Peritoneal dialysis cycler

Abstract

A technique for monitoring intraperitoneal volume (IPV) during the stay of a peritoneal dialysis patient includes using a pressure sensor to monitor intraperitoneal pressure (IPP) during the stay, monitoring the density of the dialysis fluid during the stay, and determining changes in IPV based at least on changes in IPP and changes in the density of the dialysis fluid during the stay.

Description

Technology Field

[0001] Cross-reference regarding related applications

[0002] This application claims priority under 35 USC § 119(e) to Provisional Application No. 63 / 284,131, filed on November 30, 2021, with the title of the invention “PREDICTING ULTRAFILTRATION VOLUME IN PERITONEAL DIALYSIS PATIENTS,” the entirety of which is incorporated by reference for all purposes. Background Technology

[0003] Renal dysfunction or renal failure, and particularly end-stage renal disease, causes the body to lose the ability to remove water and minerals, excrete harmful metabolites, maintain acid-base balance, and control electrolyte and mineral concentrations within physiological ranges. Toxic uremic waste metabolites, including urea, creatinine, uric acid, and phosphorus, accumulate in body tissues, which can lead to death if the kidney's filtration function is not replaced.

[0004] Dialysis is a treatment used to support patients with insufficient renal function. The two main methods of dialysis are hemodialysis and peritoneal dialysis. During hemodialysis ("HD"), the patient's blood passes through the dialyzer of a dialysis machine, while the dialysis solution or dialysis fluid also passes through the dialyzer. During peritoneal dialysis ("PD"), dialysis fluid is periodically infused into the patient's peritoneal cavity. The lining of the membrane in the patient's peritoneum acts as a natural semipermeable membrane that allows diffusion and osmotic exchange to occur between the solution and the bloodstream. This exchange across the patient's peritoneum results in the removal of waste products containing solutes, such as urea and creatinine, from the blood, and regulates the levels of other substances in the blood, such as sodium and water. Automated PD machines, called PD cyclers, control the entire PD process and are designed to be performed at home, usually overnight, without the presence of clinical staff. This process is called continuous cycler-assisted PD ("CCPD"). Most PD cyclers are designed to automatically infuse, dwell, and drain dialysate into and from the patient's peritoneal cavity. Treatment often begins with an initial drainage cycle to empty the peritoneal cavity of used or consumed dialysate, typically lasting for several hours. Subsequently, the sequence proceeds through a sequence of filling, dwelling, and drainage phases. Each phase is referred to as a cycle. Peritoneal dialysis (PD) treatment is increasingly being used in patients with end-stage kidney disease (ESKD) because it can be performed at the patient's home and / or in other non-clinical settings.

[0005] In healthy subjects, normal renal function plays a role in maintaining fluid balance, which avoids both fluid overdose and dehydration. Prolonged periods of fluid overdose or dehydration can increase cardiovascular risk. To maintain optimal fluid status in PD patients, it is advantageous to have the ability to precisely control ultrafiltration to avoid or minimize fluid overdose or dehydration. In contrast to HD, PD lacks an ultrafiltration pump capable of mechanically extracting excess fluid from the patient's body tissues. Instead, glucose in the PD dialysis solution provides the osmotic pressure required to drive ultrafiltration. However, PD is less precise than HD in controlling the ultrafiltration rate (UFR) to adjust the ultrafiltration volume (UFV) and adequately remove excess water. These disadvantages of PD are attributed, at least in part, to (1) inefficient measurement tools and (2) a lack of sufficient understanding of the variability of individual characteristics of the peritoneal membrane. For example, the background technology of the present invention is described in U.S. Patent Application Publication US 2020 / 0353148 (November 12, 2020).

[0006] According to at least one aspect of the present invention, a method for monitoring intraperitoneal volume (IPV) during a period of stay is provided. The method for monitoring IPV during a period of stay comprises: a step of monitoring intraperitoneal pressure (IPP) during a period of stay using a pressure sensor; and a step of determining a change in IPV based at least on a change in IPP during a period of stay. The change in IPV is at least partially, It can be determined using an equation including, where g represents the acceleration due to gravity, h represents the vertical distance between the pressure sensor and the intraperitoneal fluid volume, and k is a coefficient. The change in IPV is at least partially, It can be determined using an equation including ], where g represents the acceleration due to gravity, ρ represents the density of the dialysis fluid solution, h represents the vertical distance between the pressure sensor and the intraperitoneal fluid volume, and the change in IPV is inversely related to the change in IPP.

[0007] Generally, in one embodiment, a peritoneal dialysis cycler comprises: a pressure sensor configured to measure intraperitoneal pressure (IPP); one or more hardware processors; and one or more non-transient computer-readable media storing instructions that cause one or more hardware processors to perform an operation when executed by the one or more hardware processors. The operation comprises: monitoring intraperitoneal volume (IPV) during the stay of a peritoneal dialysis patient by monitoring at least the IPP during the stay using the pressure sensor; and determining a change in IPV based at least on a change in IPP during the stay. The change in IPV is at least partially, It can be determined using an equation including, where g represents the acceleration due to gravity, h represents the vertical distance between the pressure sensor and the intraperitoneal fluid volume, and k is a coefficient. The change in IPV is at least partially, It can be determined using an equation including ], where g represents the acceleration due to gravity, ρ represents the density of the dialysis fluid solution, h represents the vertical distance between the pressure sensor and the intraperitoneal fluid volume, and the change in IPV is inversely related to the change in IPP.

[0008] Generally, in one embodiment, the system comprises: at least one device comprising one or more hardware processors; and one or more non-transient computer-readable media storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform an operation. The operation includes: monitoring the intraperitoneal volume (IPV) during the stay of a peritoneal dialysis patient by monitoring the intraperitoneal pressure (IPP) during the stay using a pressure sensor; and determining a change in IPV based at least on a change in IPP during the stay. The change in IPV is at least partially, It can be determined using an equation including, where g represents the acceleration due to gravity, h represents the vertical distance between the pressure sensor and the intraperitoneal fluid volume, and k is a coefficient. The change in IPV is at least partially, It can be determined using an equation including ], where g represents the acceleration due to gravity, ρ represents the density of the dialysis fluid solution, h represents the vertical distance between the pressure sensor and the intraperitoneal fluid volume, and the change in IPV is inversely related to the change in IPP.

[0009] Generally, in one embodiment, one or more non-transient computer-readable media store instructions that, when executed by one or more hardware processors, cause one or more hardware processors to perform an operation, the operation comprising: monitoring the intraperitoneal volume (IPV) of a peritoneal dialysis patient during the period of stay by monitoring at least the intraperitoneal pressure (IPP) during the period of stay using a pressure sensor; and determining a change in IPV based at least on a change in IPP during the period of stay. The change in IPV is at least partially, It can be determined using an equation including, where g represents the acceleration due to gravity, h represents the vertical distance between the pressure sensor and the intraperitoneal fluid volume, and k is a coefficient. The change in IPV is at least partially, It can be determined using an equation including ], where g represents the acceleration due to gravity, ρ represents the density of the dialysis fluid solution, h represents the vertical distance between the pressure sensor and the intraperitoneal fluid volume, and the change in IPV is inversely related to the change in IPP.

[0010] According to at least one aspect of the present disclosure, a method for monitoring the intraperitoneal volume (IPV) of a fluid during a residence phase of peritoneal dialysis treatment is provided. In some examples, the method comprises: monitoring the intraperitoneal pressure (IPP) of the fluid during a residence period using a pressure sensor; measuring the volume and weight of at least one sample of the fluid during a residence period; determining the density of the fluid during a residence period based on the volume and weight of at least one sample; and determining the IPV based at least on the change in IPP and the change in density during a residence period.

[0011] In various examples, IPV is determined at least partially based on an equation including the following, and

[0012] ,

[0013] Here, V0 is the volume of fluid at the start of the stay period, IPP0 is the intraperitoneal pressure at the start of the stay period, ρ0 is the known density of the fluid at the start of the stay period, and ρ is the density of the fluid during the stay period. In some examples, the step of determining the density of the fluid during the stay period includes the step of extracting at least one sample of fluid from the patient's peritoneal cavity, the step of determining the volume and mass of at least one sample, and the step of returning at least one sample to the peritoneal cavity. In many examples, the step of extracting at least one sample of fluid is performed automatically, and the stay period ends when the ultrafiltration volume (UFV) reaches the target UFV, and the UFV is calculated by subtracting the initial filling volume of the fluid from the IPV. In various examples, the density is determined periodically. In many examples, determining the density periodically involves determining the density every 30 minutes. In various examples, IPP is measured by measuring the pressure of the fluid in the peritoneal dialysis catheter. In some examples, the method further includes a step of compensating for IPP and density for fluid temperature fluctuations.

[0014] According to at least one aspect of the present disclosure, a peritoneal dialysis cycler is provided. The peritoneal dialysis cycler may include a pressure sensor configured to measure the intraperitoneal pressure (IPP) of a fluid; and a controller, wherein the controller is configured to: monitor the intraperitoneal volume (IPV) of the fluid during the patient's stay by monitoring at least the IPP during the stay using the pressure sensor; determine the density of the fluid during the stay based on the volume and weight of at least one sample of the fluid; and determine a change in IPV based at least on a change in the IPP and a change in the density of the fluid during the stay.

[0015] In some examples, the controller is programmed to determine the IPV using an equation including the following:

[0016] ,

[0017] Here, V0 is the volume of fluid at the start of the stay, IPP0 is the IPP at the start of the stay, ρ0 is the known density of the fluid at the start of the stay, and ρ is the density of the fluid during the stay. In various examples, determining the density of the fluid during the stay involves extracting at least one sample from the patient's peritoneal cavity, determining the volume and mass of at least one sample, and then returning at least one sample to the peritoneal cavity. In many examples, extracting at least one sample of fluid is performed automatically, and the stay ends when the ultrafiltration volume (UFV) reaches the target UFV, and the UFV is calculated by subtracting the initial filling volume of the fluid from the IPV. In some examples, the volume of at least one sample is calculated based on flow sensor measurements of the fluid extracted from the peritoneal cavity, and the mass of the fluid is determined using a scale that measures the weight of at least one sample. In many examples, the peritoneal dialysis cycler further includes a temperature sensor configured to measure the temperature of the fluid. In some examples, the controller compensates for pressure and density based on the fluid temperature. In many examples, the controller is configured to determine density periodically.

[0018] According to at least one aspect of the present disclosure, a non-transient computer-readable medium comprising instructions is provided, wherein the instructions instruct one or more processors to perform operations including: determining the intraperitoneal pressure (IPP) of a fluid during a period of residence using a pressure sensor; determining a change in IPV based at least on a change in the IPP of the fluid during a period of residence; determining the density of the fluid during a period of residence based on the volume and weight of at least one sample of the fluid; and determining the intraperitoneal volume (IPV) of the fluid based at least on a change in the IPP and a change in density during a period of residence.

[0019] In some examples, the instruction further instructs one or more processors to determine the IPV using an equation including the following, and

[0020] ,

[0021] Here, V0 is the volume of fluid at the beginning of the stay, IPP0 is the IPP at the beginning of the stay, ρ0 is the known density of the fluid at the beginning of the stay, and ρ is the density of the fluid during the stay. In various examples, the command further instructs one or more processors to: extract at least one sample of fluid from the patient's peritoneal cavity; determine the volume of at least one sample; determine the mass of at least one sample; and return at least one sample to the peritoneal cavity. In many examples, the command further instructs one or more processors to compensate for the density and IPP based on the temperature of the fluid.

[0022] At least one aspect of the present disclosure provides a method for monitoring the IPV of a fluid during a period of residence. In some examples, the method comprises the steps of determining the IPP of the fluid during a period of residence using a pressure sensor; determining a change in IPV based at least on a change in the IPP of the fluid during a period of residence; determining the density of the fluid during a period of residence based on the height of the fluid and the volume of the fluid within the peritoneal cavity; and determining the ultrafiltration volume (UFV) of the fluid during a period of residence based on the height. In some examples, the height is determined based on the density and / or volume. Brief explanation of the drawing

[0023] The foregoing and other purposes, features, and advantages of the devices, systems, and methods described herein will become apparent from the following description of specific embodiments thereof, as illustrated in the accompanying drawings. When the drawings are arranged to illustrate the principles of the devices, systems, and methods described herein, they are not necessarily to scale but are instead emphasized. In the drawings, the same reference numerals generally identify corresponding elements. FIG. 1 illustrates an example of a segmental bioimpedance analysis system for monitoring intraperitoneal volume according to an embodiment. FIG. 2 illustrates a schematic diagram of a bench experiment according to an embodiment. FIG. 3a illustrates a plot of pressure versus height during a bench experiment according to an example. FIG. 3b shows a plot of pressure versus height during a bench experiment according to an example. FIG. 4a illustrates a plot of the patient's intraperitoneal volume (IPV) versus time during stay according to an embodiment. FIG. 4b illustrates a plot of the patient's intraperitoneal pressure (IPP) versus time during stay according to an embodiment. FIG. 5a illustrates a plot of the change in IPP from the start of the stay to the end of the stay according to an embodiment. FIG. 5b illustrates a plot of UFV versus dialysis fluid density measured by a controller (e.g., Liberty Cycler) for 12 individual patients in 14 measurements according to an embodiment. FIG. 6a illustrates a plot of IPP and IPV versus time for 8 patients during their stay according to an example. FIG. 6b illustrates a plot of average IPP versus average IPV in 8 patients according to an example. FIG. 7a shows the IPP at the start of the stay according to the embodiment versus the UFV measured by the Liberty Cycler (UFV Liberty ) exemplifies the plot. FIG. 7b shows the UFV (UFV) measured by IPP versus segmental bioimpedance analysis at the start of stay according to the embodiment SBIA or UFV BIA ) exemplifies the plot. FIG. 8a illustrates a plot of UFV versus residence time according to an embodiment. FIG. 8b illustrates a schematic diagram of a PD system according to an embodiment. FIG. 8c illustrates a plot of the dialysis fluid density before and after retention according to an embodiment. FIG. 9 illustrates a block diagram of an example of a computer system according to an embodiment. FIG. 10 illustrates a schematic diagram of a Connected Health Service ("CHS") system according to an embodiment. FIG. 11 illustrates a schematic diagram of another bench experiment according to an embodiment. FIG. 12 illustrates a plot of the results of the bench experiment of FIG. 11 according to an embodiment. Specific details for implementing the invention

[0024] Traditionally, in clinical practice for PD treatment, the total ultrafiltration volume (UFV) is determined from the weight difference between the total fill volume and the drain volume at the end of PD treatment. However, the ultrafiltration volume varies over the dwell cycle. If the ultrafiltration volume can be monitored during the dwell cycle, more precise control of the ultrafiltration volume can be achieved. For example, the dwell cycle can be terminated early or extended to achieve a target ultrafiltration volume.

[0025] One or more embodiments disclosed herein include components and techniques for predicting the ultrafiltration volume (UFV) of a peritoneal dialysis patient. Specifically, techniques for predicting UFV by monitoring intraperitoneal volume (IPV), intraperitoneal pressure (IPP), and / or dialysis fluid density during a stay cycle are described herein. The UFV during a stay can be calculated by the difference between the IPV during the stay and the initial filling volume of the dialysis fluid.

[0026] IPP is positively correlated with IPV during the filling of dialysis fluid into the peritoneal cavity. However, the relationship between IPP and UFV during the stay cycle has been unclear due to a lack of information from previous studies and the difficulty of performing continuous monitoring of IPV and IPP during the stay. In a recent study discussed below, it was found that intraperitoneal volume (IPV) is associated with intraperitoneal pressure (IPP) during the peritoneal stay cycle. The advantage of using IPP to monitor IPV is that IPP measurements can be monitored automatically and non-invasively throughout the stay cycle without patient activity.

[0027] For the study, intraperitoneal volume (IPV) was monitored during the stay using segmental bioimpedance analysis (SBIA), which provides an understanding of UFV dynamics during the stay cycle of peritoneal dialysis (PD) treatment. SBIA obtained continuous IPV data while monitoring IPP with a sensor integrated into the PD cycler. For the study, a multi-bioimpedance device (e.g., Hydra 4200) was used. FIG. 1 illustrates a schematic diagram of how measurements of fluid within the peritoneal cavity were performed using 8-point electrodes placed on the patient's torso (100). Measurements of the torso (100) included a plurality of current electrodes (102), a plurality of measurement electrodes (104), and right resistance or impedance (R). PR )(106), left resistance or impedance (R PL It was performed using )(108). The patient's peritoneal membrane (110) and controller (112) are also shown in FIG. 1.

[0028] The controller (112) can be coupled to the current electrode (102) and the measurement electrode (104). The measurement electrode (104) is R PR (106) and / or R PL It can be coupled to (108). The measuring electrode (104) located on the right side of the body (100) is R PR A measuring electrode (104) located on the left side of the body (100) can be coupled to (106), and R PL It can be coupled to (108).

[0029] For example, a controller (112), which may be a Hydra 4200 or a similar device or may include such a device, may be configured to monitor electrodes (102, 104) and resistors (106, 108) and to receive information regarding current and resistance belonging to said electrodes (102, 104) and resistors (106, 108). The controller (112) may be configured to calculate resistances (106, 108) or fluid pressure and / or volume regarding the peritoneal cavity or the peritoneal membrane (110). As illustrated, the controller (112) is coupled to the torso (100) via a belt, but the controller (112) does not need to be coupled to the torso (100). In some examples, the controller (112) may be a separate device that can stand independently.

[0030] In this example, I1, I3 and I2, I4 are current electrodes (102), and S1, S3 and S2, S4 are measurement electrodes (104) and are placed on the right and left sides, respectively. R PR (106) and R PL (108) is the resistance at a current frequency of 5 kHz on the right and left sides of the abdominal region, respectively. The measuring electrode (104) can sample periodically, for example, every 2 seconds, during the dialysis fluid filling, retention, and drainage phases. The fluid volume within the peritoneal cavity was calculated using Equation 1:

[0031] Equation 1

[0032] Here, V0 is the volume of the initial dialysis fluid filling into the peritoneal cavity, and R E is the resistance at the start when the peritoneal cavity is empty, and R F is the resistance when the dialysis fluid filling is complete, and R PC is the resistance measured after the filling phase and during the stay. The resistance of the peritoneal cavity is R PR and / or R PLIt was measured by one or more resistors including. Using Equation 1, IPV was continuously measured and calculated during the residence cycle. Ultrafiltration volume was calculated by the difference between the maximum IPV during the residence cycle and the volume of the initial dialysate charge. Throughout the residence cycle, IPP was monitored by a sensor integrated into the PD cycler.

[0033] To verify IPP measurements from a sensor integrated into a Liberty Cycler with software version 2.9.1C, a bench study was also conducted. FIG. 2 illustrates a schematic setup for a bench study (200) conducted to test the relationship between pressure change and height level. The bench study (200) included a PD simulator (202), an adjustable table (204) having at least a first height (H1) and a second height (H2), and a controller (206) (for the study, a Liberty Cycler with software version 2.9.1C). The left side illustrates a first state (201a) where H1 is greater than H2, and the right side illustrates a second state (201b) where H2 is smaller than H1. Arrows (208) indicate changes from the first state (201a) at height (H1) of the PD simulator (202) and the second state (201b) at height (H2) of the PD simulator (202).

[0034] The PD simulator (202) is placed on an adjustable table (204). The adjustable table (204) can be moved between various heights including heights (H1, H2). A controller (206) is coupled to the PD simulator (202), monitors and / or controls the PD simulator (202), and collects IPP pressure measurements. The PD simulator (202) may be configured to simulate and / or emulate the peritoneal cavity, membranes, parietal peritoneum, visceral peritoneum, associated capillaries, veins, and / or arteries of the human body.

[0035] The principle of the relationship between the pressure of the fluid volume, for example, the pressure of the fluid volume in the PD simulator (202) and the position of the fluid at the vertical level can generally be explained as follows:

[0036] P = ρ g h Equation 2

[0037] Here, P is the pressure from the fluid volume in the vertical direction, and ρ is the density of the fluid, and g is gravitational acceleration ( g 9.8 m / s 2 ) and h is the height (i.e., the vertical distance between the sensor and the fluid volume). Therefore, P It must be linearly correlated with h as the height of the fluid volume changes in the vertical direction.

[0038] In some examples, g and h are constants during the residence phase of PD treatment. g When h is constant, changes in intraperitoneal pressure may be mainly associated with changes in dialysis fluid density (ρ). An increase in intraperitoneal IPV was found to be associated with a decrease in the density of intraperitoneal fluid volume in the PD simulator (202). Changes in dialysis fluid density and changes in IPV ( dIPV The relationship between ) can generally be expressed by the following equation:

[0039] dIPV = - k d ρ Equation 3

[0040] Here, k is a coefficient that may be related to the degree of hydration and the characteristics of the individual patient's peritoneal membrane, and d ρ is the change in density of the peritoneal dialysate during the stay. From Equations 2 and 3, individual IPV and pressure IPP The relationship between them can be explained as follows:

[0041] dIPP = g h d ρ Equation 4

[0042] The combination of Equation 3 and Equation 4 is as follows, with changes in pressure and IPV It applies to the relationship between:

[0043] Equation 5

[0044] Equation 6

[0045] Equation 6 illustrates that changes in peritoneal volume are inversely correlated with changes in intraperitoneal pressure during stay. Since UFV in PD treatment is defined as the change in IPV during stay, ΔUFV and ΔIPP The same relationship between them applies during the stay as shown in Equation 6.

[0046] Generally, in a closed space such as a fluid-free empty peritoneal cavity, like the empty peritoneal cavity of the PD simulator (202), the pressure is P 0 It is expressed as follows. When the density (ρ) of the dialysis solution is filled into the peritoneal cavity, the total pressure can be expressed as follows:

[0047] Equation 7

[0048] Here, P 0 represents the initial pressure before new dialysis fluid is filled into the peritoneal cavity. P 0 may depend on the degree of transcapillary hydrostatic pressure and the characteristics of the peritoneal membrane (e.g., peritoneal membrane (110)). In this case, since ρ is constant during the filling phase, P total is two factors, namely the initial pressure ( P 0It is determined by ) and the dialysate height (h). During the filling phase, more than 2 liters (L) of new dialysate solution is filled into the peritoneal cavity to increase the dialysate height. Therefore, P total It may increase with an increase in the height of the dialysis fluid within the peritoneal cavity. Depending on the height of the dialysis fluid P total The variability of is the initial pressure in the peritoneal cavity of individual patients ( P 0 It may be based on or related to the difference of ). Furthermore, after the filling phase and at the beginning of the retention phase, excess fluid may begin to move from the capillaries into the peritoneal cavity due to the high hydrostatic pressure gradient through the surface area of ​​the dialysate within the peritoneal cavity. Since some of the excess fluid may move into the peritoneal cavity by ultrafiltration (UF) during retention, the dialysate is diluted and its density decreases, so IPP is inversely correlated with UFV (Equation 6).

[0049] The goal of the bench study was to evaluate the relationship between pressure and dialysate height (Equation 2). For the bench study, the PD simulator (202) was filled with 2 L of 2.5% glucose dialysate. The height of the simulator was gradually increased in steps of 2.5 inches until it reached a normal point (36 inches). The normal height, in some examples, may correspond to the first state (201a). Afterward, the height was reduced back from the normal point to the baseline height over a period of 2 hours. The baseline height, in some examples, may correspond to the second state (201b). Pressure was automatically measured by the controller (206).

[0050] The bench study (200) included two phases of height change: phase (a) in which the height increases from a baseline to a normal point (e.g., from a second state (201b) to a first state (201a)); and phase (b) in which the height decreases from a normal point to a baseline (e.g., from a first state (201a) to a second state (201b)). FIGS. 3A and 3B illustrate the relationship between the change in height of the PD simulator (202) on the adjustable table (204) and the change in pressure measured by the controller (206) for each of the phases ((a) and (b)). As illustrated in FIGS. 3A and 3B, the pressure measured by the controller (206) had a high correlation with the height in both phases ((a) and (b)). Bench study (200) demonstrates that changes in pressure of a PD catheter can be precisely measured by a pressure sensor, for example, a pressure sensor coupled to a controller (206).

[0051] A clinical pilot study was conducted with 14 measurements in 12 PD patients (age 59.4±14.3 years, 4 females, pre-existing weight 83±28 kg, BMI 28.6±7.8 kg / m2, PD years 13.3±7 months) studied during a 2-hour stay (2 L dialysate, 2.5% dextrose) by verifying IPP measurements using a sensor integrated into a Liberty cycler with software version 2.9.1C. IPP was measured every 15 seconds using a pressure sensor integrated into the controller (206) (Liberty cycler with software version 2.9.1C). Three techniques were used to quantify UFV: (1) drainage fluid (UFV Drain Weight measurement of ); (2) by Liberty Cycler (UFV Liberty (3) by SBIA(UFVSBIA, ml). The average UFV of all patients is UFV SBIA , UFV Liberty and UFV DrainThese were 199.1±193.2 ml, 218.8±136.4 ml, and 266.9±136.4 g, respectively. UFV in the entire group Liberty (218.6±156.6 ml) and UFV SBIA (198.1±215.6 ml) is UFV Drain It was lower than (265.6±150.3 g). By comparing IPV and IPP every 10 minutes, the correlation between IPV and IPP was found to be UFV > 200 ml in 8 patients.

[0052] FIGS. 4a through 8c illustrate results from a bench study (200) and a clinical pilot study. As shown in FIG. 4a, IPV increased by 0.499 L (UFV) during the stay. As shown in FIG. 4b, IPP decreased from 24.1 millibars to 18.6 millibars during the same time period. FIG. 5a illustrates how IPP decreases from the start of the patient's stay to the end of the stay from a clinical study. FIG. 5b illustrates how changes in dialysate density correlate with the patient's UFV from a clinical pilot study.

[0053] Figure 6a illustrates the average IPV and IPP of eight patients during their stay, showing an increase in IPV (circles) and a decrease in IPP (squares). Figure 6b illustrates the relationship between IPV and IPP during the stay of eight patients. In this example, each circle represents the relationship between the change in IPP and IPV at different stay times for the same patient. Dotted lines connect two consecutive points in chronological order. As shown in Figure 6b, IPP tends to decrease over time as IPV increases, and the change over time tends to be linear.

[0054] Figures 7a and 7b show the start of the stay (IPP Start IPP in ) is UFV Liberty and UFV SBIA (UFV in Fig. 7a BIAIt exemplifies association with (as shown). These results indicate that the IPP value at the start of the stay can be used to predict UFV. In a study designed to provide the same length of stay to all patients, IPP Start The correlation between and UFV is IPP Start It is approximately identical to the correlation between and ultrafiltration rate (UFR). Assuming that PD UFR may be related to fluid transport across the peritoneal membrane, IPP Start can be a valuable parameter for understanding the characteristics of the peritoneal membrane of individual patients (Equation 7). Fig. 7a shows the IPP (IPP) measured at the start of the stay. Start The relationship between ) and the Liberty cycler UFV is illustrated. Since the treatment time is the same for all patients, different UFVs correspond to individual UFRs that can reflect the individual membrane characteristics of each patient's individual membrane.

[0055] When IPV increases, the density of the dialysate decreases according to the amount of water moved through the membrane, which dilutes the dialysate in the peritoneal cavity. According to Equation 2 above,

[0056] Equation 2 (repeated)

[0057] Here, P is the pressure of a specific fluid, ρ is the fluid density, g g is the acceleration due to gravity, and h is the height of the fluid. If g and h are constant, pressure can decrease as density decreases. The bench study (200) described above confirms this relationship. However, if the height (h) is not constant, pressure must be calculated using at least two variables (e.g., h and ρ). The following discussion demonstrates a technique for determining pressure using at least two variables and describes the results of a bench study confirming the relationship between pressure, height, and volume.

[0058] From the above equation 1, a differential equation can be obtained:

[0059] Equation 8

[0060] Here, represents the pressure change as a function of time, and and ε₀ represents the change in density and the change in height of the dialysate solution, respectively. This example assumes that the change in dialysate density (the difference between post-diasate and pre-diasate densities: Δρ = post-diasate(ρ) - pre-diasate(ρ)) is ≤ 0, because post-diasate density typically decreases as the ultrafiltration volume (UFV) increases. When UFV is equal to 0, post-diasate(ρ) is equal to pre-diasate(ρ). Therefore, Equation 8 can be rewritten as follows:

[0061] ] Equation 9

[0062] Here, ΔP, Δ h , and Δρ represent the change in pressure, the change in height, and the change in density, respectively. From Equation 9, it can be concluded that the change in pressure (increase and / or decrease) is related to the height of the solution when the density is constant (Δρ=0), and that the change in pressure depends on the change in density (Δρ) when the height is constant. Since Δρ is inversely correlated with UFV, the change in pressure is negatively correlated with UFV. Also Then, it also leads to the conclusion that the pressure will remain constant.

[0063] FIG. 11 illustrates another bench study (300) conducted. The bench study (300) demonstrated that a change in IPP depends on a change in IPV. The bench study (300) includes a PD simulator (302), an adjustable table (304), and a controller (306). The controller (306) included a Liberty Cycler with software version 2.9.3. For any two states (301a, 301b), the height of the adjustable table (304) was kept unchanged throughout the experiment so that the height of each state (H1, H2) was the same. An arrow (308) indicates a change from the first state (301a) to the second state (301b).

[0064] The controller (306) measured IPP using sensors (e.g., pressure sensors and / or electrodes such as electrodes (102, 104)). The PD simulator (302) was used to fill a known dialysis solution (2,000 mL). The experiment included three phases: (1) a filling phase—2 L of dialysis solution was filled into the simulator within 10 minutes—; (2) a retention phase for 25 minutes; and (3) a drainage phase for about 10 minutes.

[0065] FIG. 12 is a plot of the results of the bench study (300). FIG. 12 illustrates the change in pressure during the filling and discharge of the PD simulator (302) during the bench study (300). FIG. 12 shows that the increase and decrease in IPP are due to the volume filled (filled) and removed (discharged) into or from the PD simulator (302). It will be understood that there is no change in the volume or height of the PD simulator (302) during the stay, and the pressure of the fluid within the PD simulator (302) must otherwise remain constant. Thus, the bench study (300) provides evidence that the relationship between IPV and IPP can be expressed using a piecewise function that depends on at least two independent variables: the density of the solution and the height.

[0066] The above discussion explains the relationship between IPV and IPP during the duration of stay. The above discussion illustrates that ultrafiltration volume can be monitored by IPP measurement during peritoneal dialysis treatment. Since IPP measurement can be performed automatically by an integrated sensor of the PD machine (such as a controller (112, 206, 306), or a device like the Liberty Cycler or a similar device), there is little to no additional cost or time compared to the method using bioimpedance. Furthermore, IPP Start The correlation between and UFV implies that IPP measured at the start of the stay may be associated with the characteristics of the peritoneal membrane. These findings may enable obtaining objective and quantitative information regarding the transport characteristics of the peritoneal membrane. Furthermore, the discovery of a relationship between changes in dialysate density and UFV during the stay provides an additional opportunity to understand the dynamics of chemicals moving across the membrane. Additionally, it will be understood that many electrodes of the SBIA method are not required for the pressure sensor method, and therefore, this method can be administered more easily at home compared to conventional methods.

[0067] It will be understood from the foregoing that IPV can be predicted based on IPP during the charge, stay, and discharge phases. IPV can be predicted based on IPP because, in some cases, IPV is linearly related to IPP. As a result, dialysis and dialysis-related treatments can predict IPV over time through the charge, stay, and discharge phases using IPP, and adjust treatment based on the obtained prediction and pressure values. Predicting IPV based on IPP eliminates the need to use electrodes or other methods, such as those used in SBIA.

[0068] Although IPP can be measured semi-continuously and non-invasively by pressure sensors, such as pressure sensors placed within a PD cycler or on a PD catheter, the accuracy of using IPP to calculate IPV and predict UFV can be affected by changes in dialysate density that cause changes in IPV. According to Equation 2 above:

[0069] Equation 2 (repeated)

[0070] Here, ρ is the density of the dialysate, g is the acceleration due to gravity, and h is the height of the PD dialysate within the peritoneal cavity at the measurement point. Since the acceleration due to gravity (g) is universally constant, changes in h and ρ are the factors driving changes in IPP. In the clinical studies discussed above, the decrease in density (ρ) was demonstrated to be due to the movement of water into the peritoneal cavity and the absorption of glucose from the peritoneal cavity into the patient. Knowledge of the density (ρ) and IPP during the stay enables the calculation of h (a metric related to IPV) by solving Equation 2 for h:

[0071] Equation 10

[0072] Since the volume (V) can be calculated by multiplying the cross-sectional area (A) by the height (h), Equation 2 can be expressed as follows:

[0073] Equation 11

[0074] Here, V represents the intraperitoneal volume (IPV), and A represents the cross-sectional area of ​​the dialysis fluid in the peritoneal cavity. Assuming A is a constant value, A0, Equation 11 can be rewritten as follows:

[0075] Equation 12

[0076] Here, A0 can be calculated based on the initial infusion volume (V0) and density (ρ0) of the new dialysis fluid and the initial pressure (IPP0) when the dialysis fluid is filled:

[0077] Equation 13

[0078] Equation 12 can be expressed as follows:

[0079] Equation 14

[0080] Here, V0 is the volume of new dialysate initially filled into the peritoneal cavity, IPP0 can be measured at the end of the filling procedure, for example, by a Liberty PD Cycler, and ρ0 is the known density of the new dialysate. According to Equation 14, if the IPP and the density of the dialysate are known, IPV can be calculated at any time during the stay. As discussed herein, IPP can be measured continuously by a Liberty cycler. Therefore, if the density of the dialysate can be measured during the stay, IPV can be calculated more accurately according to Equation 14 during the stay in PD patients by taking into account the change in the density of the dialysate during the stay.

[0081] According to another embodiment, the method of PD treatment may include the step of monitoring IPP and dialysis fluid density (periodically) during the stay of PD treatment. For example, a PD cycler or PD treatment system may be configured to periodically pump out a sample of dialysis fluid from the peritoneal cavity for density measurement during the stay cycle, and then return the dialysis fluid sample to the peritoneal cavity. For example, a PD cycler may be programmed to remove and return a dialysis fluid sample for density measurement every 30 minutes during the stay. FIG. 8a is a chart of UF volume versus time during the stay, and exemplary points where periodic sampling of dialysis fluid and density measurement can be performed automatically by a PD cycler or PD system are identified in FIG. 8a. Figure 8a shows that the UFV initially increases at a significantly rapid rate—for example, from 0 mL to approximately 450 mL over 120 minutes—and then, the UFV decreases at a slower and steady rate—for example, from 450 mL to approximately 350 mL over 150 minutes.

[0082] FIG. 8b illustrates a schematic diagram of a PD system (800) according to another embodiment. The PD system (800) can perform PD treatment, and the PD system (800) can automatically periodically sample the dialysis fluid and measure its density during the residence phase. The PD system (800) includes a PD cycler (810) fluidically connected to a PD patient catheter (812) and a series of valves (814, 816, 818). The valves (814, 816, 816) are configured to control the flow of dialysis fluid into and out of the catheter (812), as well as to control the opening and / or closing of a new dialysis fluid bag (820) and the opening and / or closing of a discharge bag (822). The PD cycler (810) may include a pressure sensor (not shown) configured to measure the pressure of the fluid within the catheter (812). The PD system (800) further includes a flow sensor (824) configured and positioned to measure the flow and volume of dialysis fluid flowing into or out of the patient's peritoneal cavity. In some embodiments, the PD system (800) includes a temperature sensor (826) configured to measure the ambient temperature as well as the dialysis fluid temperature. In some examples, the PD cycler (810) controls the direction and timing of the dialysis fluid flow into or out of the peritoneal cavity. The PD system (800) uses a new dialysis fluid bag (820) to temporarily receive a dialysis fluid sample during the stay cycle. The PD system (800) may further include a dialysis fluid density measuring mechanism. For example, as illustrated in FIG. 8b, the PD system (800) may include a scale (828) configured to measure the weight of the dialysis fluid sample when it is temporarily stored in the new dialysis fluid bag (820). In some embodiments, one or more of the components of the PD system (800) may be integrated into the PD cycler (810).For example, in some embodiments, valves (814, 816, 818), a flow sensor (824), a temperature sensor (826), and / or a scale (820) are integrated into the PD cycler (810).

[0083] The PD system (800) can periodically measure the density of the dialysis fluid by pumping a small sample of dialysis fluid into a new dialysis fluid bag (820) through a flow sensor (824) from the patient's peritoneal cavity. The flow measurement from the flow sensor (824) can be used to calculate the total volume of the dialysis fluid sample, and the output from the scale (828) can be used to calculate the mass of the dialysis fluid sample. Then, the density (ρ) of the dialysis fluid sample can be calculated by dividing the mass of the dialysis fluid sample by the volume of the dialysis fluid sample. The sampling frequency and the measurement of the dialysis fluid density are adjustable parameters. For example, taking the dialysis fluid sample to determine the density of the dialysis fluid sample can be performed continuously or at intervals such as every 10 minutes, 15 minutes, 20 minutes, 25 minutes, 30 minutes, or longer. In some embodiments, the PD system (800) is programmed to compensate for the density and / or pressure measurements for temperature fluctuations. Temperature fluctuations can be monitored by a temperature sensor (826). In some embodiments, the PD system (800) is programmed to calculate the IPV according to Equation 13 after each dialysis fluid sampling density calculation and to monitor the IPV throughout the entire residence cycle. Once the target ultrafiltration volume is achieved, the residence cycle is terminated.

[0084] Figure 8c is a chart showing the change in dialysate density at the start and end of the stay for 13 patients. Density decreased from 1.018 (g / ml) to an average of 0.9256±0.0106 (g / ml) with the new 2.5% glucose dialysate (p<0.0001).

[0085] In some examples, the systems and methods described herein provide for monitoring changes in IPV and / or IPP based on changes in the density of the dialysate. In some examples, the systems and methods described herein provide for predicting the ultrafiltration rate (UFR) or ultrafiltration volume (UFV) based on the IPP and / or density of the dialysate. The systems and methods described herein can be used to provide more effective PD treatment based on the calculation of IPV, IPP, UFR, and / or UFV without requiring additional equipment that would be impractical for PD patients at home.

[0086] In an embodiment, the system comprises one or more devices including one or more hardware processors configured to perform any of the operations described herein and / or mentioned in any of the claims.

[0087] In an embodiment, one or more non-transient computer-readable storage media store instructions that, when executed by one or more hardware processors, cause any of the operations described herein and / or mentioned in any of the claims to be performed.

[0088] Any combination of the features and functions described herein may be used according to the embodiments. In the foregoing specification, embodiments have been described with reference to numerous specific details that may vary from implementation to implementation. Accordingly, the specification and drawings should be regarded as illustrative rather than restrictive. The sole and exclusive indicator of the scope of the invention and what the applicant intends to define as the scope of the invention is the literal equivalent of the set of claims issued in this application, in the specific form in which these claims are issued, including any subsequent modifications.

[0089] In the embodiments, the technology described herein is implemented by one or more special-purpose computing devices (i.e., computing devices specifically configured to perform specific functions). The special-purpose computing device(s) may include digital electronic devices such as one or more application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and / or network processing units (NPUs) that can be hard-wired to perform the technology and / or continuously programmed to perform the technology. Alternatively or additionally, the computing device may include one or more general-purpose hardware processors programmed to perform the technology according to program instructions in firmware, memory, and / or other storage. Alternatively or additionally, the special-purpose computing device may combine custom hard-wired logic, ASICs, FPGAs, or NPUs with custom programming to achieve the technology. Special-purpose computing devices may include desktop computer systems, portable computer systems, handheld devices, networking devices, and / or any other device(s) that include hard-wired and / or program logic to implement the technology.

[0090] For example, FIG. 9 is a block diagram of an example of a computer system (900) according to an embodiment. The computer system (900) includes a bus (902) or other communication mechanism for communicating information, and a hardware processor (904) coupled to the bus (902) for processing information. The hardware processor (904) may be a general-purpose microprocessor.

[0091] The computer system (900) also includes main memory (906), such as random access memory (RAM) or other dynamic storage device, coupled to a bus (902) to store information and instructions to be executed by the processor (904). The main memory (906) may also be used to store temporary variables or other intermediate information during the execution of instructions to be executed by the processor (904). When such instructions are stored in one or more non-temporary storage media accessible to the processor (904), they render the computer system (900) as a special-purpose machine customized to perform actions specified in the instructions.

[0092] The computer system (900) further includes a read-only memory (ROM) (908) or other static storage device coupled to a bus (902) to store static information and instructions for a processor (904). A storage device (910), such as a magnetic disk or an optical disk, is provided to store information and instructions and is coupled to the bus (902).

[0093] The computer system (900) may be coupled via a bus (902) to a display (912), such as a liquid crystal display (LCD), a plasma display, an electronic ink display, a cathode ray tube (CRT) monitor, or any other type of device for displaying information to a computer user. An input device (914), including alphanumeric keys and other keys, may be coupled to the bus (902) to communicate information and command selections to the processor (904). Alternatively or additionally, the computer system (900) may receive user input via a cursor control unit (916), such as a mouse, trackball, trackpad, or cursor direction key, to communicate direction information and command selections to the processor (904) and to control cursor movement on the display (912). This input device typically has two degrees of freedom on two axes, namely a first axis (e.g., x) and a second axis (e.g., y), which allow the device to specify a position in a plane. Alternatively or additionally, the computer system (9) may include a touchscreen. The display (912) may be configured to receive user input through one or more pressure-sensing sensors, multi-touch sensors, and / or gesture sensors. Alternatively or additionally, the computer system (900) may receive user input through a microphone, a video camera, and / or some other type of user input device (not shown).

[0094] A computer system (900) may implement the technology described herein by using customized hard-wired logic, one or more ASICs or FPGAs, firmware, and / or program logic that, in combination with other components of the computer system (900), make the computer system (900) a special-purpose machine or program it to be a special-purpose machine. According to one embodiment, the technology of the present invention is performed by the computer system (900) in response to a processor (904) that executes one or more sequences of one or more instructions contained in a main memory (906). These instructions may be read into the main memory (906) from another storage medium, such as a storage device (910). The execution of the sequence of instructions contained in the main memory (906) causes the processor (904) to perform the process steps described herein. Alternatively or additionally, hard-wired circuits may be used instead of or in combination with software instructions.

[0095] As used herein, the term “storage medium” refers to one or more non-transient media that store data and / or instructions that cause a machine to operate in a particular way. Such storage media may include non-volatile media and / or volatile media. Non-volatile media include, for example, optical disks or magnetic disks such as storage device (910). Volatile media include dynamic memory such as main memory (906). Common forms of storage media include, for example, floppy disks, flexible disks, hard disks, solid-state drives, magnetic tapes or other magnetic data storage media, CD-ROMs or any other optical data storage media, any physical media having a pattern of holes, RAM, programmable read-only memory (PROM), erasable PROM (EPROM), flash-EPROM, non-volatile random access memory (NVRAM), any other memory chip or cartridge, content-addressable memory (CAM), and ternary content-addressable memory (TCAM).

[0096] A storage medium is distinct from a transmission medium, but can be used together with it. A transmission medium participates in the transfer of information between storage media. Examples of transmission media include coaxial cables, copper wires, and optical fibers, which include wires containing a bus (902). Transmission media may also take the form of acoustic or light waves, such as those generated during radio-wave and infrared data communication.

[0097] Various forms of media may be involved in carrying one or more sequences of one or more instructions to the processor (904) for execution. For example, the instructions may initially be carried on a magnetic disk or solid-state drive of a remote computer. The remote computer may load the instructions into dynamic memory and transmit the instructions over a network via a network interface controller (NIC), such as an Ethernet controller or a Wi-Fi controller. A NIC local to the computer system (900) may receive data from the network and place the data on a bus (902). The bus (902) carries the data to main memory (906), from which the processor (904) retrieves and executes instructions. Instructions received by the main memory (906) may be optionally stored in a storage device (910) before or after execution by the processor (904).

[0098] The computer system (900) also includes a communication interface (918) coupled to a bus (902). The communication interface (918) provides bidirectional data communication coupling to a network link (920) connected to a local network (922). For example, the communication interface (918) may be an integrated services digital network (ISDN) card, a cable modem, a satellite modem, or a modem for providing a data communication connection to a corresponding type of telephone line. As another example, the communication interface (918) may be a local area network (LAN) card for providing a data communication connection to a compatible local area network (LAN). A wireless link may also be implemented. In any such implementation, the communication interface (918) transmits and receives electrical signals, electromagnetic signals, or optical signals carrying a digital data stream representing various types of information.

[0099] A network link (920) typically provides data communication to other data devices through one or more networks. For example, a network link (920) may provide a connection to a host computer (924) or to data equipment operated by an Internet service provider (ISP) (926) through a local network (922). The ISP (926) provides data communication services through a worldwide packet data communication network, which is currently commonly referred to as the "Internet" (928). Both the local network (922) and the Internet (928) use electrical signals, electromagnetic signals, or optical signals that carry digital data streams. Signals through various networks and signals on the network link (920) and through the communication interface (918) that carry digital data to / from the computer system (900) are exemplary forms of transmission media.

[0100] A computer system (900) can transmit messages and receive data containing program code through network(s), network links (920), and communication interfaces (918). In the example of the Internet, a server (930) can transmit requested code for an application program through the Internet (928), an ISP (926), a local network (922), and communication interfaces (918).

[0101] The received code may be executed by the processor (904) when received, and / or stored in a storage device (910) or other non-volatile storage for future execution.

[0102] In an embodiment, a computer network provides connectivity between a set of nodes running software that utilizes the technology described herein. The nodes may be local to each other and / or remote from each other. The nodes are connected by a set of links. Examples of links include coaxial cables, unshielded twisted cables, copper cables, optical fibers, and virtual links.

[0103] A subset of nodes implements a computer network. Examples of these nodes include switches, routers, firewalls, and network address translators (NATs). Another subset of nodes uses a computer network. These nodes (also referred to as "hosts") can run client processes and / or server processes. Client processes make requests for computing services (e.g., requests to run a specific application and / or retrieve a specific data set). Server processes respond by executing the requested service and / or returning the corresponding data.

[0104] A computer network may be a physical network comprising physical nodes connected by physical links. A physical node is any digital device. A physical node may be a function-specific hardware device. Examples of function-specific hardware devices include hardware switches, hardware routers, hardware firewalls, and hardware NAT. Alternatively or additionally, a physical node may be any physical resource that provides computing power to perform tasks, such as one configured to run various virtual machines and / or applications that perform their respective functions. A physical link is a physical medium that connects two or more physical nodes. Examples of links include coaxial cables, unshielded twisted cables, copper cables, and optical fibers.

[0105] A computer network can be an overlay network. An overlay network is a logical network implemented on top of another network (e.g., a physical network). Each node of an overlay network corresponds to an individual node of the underlying network. Therefore, each node of an overlay network is associated with both an overlay address (for addressing the overlay node) and an underlay address (for addressing the underlay node implementing the overlay node). Overlay nodes can be digital devices and / or software processes (e.g., virtual machines, application instances, or threads). Links connecting overlay nodes can be implemented as tunnels through the underlying network. An overlay node at any end of the tunnel can treat the underlying multi-hop path between them as a single logical link. Tunneling is performed through encapsulation and decapsulation.

[0106] In one embodiment, the client may be local to the computer network and / or remote from the computer network. The client may access the computer network through a private network or another computer network such as the Internet. The client may communicate requests to the computer network using a communication protocol such as the Hypertext Transfer Protocol (HTTP). Requests are communicated through an interface such as a client interface (such as a web browser), a program interface, or an application programming interface (API).

[0107] In an embodiment, a computer network provides connectivity between clients and network resources. Network resources include hardware and / or software configured to run server processes. Examples of network resources include processors, data stores, virtual machines, containers, and / or software applications. Network resources may be shared among multiple clients. Clients request computing services from the computer network independently of one another. Network resources are dynamically allocated to requests and / or clients based on demand. Network resources allocated to each request and / or client may be scaled up or scaled down based, for example, (a) computing services requested by a specific client, (b) aggregated computing services requested by a specific tenant, and / or (c) requested aggregated computing services of the computer network. Such a computer network may be referred to as a “cloud network.”

[0108] In an embodiment, a service provider provides a cloud network to one or more end users. Various service models, including Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS), may be implemented by the cloud network. In SaaS, the service provider provides the end user with the ability to use the service provider's applications running on network resources. In PaaS, the service provider provides the end user with the ability to deploy custom applications on network resources. Custom applications may be created using programming languages, libraries, services, and tools supported by the service provider. In IaaS, the service provider provides the end user with the ability to supply processing, storage, network, and other underlying computing resources provided by network resources. Any application, including an operating system, may be deployed on network resources.

[0109] In the embodiments, various deployment models may be implemented by computer networks including, but not limited to, private clouds, public clouds, and hybrid clouds. In a private cloud, network resources are provided for exclusive use by a specific group of one or more entities (as used herein, the term “entity” refers to a legal entity, organization, individual, or other entity). Network resources may be local to the premises of the specific group of entities and / or remote from the premises of the specific group of entities. In a public cloud, cloud resources are provided for multiple entities independent of one another (referred to as “tenants” or “customers”). In a hybrid cloud, the computer network includes private clouds and public clouds. An interface between the private cloud and the public cloud allows for the portability of data and applications. Data stored in the private cloud and data stored in the public cloud may be exchanged through the interface. Applications implemented in the private cloud and applications implemented in the public cloud may have dependencies on each other. Calls from an application in a private cloud to an application in a public cloud (and vice versa) can be executed through an interface.

[0110] In the embodiments, the system supports multiple tenants. A tenant is a legal entity, organization, enterprise, business unit, employee, or other entity that accesses shared computing resources (e.g., computing resources shared in a public cloud). One tenant may be isolated from other tenants (through behavior, tenant-specific practices, identification to employees and / or the outside world). Computer networks and their network resources are accessed by clients corresponding to different tenants. Such computer networks may be referred to as "multi-tenant computer networks." Several tenants may use the same specific network resources at different times and / or simultaneously. Network resources may be local to a tenant's zone and / or remote from a tenant's zone. Different tenants may require different network requirements for the computer network. Examples of network requirements include processing speed, amount of data storage, security requirements, performance requirements, throughput requirements, potential requirements, resilience requirements, Quality of Service (QoS) requirements, tenant isolation, and / or consistency. The same computer network may need to implement different network requirements demanded by different tenants.

[0111] In the embodiments, in a multi-tenant computer network, tenant isolation is implemented to ensure that applications and / or data of different tenants are not shared with each other. Various tenant isolation approaches may be used. In the embodiments, each tenant is associated with a tenant ID. Applications implemented by the computer network are tagged with a tenant ID. Additionally, or alternatively, data structures and / or datasets stored by the computer network are tagged with a tenant ID. A tenant is allowed access to a specific application, data structure, and / or dataset only if the tenant and the specific application, data structure, and / or dataset are associated with the same tenant ID. As an example, each database implemented by the multi-tenant computer network may be tagged with a tenant ID. Only the tenant associated with the corresponding tenant ID may access the data in a specific database. As another example, each entry in a database implemented by the multi-tenant computer network may be tagged with a tenant ID. Only the tenant associated with the corresponding tenant ID can access the data of a specific entry. However, the database can be shared by multiple tenants. A subscription list can indicate which tenants have permission to access which applications. For each application, a list of tenant IDs of tenants permitted to access the application is stored. A tenant is allowed access to a specific application only if their tenant ID is included in the subscription list corresponding to that specific application.

[0112] In an embodiment, network resources corresponding to different tenants (e.g., digital devices, virtual machines, application instances, and threads) are isolated from a tenant-specific overlay network maintained by a multi-tenant computer network. For example, a packet from any source device in a tenant overlay network can only be transmitted to another device within the same tenant overlay network. An encapsulation tunnel may be used to prevent any transmission from a source device on a tenant overlay network to a device in a different tenant overlay network. Specifically, a packet received from a source device is encapsulated within an outer packet. The outer packet is transmitted from a first encapsulation tunnel endpoint (communicating with the source device in the tenant overlay network) to a second encapsulation tunnel endpoint (communicating with the destination device in the tenant overlay network). The second encapsulation tunnel endpoint decapsulates the outer packet to obtain the original packet transmitted by the source device. The original packet is transmitted from the second encapsulation tunnel endpoint to the destination device in the same specific overlay network.

[0113] FIG. 10 is a block diagram of an example of a Connected Health (CH) system (1000) according to an embodiment. In the embodiment, the CH system (1000) may include more or fewer components than those illustrated in FIG. 10. The components illustrated in FIG. 10 may be local or remote from one another. The components illustrated in FIG. 10 may be implemented in software and / or hardware. Each component may be distributed across multiple applications and / or machines. Multiple components may be combined into a single application and / or machine. An operation described for one component may instead be performed by another component.

[0114] The CH system (1000) may be part of a system such as the system (100) or configured to communicate with the system (100). The CH system (1000) may include, among other things, a processing system (1005), a CH cloud service (1010), and a gateway (CH gateway) (1020) that may be used in connection with network aspects of one or more systems described herein. The processing system (1005) may include a server and / or cloud-based system that processes, compatibility-checks, and / or formats medical information, including prescription information generated from a clinical information system (CIS) (1004) of a clinic or hospital, in connection with the data transmission operation of the CH system (1000). The CH system (1000) may include appropriate encryption and data security mechanisms. The CH cloud service (1010) may include a cloud-based application that serves as a communication pipeline (e.g., facilitating the transmission of data) between components of the CH system (1000) through a connection to a network such as the Internet. The gateway (1020) may serve as a communication device that facilitates communication between components of the CH system (1000). In various embodiments, the gateway (1020) may communicate with the dialysis machine (1002) (e.g., a peritoneal dialysis machine or a hemodialysis machine) and the system (100) via a wireless connection (1001), such as Bluetooth, Wi-Fi, and / or other suitable types of local or short-range wireless connections. The gateway (1020) may also be connected to the CH cloud service (1010) via a secure network connection (e.g., the Internet). The gateway (1020) may be configured to transmit / receive data to / from the CH cloud service (1010) and to transmit / receive data to / from the dialysis machine (10010) and the system (100).The dialysis machine (1002) can poll the CH cloud service (1010) for available files (e.g., via the gateway (1020)), and the dialysis machine (1002) and / or the system (100) can temporarily store the available files for processing.

[0115] It will be understood from the foregoing that specific hardware, such as the Liberty Cycler and Hydra 4200, is referenced. It will be understood that the foregoing does not require the Liberty Cycler or Hydra 4200, and that these devices are merely examples of devices that can be used in the capacities described herein. Other devices, combinations of devices, or systems having equivalent or similar functions may also be used.

Claims

Claim 1 A peritoneal dialysis cycler comprising: a pressure sensor configured to measure the intraperitoneal pressure (IPP) of a fluid; and a controller, wherein the controller: monitors the intraperitoneal volume (IPV) of the fluid during a patient’s stay by monitoring at least the IPP during a stay using the pressure sensor; determines the density of the fluid during the stay based on the volume and weight of at least one sample of the fluid; and determines a change in the IPV based on a change in the IPP and a change in the density of at least the fluid during the stay. Claim 2 In paragraph 1, the controller is programmed to determine the IPV using an equation including the following, and ,where V0 is the volume of fluid at the start of the stay period, IPP0 is the IPP at the start of the stay period, ρ0 is the known density of the fluid at the start of the stay period, and ρ is the density of the fluid during the stay period, a peritoneal dialysis cycler. Claim 3 A peritoneal dialysis cycler according to claim 1, wherein determining the density of the fluid during the stay period comprises extracting at least one sample from the patient's peritoneal cavity, determining the volume and mass of the at least one sample, and then returning the at least one sample to the peritoneal cavity. Claim 4 A peritoneal dialysis cycler according to paragraph 3, wherein extracting at least one sample of the fluid is performed automatically, the retention is terminated when the ultrafiltration volume (UFV) reaches a target UFV, and the UFV is calculated by subtracting the initial filling volume of the fluid from the IPV. Claim 5 A peritoneal dialysis cycler according to paragraph 3, wherein the volume of the at least one sample is calculated based on a flow sensor measurement of the fluid extracted from the peritoneal cavity, and the mass of the fluid is determined using a scale that measures the weight of the at least one sample. Claim 6 A peritoneal dialysis cycler according to claim 1, further comprising a temperature sensor configured to measure the temperature of the fluid. Claim 7 A peritoneal dialysis cycler according to claim 6, wherein the controller is configured to compensate for the pressure and the density based on the temperature of the fluid. Claim 8 A peritoneal dialysis cycler according to claim 1, wherein the controller is configured to periodically determine the density. Claim 9 delete Claim 10 delete Claim 11 delete Claim 12 delete Claim 13 delete Claim 14 delete Claim 15 delete Claim 16 delete Claim 17 delete Claim 18 delete Claim 19 delete Claim 20 delete

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