherein the controller is configured to monitor trends in the infection score that are predictive of infection resolution in the patient.

[0309]

[0338] Embodiment C38. The device of claim C32, wherein the controller is configured to monitor trends in the infection score to predict infection resolution for the patient by predicting infection resolution in response to any one or more of the infection score falling below a predetermined threshold in each of one or more consecutive measurement periods, the infection score declining from a patient baseline over time, and the infection score having a declining rate of change over time.

[0310]

[0339] Embodiment D1. A method for remotely monitoring a patient, comprising: In one or more processors, receiving an optical property measurement of a patient fluid associated with the patient via a remote communication link; determining an infection score predictive of infection in the patient, the infection score based at least in part on the received optical property measurements; associating the patient as one of a plurality of patient infection states based at least in part on the determined infection score; A method comprising:

[0311]

[0340] Embodiment D2. The method of claim D1 further comprising notifying a user of an associated patient infection status.

[0312]

[0341] Embodiment D3. The method of claim D1 further comprising prompting a user to perform one or more predetermined patient treatment actions based on the associated patient infection status.

[0313]

[0342] Embodiment D4. The method of claim D3, wherein the one or more predetermined patient treatment actions include administering a broad-spectrum antimicrobial to the patient.

[0314]

[0343] Embodiment D5. The method of claim D3, wherein the one or more predetermined patient treatment actions include administering a pathogen-specific antimicrobial to the patient.

[0315]

[0344] Embodiment D6. The method of claim D3, wherein one or more predetermined patient treatment actions include remotely monitoring a trend in an infection score that predicts resolution of the patient's infection.

[0316]

[0345] Embodiment D7. The method of claim D3, wherein remotely monitoring a trend in the infection score that predicts infection resolution comprises predicting infection resolution as a function of the infection score decreasing from the patient baseline over time.

[0317]

[0346] Embodiment D8. The method of claim D7, wherein remotely monitoring a trend in the infection score that predicts infection resolution includes predicting infection resolution based on a rate of change in the infection score over time.

[0318]

[0347] Embodiment D9. The method of claim D7, wherein remotely monitoring the trend of the infection score that predicts infection resolution comprises predicting infection resolution in response to any one or more of the infection score falling below a predetermined threshold in each of one or more consecutive measurement periods, the infection score decreasing from patient baseline over time, and the infection score having a decreasing rate of change over time.

[0319]

[0348] Embodiment D10. The method of claim D1, wherein the plurality of patient infection states includes a first patient infection state corresponding to a healthy patient.

[0320]

[0349] Embodiment D11. The method of claim D1, wherein the plurality of patient infection states includes a second patient infection state corresponding to a patient presented to a health care provider.

[0321]

[0350] Embodiment D12. The method of claim D1, wherein the plurality of patient infectious conditions includes a third patient infectious condition corresponding to a patient who has received broad-spectrum antibiotic therapy.

[0322]

[0351] Embodiment D13. The method of claim D1, wherein the plurality of patient infection states includes a third patient infection state corresponding to a patient who has received pathogen-specific antimicrobial therapy.

[0323]

[0352] Embodiment D14. The method of claim D1, wherein the plurality of patient infection states includes a fourth patient infection state corresponding to a hospitalized patient.

[0324]

[0353] Embodiment D15. The method of claim D1, wherein the plurality of patient infection states includes a fifth patient infection state corresponding to a patient transitioned to hemodialysis.

[0325]

[0354] Embodiment D16. The method of claim D1, wherein the predicted infection is peritonitis.

[0326]

[0355] The foregoing description, for purposes of explanation, used specific terminology to provide a thorough understanding of the present invention. However, it will be apparent to those skilled in the art that specific details are not required to practice the present invention. Thus, the foregoing descriptions of specific variations of the present invention have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the invention to the precise forms disclosed, and obviously, many modifications and variations are possible in light of the above teachings. The variations have been chosen and described in order to best explain the principles of the invention and its practical application, so that those skilled in the art can best utilize the present invention and its various implementations with various modifications as suited to the particular use contemplated. It is intended that the following claims and their equivalents define the scope of the invention.

Claims

1. 1. A method for predicting an infection in a patient, comprising: illuminating the patient's body fluid within the fluid conduit from a plurality of illumination directions; measuring optical properties of the illuminated patient's body fluid with one or more sensors; predicting an infection status of the patient based at least in part on the measured optical properties; and A method comprising:

2. The method of claim 1 , wherein the plurality of illumination directions includes a first illumination direction and a second illumination direction orthogonal to the first illumination direction.

3. 3. The method of claim 2, wherein the predicted infection state of the patient is based at least in part on one or more 90 degree scattering angle light intensity measurements from the one or more sensors.

4. 4. The method of claim 3, wherein the predicted infection state of the patient is based at least in part on one or more 180 degree attenuated angle light intensity measurements from the one or more sensors.

5. The method of claim 1 , wherein the plurality of illumination directions includes a first illumination direction and a second illumination direction that is offset 180 degrees from the first illumination direction.

6. 10. The method of claim 1, wherein illuminating the patient's body fluid comprises illuminating the patient's body fluid with a first wavelength from a first illumination direction and with the first wavelength from a second illumination direction, the first illumination direction and the second illumination direction extending along a first plane.

7. 7. The method of claim 6, wherein illuminating the patient's body fluid comprises illuminating the patient's body fluid at least along the first plane and along a second plane substantially parallel to the first plane.

8. The method of claim 1 , wherein illuminating the patient's body fluid comprises illuminating the patient's body fluid with a first wavelength of about 800 nm to about 900 nm.

9. 9. The method of claim 8, wherein illuminating the patient's body fluid comprises sequentially illuminating the patient's body fluid with a plurality of wavelengths including the first wavelength.

10. 10. The method of claim 9, wherein the plurality of wavelengths comprises a second wavelength between about 400 nm and about 450 nm and a third wavelength between about 500 nm and about 550 nm.

11. 11. The method of claim 10, wherein illuminating the patient's body fluid comprises sequentially illuminating the patient's body fluid with the third wavelength, the first wavelength, and then the second wavelength.

12. The method of claim 10, wherein the plurality of wavelengths includes a fourth wavelength from about 230 nm to about 290 nm.

13. The method of claim 1 , wherein the optical properties include one or more of a light scattering angle and an attenuation detection angle.

14. The method of claim 1 , wherein predicting the infection status comprises generating an infection score.

15. 15. The method of claim 14, further comprising estimating a turbidity of the patient's bodily fluid based at least in part on the measured optical properties, and wherein the infection score is based at least in part on the estimated turbidity.

16. 16. The method of claim 15, wherein predicting the infection status comprises predicting infection in response to the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods.

17. 16. The method of claim 15, wherein predicting the infection status comprises predicting infection as a function of the infection score increasing over time from a patient baseline.

18. 16. The method of claim 15, wherein predicting the infection status comprises predicting infection based on a rate of change of the infection score over time.

19. 16. The method of claim 15, wherein predicting the infection status comprises predicting infection depending on any one or more of the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods, the infection score increasing from a patient baseline value over time, and the infection score having an increasing rate of change over time.

20. The method of claim 1 , wherein predicting the infection status comprises predicting a probability of infection.

21. The method of claim 1 , wherein the fluid conduit is coupled to a peritoneal dialysis machine flow path.

22. 10. The method of claim 1, wherein the fluid conduit is coupled to a peritoneal dialysis machine tubing set.

23. 10. The method of claim 1, wherein the fluid conduit is coupled to an inlet of a peritoneal dialysis machine tubing set.

24. 10. The method of claim 1, wherein the fluid conduit is coupled to an outlet of a peritoneal dialysis machine tubing set.

25. 10. The method of claim 1, wherein the fluid conduit is coupled to a drain line of a peritoneal dialysis cycler tubing set.

26. 10. The method of claim 1, wherein the fluid conduit is coupled to a drain line extension configured to be coupled to a drain line of a peritoneal dialysis cycler tubing set.

27. The method of claim 1 , wherein the fluid conduit is coupled to a patient line of the peritoneal dialysis cycler tubing set.

28. 10. The method of claim 1, further comprising estimating a fluid flow rate in the fluid conduit based at least in part on the measured optical property, and wherein illuminating the patient body fluid comprises activating an illumination based on the estimated fluid flow rate.

29. 29. The method of claim 28, further comprising determining a fluid flow state based on the estimated fluid flow rate, the determining including detecting at least one of an on state and an off state, and illuminating the patient body fluid includes activating illumination in response to detecting the on state and terminating illumination in response to detecting the off state.

30. 30. The method of claim 28, further comprising identifying a false positive fluid flow condition based on the estimated fluid flow rate.

31. 30. The method of claim 29, wherein identifying the false positive fluid flow condition comprises detecting a predetermined number of pulses in less than each of two or more consecutive measurement periods.

32. 30. The method of claim 29, wherein detecting the on state comprises detecting a predetermined number of pulses in each of two or more consecutive measurement periods.

33. 33. The method of claim 32, wherein the two or more consecutive measurement periods are separated by a predetermined delay period.

34. 30. The method of claim 29, wherein estimating the fluid flow rate is based at least in part on applying one or more of a low-pass filter and a high-pass filter to the measured optical properties.

35. The method of claim 1 , further comprising initiating the illuminating of the patient's body fluid and the measuring of the optical properties based on user input.

36. The method of claim 1 , further comprising detecting air bubbles in the fluid conduit based at least in part on the optical measurements.

37. The method of claim 1 , further comprising providing an indication of the predicted infection status to a user.

38. The method of claim 1 , further comprising predicting a particle concentration of the patient's bodily fluid based at least in part on the measured optical properties.

39. The method of claim 1 , further comprising predicting bleeding in the patient based at least in part on the measured optical properties.

40. The method of claim 1 , further comprising predicting an immune response of the patient based at least in part on the measured optical properties.

41. The method of claim 1 , further comprising predicting an infection onset for an ascites drainage patient based at least in part on the measured optical properties.

42. The method of claim 1 , further comprising predicting a fibrin content of the patient's bodily fluid based at least in part on the measured optical properties.

43. 1. A vessel for use in a fluid conduit, comprising: The entrance and The exit section, an optically transparent measurement section between the inlet section and the outlet section, the measurement section comprising at least two substantially planar surfaces, a rotational alignment feature, and a depth alignment feature; A container comprising:

44. 44. The container of claim 43, wherein the measuring portion includes an interior volume configured to receive a fluid, the interior volume including rounded corners.

45. 44. The container of claim 43, wherein the at least two substantially planar surfaces include a first plane generally perpendicular to a second plane.

46. 44. The container of claim 43, wherein the at least two substantially planar surfaces include a first planar surface opposed to a second planar surface.

47. 47. The container of claim 46, wherein the measuring portion comprises a substantially square cross-section.

48. 44. The container of claim 43, wherein at least a portion of the measuring portion is tapered.

49. 44. The container of claim 43, wherein the measuring portion comprises one or more of copolyester, acrylonitrile butadiene styrene, polycarbonate, acrylic, cyclic olefin copolymer, cyclic olefin polymer, polyester, polystyrene, Ultem, polyethylene glycol coated silicone, zwitterionic coated polyurethane, polyethylene oxide coated polyvinyl chloride, amphiphilic polysilicone.

50. 44. The container of claim 43, further comprising an opaque connector connectable to the inlet or the outlet.

51. 51. The container of claim 50, wherein at least one of the inlet and outlet is connectable to the fluid conduit.

52. 52. The container of claim 51, further comprising one or more of a vent cap, a clamp, and a connector coupled to the fluid conduit.

53. 52. The container of claim 51, coupled to a peritoneal dialysis drain set extension tube.

54. 52. The container of claim 51, coupled to a peritoneal dialysis cycler tubing cassette.

55. 52. The container of claim 51, coupled to an inlet of a peritoneal dialysis cycler tubing cassette.

56. 52. The container of claim 51, coupled to a peritoneal dialysis drain bag connector.

57. 52. The container of claim 51, wherein the container is coupled to a proximal end of a peritoneal dialysis drain bag connector.

58. 52. The container of claim 51, wherein the container is coupled to a drain bag of a urinary catheter or a Foley catheter.

59. 52. The container of claim 51, wherein the container is coupled to a central venous drain line.

60. 52. The container of claim 51, coupled to a hemodialysis blood circulation tubing set.

61. 52. The container of claim 51, coupled to an indwelling catheter.

62. 52. The container of claim 51, wherein the container is coupled to the proximal end of an indwelling catheter.

63. 1. A patient monitoring device, comprising: a housing, the housing comprising: a holder configured to releasably receive a portion of the fluid conduit; at least one illumination source configured to illuminate the received portion of the fluid conduit; at least one optical sensor configured to generate a signal; Equipped with the holder comprising one or more engagement features configured to orient the received portion of the fluid conduit at a predetermined rotational and vertical orientation relative to the at least one illumination source and the at least one optical sensor. Device.

64. 64. The device of claim 63, wherein the housing comprises a light seal.

65. 64. The device of claim 63, wherein the one or more engagement features are configured to orient the received portion of the fluid conduit by mating with alignment features of the received portion of the fluid conduit.

66. 64. The device of claim 63, wherein the one or more engagement features comprise an open slot.

67. 64. The apparatus of claim 63, wherein the at least one illumination source comprises a plurality of illumination sources.

68. 68. The apparatus of claim 67, wherein the illumination source is configured to illuminate in a first illumination direction and a second illumination direction orthogonal to the first illumination direction.

69. 68. The apparatus of claim 67, wherein at least two of the illumination sources are configured to illuminate along a first plane at a first wavelength.

70. 68. The apparatus of claim 67, wherein at least another two of the illumination sources are configured to illuminate along a second plane that is substantially parallel to the first plane.

71. 68. The apparatus of claim 67, wherein the illumination source is configured to illuminate in a first illumination direction and a second illumination direction opposite the first illumination direction.

72. 64. The apparatus of claim 63, wherein the illumination source is configured to illuminate in a first illumination direction and a second illumination direction that is offset by 180 degrees from the first illumination direction.

73. 64. The apparatus of claim 63, wherein the illumination source comprises a first illumination source configured to emit light at a first wavelength of about 800 nm to about 900 nm.

74. 64. The apparatus of claim 63, wherein the illumination source comprises a second illumination source configured to emit light at a second wavelength of about 400 nm to about 450 nm.

75. 64. The apparatus of claim 63, wherein the illumination source comprises a third illumination source configured to emit light at a third wavelength of about 500 nm to about 550 nm.

76. 64. The apparatus of claim 63, wherein the illumination source includes a fourth illumination source configured to emit light at a third wavelength of from about 230 nm to about 290 nm.

77. 64. The apparatus of claim 63, wherein the at least one optical sensor comprises a plurality of optical sensors.

78. 64. The apparatus of claim 63, wherein one or more of the at least one illumination source and the at least one optical sensor include an anti-reflective coating.

79. 64. The apparatus of claim 63, wherein the holder defines a longitudinal axis, and the at least one optical sensor comprises a plurality of optical sensors spaced apart parallel to the longitudinal axis.

80. 64. The apparatus of claim 63, further comprising a controller configured to generate patient data based at least in part on the signal.

81. 64. The apparatus of claim 63, wherein the patient data includes an infection status.

82. 64. The device of claim 63, further comprising a display.

83. 64. The device of claim 63, further comprising a base, the housing being offset and spaced apart from the base.

84. 64. The device of claim 63, wherein the housing comprises a peritoneal dialysis cycler.

85. 64. The device of claim 63, wherein the housing comprises a hemodialysis machine.

86. 64. The device of claim 63, wherein the housing is configured to couple to one or more of a patient platform and a medical cart.

87. 64. The device of claim 63, wherein the housing comprises a peritoneal dialysis device fluid path.

88. 64. The apparatus of claim 63, wherein the fluid conduit is coupled to a peritoneal dialysis tubing set.

89. 64. The apparatus of claim 63, wherein the fluid conduit is coupled to a peritoneal dialysis cycler tubing set.

90. 64. The apparatus of claim 63, wherein the fluid conduit is coupled to a peritoneal dialysis drain bag connector.

91. The fluid conduit is The entrance and The exit section, an optically transparent measurement section between the inlet section and the outlet section, the measurement section comprising at least two substantially planar surfaces, a rotational alignment feature, and a depth alignment feature; 64. The apparatus of claim 63, comprising:

92. 92. The apparatus of claim 91, wherein at least one of the rotational alignment feature and the depth alignment feature is configured to mate with the one or more engagement features of the holder.

93. 64. The apparatus of claim 63, further comprising a controller configured to generate patient data based at least in part on the signal.

94. 64. The apparatus of claim 63, wherein the controller is located remotely from the housing, the apparatus further comprising a communications device configured to transmit data representing the signal to the controller.

95. 95. The apparatus of claim 94, wherein the controller is configured to predict an infection score for the patient based at least in part on the signal.

96. 95. The device of claim 94, wherein the controller is configured to predict the patient's infection status in response to any one or more of the infection score exceeding a predetermined threshold in each of one or more consecutive measurement periods, the infection score increasing over time from a patient baseline value, and the infection score having an increasing rate of change over time.

97. 97. The apparatus of claim 96, wherein the infection status comprises a probability of infection.

98. 95. The apparatus of claim 94, wherein the fluid conduit is configured to receive a patient bodily fluid, the controller is configured to estimate a turbidity of the patient bodily fluid based at least in part on the signal, and the infection score is based at least in part on the estimated turbidity.

99. 95. The apparatus of claim 94, wherein the controller is configured to monitor trends in infection scores that predict infection resolution for the patient.

100. 95. The device of claim 94, wherein the controller is configured to monitor trends in the infection score to predict infection resolution for the patient by predicting infection resolution in response to any one or more of the infection score falling below a predetermined threshold in each of one or more consecutive measurement periods, the infection score declining from a patient baseline value over time, and the infection score having a declining rate of change over time.

101. 1. A method for remotely monitoring a patient, comprising: In one or more processors, receiving an optical property measurement of a patient fluid associated with the patient via a remote communication link; determining an infection score predictive of infection in the patient, the infection score based at least in part on the received optical property measurements; associating the patient as one of a plurality of patient infection states based at least in part on the determined infection score; A method comprising:

102. 102. The method of claim 101, further comprising notifying a user of the associated patient infection status.

103. 102. The method of claim 101, further comprising prompting a user to perform one or more predetermined patient treatment actions based on the associated patient infection status.

104. 104. The method of claim 103, wherein the one or more predetermined patient treatment actions include administering a broad-spectrum antimicrobial to the patient.

105. 104. The method of claim 103, wherein the one or more predetermined patient treatment actions comprise administering a pathogen-specific antimicrobial to the patient.

106. 104. The method of claim 103, wherein the one or more predetermined patient treatment actions include remotely monitoring an infection score trend that predicts resolution of the infection in the patient.

107. 104. The method of claim 103, wherein remotely monitoring the trend of the infection score predicting infection resolution comprises predicting infection resolution as a function of the infection score decreasing from a patient baseline value over time.

108. 108. The method of claim 107, wherein remotely monitoring the trend of the infection score to predict infection resolution comprises predicting infection resolution based on a rate of change of the infection score over time.

109. 108. The method of claim 107, wherein remotely monitoring the trend of the infection score that predicts infection resolution comprises predicting infection resolution in response to any one or more of the infection score falling below a predetermined threshold in each of one or more consecutive measurement periods, the infection score decreasing from a patient baseline value over time, and the infection score having a decreasing rate of change over time.

110. 102. The method of claim 101, wherein the plurality of patient infection states includes a first patient infection state corresponding to a healthy patient.

111. 102. The method of claim 101, wherein the plurality of patient infection states includes a second patient infection state corresponding to a patient presented to a healthcare provider.

112. 102. The method of claim 101, wherein the plurality of patient infection states includes a third patient infection state corresponding to a patient receiving broad-spectrum antibiotic therapy.

113. 102. The method of claim 101, wherein the plurality of patient infection states includes a third patient infection state corresponding to a patient who has received pathogen-specific antimicrobial therapy.

114. 102. The method of claim 101, wherein the plurality of patient infection states includes a fourth patient infection state corresponding to a hospitalized patient.

115. 102. The method of claim 101, wherein the plurality of patient infection states includes a fifth patient infection state corresponding to a patient transitioning to hemodialysis.

116. 102. The method of claim 101, wherein the predicted infection is peritonitis.

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