Determining utility of a treatment plan

Abstract

The present disclosure relates to devices, systems, and techniques for determining the efficacy of a treatment plan. For example, a medical device system includes a medical device including one or more sensors configured to generate signals indicative of a parameter of a patient. Additionally, the medical device system includes processing circuitry configured to receive data indicative of a user’s selection of a reference time; determine a plurality of parameter values of the parameter based on a portion of the signals corresponding to a period of time including the reference time. Additionally, the processing circuitry is configured to identify a reference parameter value based on a first set of parameter values; calculate a parameter change value; and determine whether the patient has experienced an improvement or a worsening in response to a treatment administered beginning at the reference time based on the parameter change value.

Description

Technical Field

[0001] This disclosure relates generally to medical device systems, and more specifically to medical device systems configured to monitor patient parameters. Background Technology

[0002] Some types of medical devices can be used to monitor one or more physiological parameters of a patient. Such medical devices may include sensors that detect signals associated with these physiological parameters, or may be part of a system that includes said sensors. Values ​​determined based on these signals can be used to help detect changes in the patient's condition, assess the effectiveness of treatment, or evaluate the patient's overall health. Summary of the Invention

[0003] In general, this disclosure relates to devices, systems, and techniques for determining whether one or more symptoms or physiological parameters of a patient have improved or worsened in response to applied treatment. For example, a medical device (e.g., an implantable medical device (IMD)) may collect signals including one or more values ​​of a patient's parameter (e.g., a physiological parameter) over a period of time prior to treatment application and one or more values ​​of that parameter over a period of time following treatment application. Based on these signals, processing circuitry can identify whether the parameter has changed from the time prior to treatment application to the time following treatment application, for example, whether the parameter has improved or worsened. For example, if the parameter change value is greater than a first threshold parameter change value, the processing circuitry can determine that improvement (e.g., recovery) of the physiological parameter has occurred. Alternatively, if the parameter change value is less than a second threshold parameter change value, the processing circuitry can determine that the patient's physiological parameter has worsened.

[0004] The technology disclosed herein can provide one or more advantages. For example, it can be beneficial for the processing circuitry to receive data indicating the start time (e.g., a specific day, hour, or second) of a treatment plan applied to a patient. In some examples, the processing circuitry can receive data from an external device (e.g., a clinician programmer, a patient programmer, or a mobile device) representing user input regarding the start time of the treatment plan. The processing circuitry can store the data in memory. Additionally, the IMD can collect multiple parameter values, each representing a parameter measurement at a corresponding time point, some before and some after the start time of the treatment plan. In this way, compared to techniques that determine the patient's condition without an indication of the start time of the treatment plan, the processing circuitry can more accurately determine whether the corresponding physiological parameters have improved or worsened based on multiple parameter values ​​measured by the IMD and the start time of the treatment plan.

[0005] In some examples, a medical device system includes: a medical device comprising: one or more sensors configured to generate signals indicative of parameters to a patient; and processing circuitry configured to: receive data indicative of a user's selection of a reference time; determine a plurality of parameter values ​​for the parameter based on a portion of the signal corresponding to a period of time including the reference time, wherein each of the plurality of parameter values ​​represents a measurement of the parameter within a corresponding time interval during the period of time; identify a reference parameter value based on a first set of parameter values ​​occurring before the reference time; calculate a parameter change value based on a second set of parameter values ​​occurring after the reference time and based on the reference parameter values; and determine, based on the parameter change value, whether the patient has improved or worsened in response to treatment initiated at the reference time.

[0006] In some examples, a method includes: a medical device including one or more sensors generating a signal indicative of a patient's parameters; a processing circuit receiving data indicative of a user's selection of a reference time; the processing circuit determining a plurality of parameter values ​​for the parameters based on a portion of the signal corresponding to a period of time including the reference time, wherein each of the plurality of parameter values ​​represents a measurement of the parameter within a corresponding time interval during the period of time; the processing circuit identifying a reference parameter value based on a first set of parameter values ​​occurring before the reference time; the processing circuit calculating a parameter change value based on a second set of parameter values ​​occurring after the reference time and based on the reference parameter value; and the processing circuit determining, based on the parameter change value, whether the patient has improved or worsened in response to treatment initiated at the reference time.

[0007] In some examples, a non-transitory computer-readable medium includes instructions for causing one or more processors to: generate a signal indicative of a patient's parameters; receive data indicative of a user's selection of a reference time; determine a plurality of parameter values ​​for the parameters based on a portion of the signal corresponding to a period of time including the reference time, wherein each of the plurality of parameter values ​​represents a measurement of the parameter within a corresponding time interval during the period of time; identify a reference parameter value based on a first set of parameter values ​​occurring before the reference time; calculate a parameter change value based on a second set of parameter values ​​occurring after the reference time and based on the reference parameter value; and determine, based on the parameter change value, whether the patient has improved or worsened in response to treatment initiated at the reference time.

[0008] This summary is intended to provide an overview of the subject matter described in this disclosure. It is not intended to provide an exclusive or exhaustive explanation of the systems, apparatus, and methods described in detail in the following drawings and description. Further details of one or more examples of this disclosure are set forth in the following drawings and description. Other features, objects, and advantages will become apparent from this specification, the drawings, and the claims. Attached Figure Description

[0009] Figure 1 An environment for an example medical device system combined with a patient, based on one or more technologies of this disclosure, is shown.

[0010] Figure 2 It demonstrates one or more technologies as described in this article. Figure 1 A conceptual diagram of an example configuration of an implantable medical device (IMD) for a medical device system.

[0011] Figure 3 It demonstrates one or more technologies as described in this article. Figure 1 and Figure 2 A functional block diagram of an example configuration for an IMD.

[0012] Figure 4A and Figure 4B This demonstrates the compatibility of one or more of the techniques described herein with... Figures 1 to 3 The two additional example IMDs are basically similar but can include one or more additional features.

[0013] Figure 5 It demonstrates one or more technologies according to this disclosure. Figure 1 A block diagram illustrating an example configuration of components for an external device.

[0014] Figure 6 This is a block diagram illustrating an example system based on one or more of the technologies described herein. The example system includes an access point, a network, external computing devices (e.g., servers), and one or more other computing devices that can be coupled via the network to… Figure 1 IMD, external devices and processing circuitry.

[0015] Figure 7 It is a graph that displays the sequence of parameter values ​​and the first set of differences according to one or more techniques described in this article.

[0016] Figure 8 It is a graph that displays a sequence of parameter values ​​and a second set of differences based on one or more techniques described in this article.

[0017] Figure 9 It is a demonstration of one or more techniques described in this article by Figure 1 A graph showing the sequence of impedance parameter values ​​measured by the IMD over a period of time.

[0018] Figure 10 It is a graph that displays a sequence of impedance parameter values, mean baseline impedance, and mean estimated impedance according to one or more techniques described in this article.

[0019] Figure 11 It is a graph that displays a sequence of impedance parameter values ​​according to one or more techniques described in this article.

[0020] Figure 12 It is a graph showing the parametric curves of the deterioration threshold and the improvement threshold according to one or more techniques described in this article.

[0021] Figure 13 This is a flowchart illustrating an example operation of determining whether one or more of a patient's symptoms or physiological parameters have improved or worsened based on a user's selection of a reference time, according to one or more techniques disclosed herein.

[0022] Figure 14 This is a flowchart illustrating an example operation of determining, based on a scrolling window, whether one or more of a patient's symptoms or physiological parameters have improved or worsened, according to one or more techniques of this disclosure.

[0023] Throughout the specification and drawings, similar reference numerals denote similar elements. Detailed Implementation

[0024] This disclosure describes techniques for measuring signals representing one or more parameters of a patient. Changes in patient parameters can be markers of changes (e.g., improvement or worsening) in patient symptoms, patient condition, or physiological parameters in response to an event (e.g., administration of a treatment plan to the patient). In some examples, it may be advantageous to track parameters in response to the start time of the treatment plan to determine whether the parameters have changed significantly over a period after the administration of the treatment plan. More specifically, a significant change in patient parameters from a period before the start of the treatment plan to a period after the start of the treatment plan can be a marker that one or more of the patient's symptoms or physiological parameters have improved or worsened due to the treatment plan. Additionally, in some cases, it may be advantageous to track more than one parameter of the patient relative to the start time of the treatment plan to determine whether the patient has improved or worsened. In some examples, it may be advantageous to track parameters on a rolling basis to determine whether there has been a significant change in the parameter over a period prior to the current time (e.g., 7 days).

[0025] Figure 1An environment for an example medical device system 2, in conjunction with a patient 4, is illustrated according to one or more technologies of this disclosure. The example technologies can be used with an implantable medical device (IMD) 10, which can be used with an external device 12, processing circuitry 14, and... Figure 1 At least one of the other devices not depicted herein performs wireless communication. For example, an external device ( Figure 1 (Not shown) may include at least a portion of processing circuitry 14, the external device being configured to communicate with the IMD 10 and the external device 12. In some examples, the IMD 10 is implanted outside the chest cavity of the patient 4 (e.g., Figure 1 The chest location shown is subcutaneous. The IMD 10 can be positioned near the sternum at or just below the level of the heart, for example, at least partially within the heart contour. In some examples, the IMD 10 takes the form of the LINQ™ Insertable Cardiac Monitor (ICM), available from Medtronic in Dublin, Ireland. Alternatively or concurrently, the example technology can be... Figure 1 It can be used with other medical devices not shown in the description (such as another type of IMD, patch monitoring device, wearable device (e.g., smartwatch) or another type of external medical device).

[0026] Although in one example the IMD 10 takes the form of an ICM, in other examples, as an example, the IMD 10 may take the form of an implantable cardiac device (ICD) with intravascular or extravascular leads, a pacemaker, a cardiac resynchronization therapy device (CRT-D), a neuromodulation device, a left ventricular assist device (LVAD), an implantable sensor, a cardiac resynchronization therapy pacemaker (CRT-P), an implantable pulse generator (IPG), an orthotic device, or a drug pump. Furthermore, based on signals collected by one or more of the aforementioned devices, the techniques of this disclosure can be used to measure one or more patient parameters. Alternatively or additionally, based on signals collected by one or more external devices (such as patch devices, wearable devices (e.g., smartwatches), wearable sensors, or any combination thereof), the techniques of this disclosure can be used to measure one or more patient parameters.

[0027] Clinicians sometimes diagnose a patient's (e.g., Patient 4) medical condition and / or determine whether Patient 4's condition is improving or worsening based on one or more observed physiological signals collected by physiological sensors (e.g., electrodes, optical sensors, chemical sensors, temperature sensors, acoustic sensors, and motion sensors). In some cases, when a patient is in a clinic, clinicians apply non-invasive sensors to the patient to sense one or more physiological signals. However, in some examples, events that could alter a patient's condition (e.g., the administration of treatment) may occur outside the clinic. Therefore, in these examples, clinicians may not be able to observe the physiological indicators needed to determine whether an event has altered the patient's medical condition and / or whether the patient's medical condition is improving or worsening when monitoring one or more of the patient's physiological signals during a medical visit. Figure 1 In the example shown, IMD 10 was implanted in patient 4 to continuously record one or more physiological signals of patient 4 over an extended period of time.

[0028] In some examples, the IMD 10 includes multiple electrodes. These electrodes are configured to detect signals that enable the processing circuitry of the IMD 10 to determine current values ​​of additional parameters associated with the patient's cardiac and / or lung function. In some examples, the multiple electrodes of the IMD 10 are configured to detect signals indicating the electrical potential of the tissue surrounding the IMD 10. Furthermore, in some examples, the IMD 10 may additionally or alternatively include one or more optical sensors, accelerometers, temperature sensors, chemical sensors, light sensors, pressure sensors, and acoustic sensors. Such sensors can detect one or more physiological parameters indicative of the patient's condition.

[0029] External device 12 may be a handheld computing device having a display viewable by a user and an interface for providing input to external device 12 (i.e., a user input mechanism). For example, external device 12 may include a small display screen (e.g., a liquid crystal display (LCD) or a light-emitting diode (LED) display) that presents information to the user. Alternatively, external device 12 may include a touchscreen display, a keyboard, buttons, peripheral pointing devices, voice activation, or another input mechanism that allows the user to navigate the user interface of external device 12 and provide input. If external device 12 includes buttons and a keyboard, the buttons may be dedicated to performing a specific function (e.g., a power button), and the buttons and keyboard may be soft keys that change in function depending on the portion of the user interface currently being viewed by the user or any combination thereof.

[0030] In other examples, external device 12 may be a larger workstation or a separate application within another multi-functional device, rather than a dedicated computing device. For example, the multi-functional device may be a laptop computer, tablet computer, workstation, one or more servers, cellular phone, personal digital assistant, or another computing device that can run an application that enables the computing device to operate as a security device.

[0031] When external device 12 is configured for use by a clinician, it can be used to transmit commands to IMD 10. Example commands may include a request to set up the electrode combination for sensing, as well as any other information that may be useful for programming into IMD 10. Clinicians can also use external device 12 to configure and store operating parameters of IMD 10 within IMD 10. In some examples, external device 12 assists clinicians in configuring IMD 10 by providing a system for identifying potentially beneficial operating parameter values.

[0032] Whether external device 12 is configured for use by clinicians or patients, external device 12 is configured to communicate wirelessly with IMD 10 and optionally another computing device. Figure 1 (Not shown in the image) Communication. For example, external device 12 can communicate via near-field communication technologies (e.g., inductive coupling, NFC, or other communication technologies that operate within a range of less than 10 cm to 20 cm) and far-field communication technologies (e.g., RF telemetry according to the 802.11 or Bluetooth® specification set, or other communication technologies that operate beyond the range of near-field communication technologies). In some examples, external device 12 is configured to communicate with a computer network, such as the Medtronic CareLink® network developed by Medtronic in Dublin, Ireland. For example, external device 12 can send data (e.g., data received from IMD 10) to another external device (e.g., a smartphone, tablet, or desktop computer), which in turn can send the data to the computer network. In other examples, external device 12 can communicate directly with the computer network without intermediate devices.

[0033] In some examples, processing circuitry 14 may include one or more processors configured to implement functions and / or process instructions for execution within IMD 10. For example, processing circuitry 14 may be able to process instructions stored in a storage device. Processing circuitry 14 may include, for example, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or equivalent discrete or integrated logic circuitry, or a combination of any of the foregoing devices or circuits. Therefore, processing circuitry 14 may include any suitable structure (whether in hardware, software, firmware, or any combination thereof) to perform the functions attributed to processing circuitry 14 herein.

[0034] Processing circuitry 14 may represent processing circuitry located within either or both of the IMD 10 and the external device 12. In some examples, processing circuitry 14 may be entirely located within the housing of the IMD 10. In other examples, processing circuitry 14 may be entirely located within the housing of the external device 12. In still other examples, processing circuitry 14 may be located within the housing of the IMD 10, the external device 12, and... Figure 1 This refers to any other device or group of devices not shown herein. Therefore, the technology and capabilities of the processing circuitry 14 attributed herein may be attributed to IMD 10, external device 12, and... Figure 1 Any combination of other devices not shown in the document.

[0035] Figure 1 The medical device system 2 is an example of a system configured to collect electrogrammography (EGM) signals according to one or more techniques of this disclosure. In some examples, the processing circuitry 14 includes EGM analysis circuitry configured to determine one or more parameters of the EGM signal of the patient 4. In one example, the EGM signal is sensed via one or more electrodes of the IMD 10. The EGM is a signal representing cardiac electrical activity measured by electrodes implanted in the body and is typically within the heart itself. For example, cardiac EGM may include P waves (atrial depolarization), R waves (ventricular depolarization), and T waves (ventricular repolarization), as well as other events. Information related to the aforementioned events (e.g., the time intervals separating one or more events) can be applied for various purposes, such as determining whether an arrhythmia is occurring and / or predicting whether an arrhythmia may occur. The cardiac signal analysis circuitry, which may be implemented as part of the processing circuitry 14, can perform signal processing techniques to extract information indicating one or more parameters of the cardiac signal.

[0036] In some examples, the IMD 10 includes one or more accelerometers. The accelerometers of the IMD 10 can collect accelerometer signals reflecting measurements of any one or more of the patient 4's motion, posture, and body angles. In some cases, the accelerometers can collect triaxial accelerometer signals indicating the patient 4's movement in three-dimensional Cartesian space. For example, the accelerometer signals may include a vertical axis accelerometer signal vector, a lateral axis accelerometer signal vector, and a positive axis accelerometer signal vector. The vertical axis accelerometer signal vector may represent the patient 4's acceleration along the vertical axis, the lateral axis accelerometer signal vector may represent the patient 4's acceleration along the lateral axis, and the positive axis accelerometer signal vector may represent the patient 4's acceleration along the positive axis. In some cases, the vertical axis extends substantially along the patient 4's torso from the neck to the waist, the lateral axis extends perpendicular to the vertical axis across the patient 4's chest, and the positive axis extends outward from and across the patient 4's chest, perpendicular to both the vertical and lateral axes.

[0037] IMD 10 can measure a set of parameters including patient 4's impedance (e.g., subcutaneous impedance, intrathoracic impedance, or intracardiac impedance), patient 4's nocturnal respiratory rate, patient 4's daytime respiratory rate, patient 4's nocturnal heart rate, patient 4's daytime heart rate, patient 4's atrial fibrillation (AF) burden, patient 4's ventricular rate during AF, or any combination thereof. Processing circuitry 14 can analyze any one or more parameters in this set to determine the utility of a treatment plan applied to patient 4. In some examples, the treatment plan may include treatment delivered by one or more medical devices (e.g., an ICD with intravascular or extravascular leads, a pacemaker, a CRT-D, a neuromodulation device, an LVAD, an implantable sensor, an orthopedic device, or a drug pump). Alternatively or concurrently, the treatment plan may include outpatient treatment administered by a medical professional, a prescription drug treatment regimen, treatment administered by one or more external medical devices, or any combination thereof. In any case, processing circuit 14 can determine the utility of the treatment plan by determining the time when the treatment plan is applied (e.g., including the start and / or end times of the treatment plan) and analyzing the value of any one or more parameters in that set of parameters relative to the time of application of the treatment plan. Alternatively, in some examples, processing circuit 14 can determine the utility of the treatment plan by evaluating one or more parameters on a rolling basis to determine whether the one or more parameters have changed over a period of time.

[0038] In some examples, one or more sensors of the IMD 10 (e.g., electrodes, motion sensors, optical sensors, temperature sensors, or any combination thereof) can generate signals indicating patient parameters. In some examples, the signals indicating parameters include multiple parameter values, where each of the multiple parameter values ​​represents a measurement of the parameter within a corresponding time interval. These multiple parameter values ​​can represent a sequence of parameter values, where each parameter value in the sequence is collected by the IMD 10 at the beginning of each time interval in the time interval sequence. For example, the IMD 10 can perform parameter measurements to determine the parameter values ​​in the sequence of parameter values ​​based on cyclic time intervals (e.g., daily, nightly, every other day, every twelve hours, hourly, or any other cyclic time interval). In this way, the IMD 10 can be configured to track corresponding patient parameters more efficiently than techniques that track patient parameters during a patient's visit, because the IMD 10 is implanted in the patient and configured to perform parameter measurements according to cyclic time intervals without missing a time interval or performing parameter measurements out of schedule.

[0039] Processing circuit 14 can receive a portion of a signal including multiple parameter values. In this way, processing circuit 14 can receive at least a portion of a sequence of parameter values, allowing it to analyze the signal to determine whether patient 4 is experiencing improvement or deterioration. In some examples, processing circuit 14 can receive data indicating a user's selection of a reference time. Processing circuit 14 can receive data from external device 12 or another device, wherein the user's selection is a choice by the patient and / or clinician regarding the timing of the treatment plan. As described herein, the "time" at which the treatment plan begins can refer to a time window for administering the treatment plan, a point in time when the treatment plan begins (e.g., a day, an hour, a second, or a fraction of a second), a point in time when the treatment plan ends, or any combination thereof. In some examples, the treatment plan can be administered in an inpatient facility, an outpatient facility, outside of a medical facility (e.g., at the patient's home), or any combination thereof.

[0040] In some examples, IMD 10 may continuously collect parameter values ​​at a predetermined frequency. IMD 10, the server, or another storage device may include buffers or other memory structures for temporary or permanent storage of parameter values. In response to receiving data indicating a user's selection of a reference time, processing circuitry 14 retrieves or accesses one or more parameter values ​​for analysis based on the reference time indicating an event such as the start of a treatment plan.

[0041] To determine whether a treatment plan is effective, it may be beneficial for processing circuit 14 to determine whether patient parameters reflect improvement (e.g., recovery) in patient 4 regarding various aspects of the time window for administering the treatment plan (e.g., the start time of the treatment plan). Processing circuit 14 can identify reference parameter values ​​corresponding to a period of time prior to administering the treatment plan to patient 4. In this way, processing circuit 14 can determine a baseline value and compare it with parameter values ​​measured at the time of administering the treatment plan or after the treatment plan has ended.

[0042] Processing circuit 14 can determine whether a patient parameter reflects improvement in patient 4 based on a clinically significant change in the patient parameter relative to the occurrence of an event. This event may include, for example, the start of a treatment program administered to the patient or the end of a treatment program administered to patient 4. A clinically significant change can represent a positive or negative change in the parameter. As used herein, "start of a treatment program" can refer to a change in an ongoing treatment program (e.g., a change in drug dosage, a change in one or more parameters of electrical stimulation therapy) and / or the start of a new treatment program.

[0043] Processing circuit 14 can identify a reference parameter value based on a first set of parameter values ​​from a plurality of parameter values. For example, processing circuit 14 can identify the reference parameter value as the mean or median of the first set of parameter values. The first set of parameter values ​​can represent parameter values ​​collected by IMD 10 prior to the start time of the treatment plan. In some examples, processing circuit 14 can select the first set of parameter values ​​based on the start time of the treatment plan and calculate the "increment (Δ) value" as the difference between the reference parameter value and the target parameter value. The target parameter value can represent a parameter value corresponding to the complete or near-complete recovery of patient 4 from symptoms or condition. In other words, if a parameter deviates from the target parameter value due to the condition or symptoms present in patient 4, in some cases, the improvement of patient 4 can be measured based on the return or partial return of the parameter to the target parameter value. In this way, the deviation of the parameter from the target parameter value caused by the condition or symptoms can be indicated by the reference parameter value. Additionally, in some examples, processing circuit 14 can be configured to identify a significant deterioration of the patient's condition or physiological parameter by determining that the parameter has changed away from the reference parameter value from the target parameter value.

[0044] After identifying the reference parameter value and the incremental value, the processing circuit 14 can calculate the parameter change value based on a second set of parameter values ​​that occurred after the reference time, and based on the reference parameter value. The parameter change value can represent a value indicating the relative amount by which a parameter has changed from the reference parameter value since the start of the treatment plan. The second set of parameter values ​​can represent the parameter values ​​collected by the IMD 10 after the start time of the treatment plan. If the parameter change value indicates a change towards the target parameter value, the processing circuit can determine that patient 4 has improved. If the parameter change value indicates a change away from the target parameter value, the processing circuit can determine that patient 4 has deteriorated.

[0045] In some examples, processing circuitry 14 is configured to select a second set of parameter values. In some examples, to select the second set of parameter values, processing circuitry 14 is configured to select the second set of parameter values ​​based on the time when the treatment plan begins. For example, each of the plurality of parameter values ​​can be separated from its corresponding adjacent (e.g., consecutive) parameter values ​​by a time window of a predetermined duration (e.g., one day). In this way, the plurality of parameter values ​​can form a sequence of parameter values ​​collected by IMD 10 at a predetermined frequency (e.g., one parameter value per day, one parameter value per hour, one parameter value per minute, or any other frequency). In some examples, processing circuitry 14 can receive data indicating the user's selection of a predetermined duration and / or a predetermined frequency. To select the second set of parameter values, processing circuitry 14 can select the parameter from the parameter value sequence collected by IMD 10 closest to the time when the treatment plan begins. For example, processing circuitry 14 can receive data indicating the time when the treatment plan begins. Subsequently, processing circuitry 14 can identify the parameter value from the parameter value sequence collected closest to the time when the treatment plan begins (e.g., the treatment start parameter value). In some examples, the processing circuit 14 may select the second set of parameter values ​​to include (e.g., consecutive) groups of parameter values ​​collected by IMD 10 after the treatment start parameter values ​​from the parameter value sequence.

[0046] In some examples, processing circuit 14 may select the second set of parameter values ​​as including a predetermined number of parameter values ​​(e.g., four parameter values) following the treatment start parameter value in the parameter value sequence. Alternatively, processing circuit 14 may select the second set of parameter values ​​as including five parameter values ​​following the treatment start parameter value in the parameter value sequence, and processing circuit 14 may select the second set of parameter values ​​as including six parameter values ​​following the treatment start parameter value in the parameter value sequence. In this way, the second set of parameter values ​​may include three consecutive parameter values ​​starting a predetermined number of days (e.g., 5 days) after the start of treatment, but this is not mandatory. In some examples, the second set of parameter values ​​may include a set of fewer than three consecutive parameter values, a set of more than three consecutive parameter values, or a set of parameter values ​​including at least two non-consecutive parameter values. In some examples, the second set of parameter values ​​may begin less than five days after the treatment start parameter value or more than five days (e.g., six days) after the treatment start parameter value.

[0047] The second set of parameter values ​​may include any one or more parameter values ​​collected by IMD 10 after the treatment start parameter value. Much like the second set of parameter values, processing circuitry 14 may select the first set of parameter values ​​based on the treatment start parameter value representing the parameter value closest to the start time of the treatment plan. For example, processing circuitry 14 may select the first set of parameter values ​​to include four consecutive parameter values ​​in the parameter value sequence immediately preceding the treatment start parameter value, but this is not required. Processing circuitry 14 may select the first set of parameter values ​​to include any one or more parameter values ​​in the parameter value sequence immediately preceding the treatment start parameter value.

[0048] To calculate the parameter change value, processing circuit 14 can be configured to identify a set of differences. In some examples, processing circuit 14 can identify each difference in the set of differences by calculating the difference between the corresponding parameter value in the second set of parameter values ​​and a reference parameter value, and processing circuit 14 can calculate the parameter change value based on the set of differences. For example, processing circuit 14 can determine the sum of the set of differences, and processing circuit 14 can determine the increment value representing the difference between the reference parameter value and the target parameter value. Processing circuit 14 can calculate the parameter change value as the ratio of the sum of the set of differences to the increment value.

[0049] Processing circuit 14 can determine whether a patient has improved or worsened in response to treatment administered to patient 4 based on parameter change values. For example, to determine whether patient 4 has improved, processing circuit 14 is configured to determine whether the parameter change value exceeds a first threshold parameter change value. If the parameter change value exceeds the first threshold parameter change value, processing circuit 14 can determine that patient 4 has improved (e.g., recovered) by the end of the second set of parameter values. As used herein, the term "exceeds" refers to examples where the parameter change value is greater than the corresponding threshold when the threshold is positive, and examples where the parameter change value is less than the corresponding threshold when the threshold is negative. If the parameter change value does not exceed the first threshold parameter change value, processing circuit 14 can determine that patient 4 has not improved by the end of the second set of parameter values. In some examples, the first threshold parameter change value is in the range of 0.5 to 0.9 (e.g., 0.7), but this is not required. The parameter change value can represent any value or range of values.

[0050] In some examples, if the parameter change exceeds a second threshold parameter change, the processing circuit 14 can determine that the patient 4 has deteriorated by the end of the second set of parameter values. In some examples, the first threshold parameter change and the second parameter change have opposite signs. That is, the first threshold parameter change can be positive and the second threshold parameter change can be negative, or the first threshold parameter change can be negative and the second threshold parameter change can be positive.

[0051] Although processing circuit 14 is described herein as determining whether patient 4 has improved or worsened due to the treatment plan based on whether a single parameter measured by IMD 10 has improved or worsened, in some cases, processing circuit 14 may be based on the parameters measured by IMD 10 and / or Figure 1 Other devices, not shown, collect more than one parameter to identify improvement or deterioration in patient 4. For example, processing circuit 14 may receive data indicating a sequence of parameter values, where each parameter value sequence in the set corresponds to a corresponding parameter in a set of parameters. Processing circuit 14 may determine whether improvement or deterioration of each parameter in the set of parameters has been detected based on the time when the treatment plan started. Based on whether the processing circuit detected improvement or deterioration of each parameter in the set of parameters, processing circuit 14 may determine whether patient 4's medical condition has improved or deteriorated due to the treatment plan. Alternatively, processing circuit 14 may combine the sequence of parameter values ​​into a single set of parameter values ​​that defines a combined metric. Processing circuit 14 may analyze this single set of parameter values ​​that defines the combined metric to determine whether patient 4's medical condition has improved or deteriorated.

[0052] In some examples, as a supplement or alternative to determining parameter change values ​​and comparing them to one or more threshold parameter change values, processing circuitry 14 is configured to determine whether patient 4 has improved or worsened based on one or more parameters. For example, processing circuitry 14 can analyze the parameter value sequence by performing one or more operations on the parameter value sequence (e.g., assessing the rate of change or assessing diagnostic metrics such as transition rate and slope). In some examples, processing circuitry 14 can calculate the derivative of the parameter value sequence, calculate the integral of the parameter value sequence, fit the parameter value sequence to a known curve to assess deviation from a normal trajectory, or any combination thereof. Processing circuitry 14 can use any of these operations to determine whether patient 4 has improved or worsened.

[0053] In some examples, processing circuit 14 may use raw diagnostic variables collected by IMD 10 to calculate parameter changes to assess the efficacy of the diuretic. These diagnostic variables include impedance (e.g., subcutaneous impedance, intrathoracic impedance, or intracardiac impedance), respiratory rate, nocturnal heart rate, AF load, ventricular rate during AF, R-wave amplitude, R-wave width, R-wave transition rate, heart sound amplitude, tissue perfusion value, tissue temperature value, or any combination thereof, as these diagnostic variables can dynamically respond to the patient's volume status. In some examples, for each corresponding diagnostic variable, a reference value may be calculated as the average of the last four days prior to the start of a treatment plan (e.g., an on-demand (PRN) treatment plan). In some examples, the difference between the raw value and the target value for each corresponding diagnostic variable on days 5 through 7 after PRN initiation may be calculated to determine whether the patient's medical condition has improved or worsened.

[0054] Figure 2 It demonstrates one or more technologies as described in this article. Figure 1 A conceptual diagram of an example configuration of IMD 10 for Medical Device System 2. Figure 2 In the example shown, IMD 10 may include a leadless subcutaneous implantable monitoring device having a housing 15, a proximal electrode 16A, and a distal electrode 16B. The housing 15 may further include a first main surface 18, a second main surface 20, a proximal end 22, and a distal end 24. In some examples, IMD 10 may include one or more additional electrodes 16C, 16D positioned on one or both of the main surfaces 18, 20 of IMD 10. The housing 15 surrounds the electronic circuitry located within IMD 10 and protects the contained circuitry from fluids (e.g., bodily fluids). In some examples, an electrical feedthrough provides electrical connections between electrodes 16A-16D and antenna 26 to the circuitry within housing 15. In some examples, electrode 16B may be formed from an uninsulated portion of the conductive housing 15.

[0055] exist Figure 2 In the example shown, IMD 10 is defined by a length L, a width W, and a thickness or depth D. In this example, IMD 10 has the shape of an elongated rectangular prism, where the length L is significantly greater than the width W, and where the width W is greater than the depth D. However, other configurations of IMD 10 are envisioned, such as those where the relative proportions of the length L, width W, and depth D differ. Figure 2 The configurations described and illustrated herein. In some examples, the geometry of the IMD 10 (e.g., width W greater than depth D) can be selected to allow the IMD 10 to be inserted under the patient's skin using minimally invasive surgery and to maintain the desired orientation during insertion. Additionally, the IMD 10 may include radial asymmetry (e.g., a rectangular shape) along the longitudinal axis of the IMD 10, which can help maintain the device in the desired orientation after implantation.

[0056] In some examples, the spacing between the proximal electrode 16A and the distal electrode 16B can range from approximately 30 mm to 55 mm, approximately 35 mm to 55 mm, or approximately 40 mm to 55 mm, or more generally from approximately 25 mm to 60 mm. In general, the IMD 10 can have a length L of approximately 20 mm to 30 mm, approximately 40 mm to 60 mm, or approximately 45 mm to 60 mm. In some examples, the width W of the main surface 18 can range from approximately 3 mm to 10 mm, and can be any single width or width range between approximately 3 mm and 10 mm. In some examples, the depth D of the IMD 10 can range from approximately 2 mm to 9 mm. In other examples, the depth D of the IMD 10 can range from approximately 2 mm to 5 mm, and can be any single depth or depth range between approximately 2 mm and 9 mm. In any such example, the IMD 10 is compact enough to be implanted within the subcutaneous space of the patient's 4th pectoral muscle region.

[0057] According to examples of this disclosure, the IMD 10 can have a geometry and size designed for easy implantation and patient comfort. Examples of the IMD 10 described in this disclosure can have a volume of 3 cubic centimeters (cm²). 3 or smaller, 1.5 cm 3 Or a smaller volume, or any volume in between. Additionally, in Figure 2 In the example shown, the proximal end 22 and the distal end 24 are rounded to reduce discomfort and irritation to surrounding tissues when implanted under the skin of the patient 4.

[0058] exist Figure 2In the example shown, when the IMD 10 is inserted into the patient 4, the first main surface 18 of the IMD 10 faces outward toward the skin, while the second main surface 20 faces inward toward the muscle tissue of the patient 4. Therefore, the first main surface 18 and the second main surface 20 can face along the patient 4 (see...). Figure 1 The orientation of the sagittal axis is maintained, and due to the size of the IMD 10, this orientation can be maintained during implantation.

[0059] When the IMD 10 is implanted subcutaneously in patient 4, the proximal electrode 16A and distal electrode 16B can be used to sense cardiac EGM signals (e.g., electrocardiogram (ECG) signals). In some examples, the processing circuitry of the IMD 10 can also determine whether the patient 4's cardiac ECG signal indicates an arrhythmia or other abnormality, which can be evaluated by the processing circuitry of the IMD 10 to determine whether the patient 4's medical condition (e.g., heart failure, sleep apnea, or COPD) has changed. The cardiac ECG signal can be stored in the memory of the IMD 10, and data derived from the cardiac ECG signal can be transmitted via the integrated antenna 26 to another medical device, such as external device 12. In some examples, one or both of electrodes 16A and 16B can also be used by the IMD 10 to detect impedance values ​​during impedance measurements performed by the IMD 10. In some examples, such impedance values ​​detected by the IMD 10 can reflect the resistance values ​​associated with the contact between electrodes 16A, 16B and the target tissue of patient 4. Additionally, in some examples, electrodes 16A and 16B can be used by the communication circuitry of IMD 10 to perform tissue conduction communication (TCC) with external device 12 or another device.

[0060] exist Figure 2 In the example shown, the proximal electrode 16A is very close to the proximal end 22, and the distal electrode 16B is very close to the distal end 24 of the IMD 10. In this example, the distal electrode 16B is not limited to a flat, outward-facing surface, but can extend from the first main surface 18 around the circular edge 28 or the end surface 30 and reach the second main surface 20 in a three-dimensional curved configuration. As shown, the proximal electrode 16A is located on the first main surface 18 and is substantially flat and outward-facing. However, in other examples not shown here, both the proximal electrode 16A and the distal electrode 16B can be configured similarly to Figure 2 The proximal electrode 16A shown, or may be configured similarly Figure 2The distal electrode 16B is shown. In some examples, additional electrodes 16C and 16D may be positioned on one or both of the first main surface 18 and the second main surface 20, such that the IMD 10 comprises a total of four electrodes. Any one of electrodes 16A-16D may be formed of a biocompatible conductive material. For example, any one of electrodes 16A-16D may be formed of stainless steel, titanium, platinum, iridium, or alloys thereof. Additionally, the electrodes of the IMD 10 may be coated with materials such as titanium nitride or fractal titanium nitride, although other suitable materials and coatings for such electrodes may also be used.

[0061] exist Figure 2 In the example shown, the proximal end 22 of the IMD 10 includes a head assembly 32 having one or more of a proximal electrode 16A, an integrated antenna 26, an anti-migration protrusion 34, and a suture hole 36. The integrated antenna 26 is located on the same main surface as the proximal electrode 16A (e.g., a first main surface 18) and may be integral with the head assembly 32. In other examples, the integrated antenna 26 may be formed on a main surface opposite to the proximal electrode 16A, or in still other examples, it may be integrated within the housing 15 of the IMD 10. The antenna 26 may be configured to transmit or receive electromagnetic signals for communication. For example, the antenna 26 may be configured to transmit or receive signals from a programmer via inductive coupling, electromagnetic coupling, tissue conduction, near-field communication (NFC), radio frequency identification (RFID), Bluetooth®, Wi-Fi®, or other proprietary or non-proprietary wireless telemetry communication schemes. Antenna 26 can be coupled to the communication circuit of IMD 10, which can drive antenna 26 to transmit signals to external device 12, and can also transmit signals received from external device 12 to the processing circuit of IMD 10 via the communication circuit.

[0062] IMD 10 may include several features for retention in place after subcutaneous implantation in a patient. For example, such as Figure 2 As shown, the housing 15 may include anti-migration protrusions 34 positioned adjacent to the integrated antenna 26. The anti-migration protrusions 34 may include a plurality of bumps or protrusions extending away from the first main surface 18 and may help prevent longitudinal movement of the IMD 10 after implantation in the patient 4. In other examples, the anti-migration protrusions 34 may be located on the main surface opposite to the proximal electrode 16A and / or the integrated antenna 26. Additionally, in Figure 2In the example shown, the head assembly 32 includes a suture hole 36, which provides another means of securing the IMD 10 to the patient to prevent movement after insertion. In the example shown, the suture hole 36 is positioned adjacent to the proximal electrode 16A. In some examples, the head assembly 32 may include a molded head assembly made of polymer or plastic material, which may be integrated with or detached from the main portion of the IMD 10.

[0063] As described above, electrodes 16A and 16B can be used to sense cardiac ECG signals. In some examples, as a supplement to or alternative to electrodes 16A and 16B, additional electrodes 16C and 16D can be used to sense subcutaneous tissue impedance. In some examples, the processing circuitry of IMD 10 can determine the impedance value of patient 4 based on signals received from at least two of electrodes 16A-16D. For example, the processing circuitry of IMD 10 can generate either a current signal or a voltage signal, deliver the signal via two or more electrodes selected from electrodes 16A-16D, and measure the other of the generated current or voltage. The processing circuitry of IMD 10 can determine the impedance value based on the delivered current or voltage and the measured voltage or current.

[0064] In some examples, IMD 10 may include one or more additional sensors, such as one or more accelerometers (not shown) and / or one or more optical sensors (not shown). Such accelerometers may be 3D accelerometers configured to generate signals indicating one or more types of patient movement (e.g., overall body movement, patient posture, movement associated with heartbeat, or coughing, rales, or other respiratory abnormalities). One or more parameters monitored by IMD 10 (e.g., impedance, EGM) may fluctuate in response to changes in one or more of these types of movement. For example, changes in parameter values ​​may sometimes be attributed to increased patient movement (e.g., exercise or other body movements compared to immobility) or changes in patient posture, rather than necessarily to changes in the patient's medical condition. Therefore, in some methods of determining the utility of a treatment plan, it may be advantageous to consider such fluctuations when determining whether changes in parameters indicate an improvement or deterioration in the patient's medical condition.

[0065] Figure 3 It demonstrates one or more technologies as described in this article. Figure 1 and Figure 2 A functional block diagram of an example configuration of IMD 10. In the example shown, IMD 10 includes electrodes 16, an antenna 26, processing circuitry 50, sensing circuitry 52, communication circuitry 54, a storage device 56, a switching circuitry 58, a sensor 62, and a power supply 64, the sensor including (multiple) motion sensors 42. Although Figure 3Not shown, but sensor 62 may also include one or more photodetectors.

[0066] Processing circuitry 50 may include fixed-function circuitry and / or programmable processing circuitry. Processing circuitry 50 may include any one or more microprocessors, controllers, DSPs, ASICs, FPGAs, or equivalent discrete or analog logic circuits. In some examples, processing circuitry 50 may include multiple components, such as one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs, and any combination of other discrete or integrated logic circuits. The functionality of processing circuitry 50 as described herein may be implemented as software, firmware, hardware, or any combination thereof.

[0067] Sensing circuit 52 and communication circuit 54 can be selectively coupled to electrodes 16A-16D via switching circuit 58 controlled by processing circuit 50. Sensing circuit 52 can monitor signals from electrodes 16A-16D to monitor cardiac electrical activity (e.g., EGM-generating) and / or subcutaneous tissue impedance, which indicates at least some aspects of the patient 4's respiratory pattern, and EMG indicates at least some aspects of the patient 4's cardiac pattern. In some examples, the subcutaneous impedance signal collected by IMD 10 can indicate the patient 4's respiratory rate and / or respiratory intensity, and the EMG collected by IMD 10 can indicate the patient 4's heart rate and atrial fibrillation (AF) load. Sensing circuit 52 can also monitor signals from sensor 62, which may include motion sensors 42(s) and any additional sensors (such as photodetectors or pressure sensors) that can be positioned on IMD 10. In some examples, the sensing circuit 52 may include one or more filters and amplifiers for filtering and amplifying signals received from one or more electrodes 16A-16D and / or (multiple) motion sensors 42.

[0068] The communication circuitry 54 may include any suitable hardware, firmware, software, or any combination thereof for communicating with another device, such as external device 12 or another IMD or sensor (e.g., a pressure sensing device). Under the control of the processing circuitry 50, the communication circuitry 54 may receive downlink telemetry from external device 12 or another device and send uplink telemetry to it via an internal or external antenna (e.g., antenna 26). Additionally, the processing circuitry 50 may communicate with networked computing devices via external devices (e.g., external device 12) and computer networks (e.g., the Medtronic CareLink® network developed by Medtronic in Dublin, Ireland).

[0069] Clinicians or other users can obtain data from the IMD 10 using external device 12 or by using another local or networked computing device configured to communicate with the processing circuitry 50 via communication circuitry 54. Clinicians can also use external device 12 or another local or networked computing device to program the parameters of the IMD 10.

[0070] In some examples, storage device 56 includes computer-readable instructions that, when executed by processing circuitry 50, cause IMD 10 and processing circuitry 50 to perform various functions borne by IMD 10 and processing circuitry 50 herein. Storage device 56 may include any volatile, non-volatile, magnetic, optical, or electrical medium, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other digital medium.

[0071] Power source 64 is configured to deliver operating power to components of IMD 10. Power source 64 may include a battery and power generation circuitry for generating operating power. In some examples, the battery is rechargeable to allow for extended operation. In some examples, recharging is achieved via near-end inductive interaction between an external charger and an inductive charging coil within external device 12. Power source 64 may include any one or more of a variety of battery types, such as nickel-cadmium and lithium-ion batteries. Non-rechargeable batteries may be selected to last for several years, while rechargeable batteries may be inductively charged from an external device, for example, daily or weekly.

[0072] Figure 4A and Figure 4B This demonstrates the compatibility of one or more of the techniques described herein with... Figures 1 to 3 The two additional example IMDs are basically similar to IMD 10 but may include one or more additional features. Figure 4A and Figure 4B The components do not necessarily have to be drawn to scale, but can be enlarged to show details. Figure 4A This is a top view block diagram of an example configuration of IMD 10A. Figure 4B This is a block diagram of a side view of an example IMD 10B, which may include the insulating layer described below.

[0073] Figure 4A It demonstrates that it can be used with Figure 1 A conceptual diagram of another example, IMD 10A, which is basically similar to IMD 10. Besides... Figures 1 to 3 In addition to the components shown, Figure 4AThe example of IMD 10 shown may also include a body portion 72 and an attachment plate 74. The attachment plate 74 may be configured to mechanically couple the head assembly 32 to the body portion 72 of the IMD 10A. The body portion 72 of the IMD 10A may be configured to accommodate... Figure 3 One or more of the internal components of the IMD 10 shown, such as processing circuitry 50, sensing circuitry 52, communication circuitry 54, storage device 56, switching circuitry 58, internal components of sensor 62, and power supply 64. In some examples, the body portion 72 may be formed of one or more of titanium, ceramic, or any other suitable biocompatible material.

[0074] Figure 4B It shows that it can include and Figure 1 A conceptual diagram of another component, the IMD 10B, which is basically similar to the IMD 10. Besides... Figures 1 to 3 In addition to the components shown in the image, Figure 4B The example of the IMD 10B shown may also include a wafer-level insulating cover 76, which helps isolate electrical signals transmitted between electrodes 16A-16D and processing circuitry 50. In some examples, the insulating cover 76 may be positioned over an open housing 15B to form a housing for components of the IMD 10B. One or more components of the IMD 10B (e.g., antenna 26, light emitter 38, processing circuitry 50, sensing circuitry 52, communication circuitry 54, switching circuitry 58, and / or power supply 64) may be formed on the underside of the insulating cover 76, for example, using flip-chip technology. The insulating cover 76 may be flipped onto the housing 15B. When flipped and placed on the housing 15B, components of the IMD 10B formed on the underside of the insulating cover 76 may be positioned within a gap 78 defined by the housing 15B.

[0075] The insulating cover 76 can be configured not to interfere with the operation of the IMD 10B. For example, one or more electrodes 16A-16D can be formed or placed above or on top of the insulating cover 76 and electrically connected to the switching circuit 58 through one or more through-holes (not shown) formed through the insulating cover 76. The insulating cover 76 can be formed of sapphire (i.e., corundum), glass, parylene, and / or any other suitable insulating material.

[0076] Figure 5 This is a block diagram illustrating an example configuration of components of an external device 12 according to one or more technologies of this disclosure. Figure 5 In the example, external device 12 includes processing circuitry 80, communication circuitry 82, storage device 84, user interface (UI) 86, and power supply 88.

[0077] In one example, processing circuitry 80 may include one or more processors configured to perform functions and / or process instructions for execution within external device 12. For example, processing circuitry 80 may be able to process instructions stored in storage device 84. Processing circuitry 80 may include, for example, a microprocessor, DSP, ASIC, FPGA, or equivalent discrete or integrated logic circuitry, or any combination of the foregoing devices or circuits. Thus, processing circuitry 80 may include any suitable structure (whether in hardware, software, firmware, or any combination thereof) to perform the functions attributed to processing circuitry 80 herein.

[0078] The communication circuit 82 may include any suitable hardware, firmware, software, or any combination thereof for communicating with another device, such as IMD 10. Under the control of the processing circuit 80, the communication circuit 82 can receive downlink telemetry from IMD 10 or another device and send uplink telemetry to it.

[0079] Storage device 84 can be configured to store information within external device 12 during operation. Storage device 84 may include a computer-readable storage medium or a computer-readable storage device. In some examples, storage device 84 includes one or more of short-term or long-term memory. Storage device 84 may include, for example, RAM, dynamic random-access memory (DRAM), static random-access memory (SRAM), magnetic disk, optical disk, flash memory, or electrically programmable memory (EPROM) or EEPROM. In some examples, storage device 84 is used to store data indicating instructions executed by processing circuitry 80. Storage device 84 can be used by software or applications running on external device 12 to temporarily store information during program execution.

[0080] The data exchanged between external device 12 and IMD 10 may include operating parameters. External device 12 may transmit data including computer-readable instructions that, when implemented by IMD 10, can control IMD 10 to change one or more operating parameters and / or export collected data. For example, processing circuitry 80 may transmit an instruction to IMD 10 requesting IMD 10 to export collected data (e.g., data corresponding to one or both of ECG and accelerometer signals) to external device 12. Furthermore, external device 12 can receive the collected data from IMD 10 and store the collected data in storage device 84. Alternatively, processing circuitry 80 may export an instruction to IMD 10 requesting IMD 10 to update the electrode combination used for stimulation or sensing.

[0081] For example, a clinician or patient 4 can interact with external device 12 through user interface 86. User interface 86 includes a display (not shown), such as an LCD or LED display or other type of screen, which processing circuitry 80 can utilize to present information related to IMD 10 (e.g., EGM signals obtained from at least one electrode or at least a combination of electrodes). Additionally, user interface 86 may include an input mechanism for receiving input from the user. The input mechanism may include any one or more of the following: buttons, a keyboard (e.g., an alphanumeric keypad), a peripheral pointing device, a touchscreen, or another input mechanism that allows the user to navigate the user interface presented by processing circuitry 80 of external device 12 and provide input. In other examples, user interface 86 may also include audio circuitry for providing audible notifications, instructions, or other sounds to patient 4, receiving voice commands from patient 4, or both. Storage device 84 may include instructions for operating user interface 86 and for managing power supply 88.

[0082] Power source 88 is configured to deliver operating power to components of external device 12. Power source 88 may include a battery and power generation circuitry for generating operating power. In some examples, the battery is rechargeable to allow for extended operation. Recharging can be achieved by electrically coupling power source 88 to a bracket or plug connected to an AC outlet. Alternatively, recharging can be achieved through near-end inductive interaction between an external charger and an inductive charging coil within external device 12. In other examples, conventional batteries (e.g., nickel-cadmium batteries or lithium-ion batteries) may be used. Alternatively, external device 12 may be directly coupled to an AC outlet for operation.

[0083] Figure 6 This is a block diagram illustrating an example system based on one or more of the techniques described herein. The example system includes an access point 90, a network 92, an external computing device (e.g., a server 94), and one or more other computing devices 100A-100N, which can be coupled to an IMD 10, an external device 12, and processing circuitry 14 via the network 92. In this example, the IMD 10 can use communication circuitry 54 to communicate with the external device 12 via a first wireless connection and with the access point 90 via a second wireless connection. Figure 6 In the example, access point 90, external device 12, server 94, and computing devices 100A-100N are interconnected and can communicate with each other via network 92.

[0084] Access point 90 may include a device connected to network 92 via any of various connections, such as dial-up, digital subscriber line (DSL), or cable modem connections. In other examples, access point 90 may be coupled to network 92 via different forms of connection, including wired or wireless connections. In some examples, access point 90 may be a user device that can be located in the same place as the patient, such as a tablet or smartphone. As described above, IMD 10 may be configured to transmit data to external device 12, such as any one or a combination of EGM signals, accelerometer signals, and tissue impedance signals. Additionally, access point 90 may (e.g., periodically or in response to commands from the patient or network 92) query IMD 10 to obtain parameter values ​​or other operational or patient data determined by processing circuitry 50 of IMD 10. Access point 90 may then transmit the obtained data to server 94 via network 92.

[0085] In some cases, server 94 can be configured to provide a secure storage site for data already collected from IMD 10 and / or external device 12. In some cases, server 94 can aggregate data in web pages or other documents for viewing by trained professionals, such as clinicians, via computing devices 100A-100N. Figure 6 One or more aspects of the system shown can be implemented using common networking technologies and functions, which may be similar to those provided by the Medtronic CareLink® network developed by Medtronic, Dublin, Ireland.

[0086] Server 94 may include processing circuitry 96. Processing circuitry 96 may include fixed-function circuitry and / or programmable processing circuitry. Processing circuitry 96 may include any one or more of a microprocessor, controller, DSP, ASIC, FPGA, or equivalent discrete or analog logic circuitry. In some examples, processing circuitry 96 may include multiple components, such as one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs, and any combination of other discrete or integrated logic circuitry. The functionality of processing circuitry 96 as described herein may be implemented as software, firmware, hardware, or any combination thereof. In some examples, as an example, processing circuitry 96 may perform one or more of the techniques described herein based on EGM signals, impedance signals, accelerometer signals, or other sensor signals received from IMD 10, or parameter values ​​determined by IMD 10 based on such signals and received from IMD 10. For example, processing circuitry may perform one or more of the techniques described herein to identify significant changes in one or more physiological parameters caused by an event, such changes being caused by medical treatment.

[0087] Server 94 may include memory 98. Memory 98 includes computer-readable instructions that, when executed by processing circuitry 96, cause IMD 10 and processing circuitry 96 to perform various functions accorded to IMD 10 and processing circuitry 96 herein. Memory 98 may include any volatile, non-volatile, magnetic, optical, or electrical medium, such as RAM, ROM, NVRAM, EEPROM, flash memory, or any other digital medium.

[0088] In some examples, one or more of computing devices 100A-100N (e.g., device 100A) may be a tablet computer or other smart device located with a clinician, through which the clinician can program the IMD 10, receive alerts from it, and / or query it. For example, the clinician can access data via device 100A corresponding to any one or combination of EGM signals, accelerometer signals, impedance signals, and other types of signals collected by the IMD 10, or parameter values ​​determined by the IMD 10 based on such signals (e.g., when patient 4 is between clinician visits) to check the status of the medical condition. In some examples, the clinician can input medical intervention instructions for patient 4 into an app on device 100A, based, for example, on the status of the patient's condition determined by the IMD 10, external device 12, processing circuitry 14, or any combination thereof, or on other patient data known to the clinician. Device 100A can then transmit medical intervention instructions to another computing device 100A-100N (e.g., device 100B) located with patient 4 or patient 4's caregiver. For example, such medical intervention instructions may include instructions to change medication dosage, timing, or selection, to schedule a clinician appointment, or to seek medical assistance. In a further example, device 100B can generate an alert for patient 4 based on the status of patient 4's medical condition determined by IMD 10, which could enable patient 4 to proactively seek medical assistance before receiving medical intervention instructions. In this way, patient 4 can be authorized to take action as needed to address his or her medical condition, thereby helping to improve patient 4's clinical outcomes.

[0089] Figure 7Figure 700 illustrates a sequence of parameter values ​​720A-720K and a first set of differences 740A-740C according to one or more techniques described herein. The sequence of parameter values ​​720A-720K (collectively referred to as "parameter values ​​720") includes a first set of parameter values ​​722 and a second set of parameter values ​​724. Additionally, Figure 700 illustrates a reference parameter value 732, a target parameter value 734, an increment value 736, and the first differences 740A-740C (collectively referred to as "first differences 740").

[0090] In some examples, IMD 10 may collect parameter value sequence 720 at a predetermined frequency. For example, IMD 10 may collect one parameter value of parameter value sequence 720 per day (e.g., a 24-hour time interval can separate the parameter value of parameter value sequence 720 from each corresponding consecutive parameter value of parameter value sequence 720). In other words, 24 hours may have elapsed between the time IMD 10 measures parameter value 720A and the time IMD 10 measures parameter value 720B, between the time IMD 10 measures parameter value 720B and the time IMD 10 measures parameter value 720C, between the time IMD 10 measures parameter value 720C and the time IMD 10 measures parameter value 720D, and so on. However, it is not required that IMD 10 collect parameter value 720 at a frequency of one parameter value per day. IMD 10 may collect parameter value 720 at any frequency (e.g., one parameter value per hour, one parameter value every other day, or one parameter value per minute). Additionally, in some examples, the measurement of a parameter over a period of time (e.g., a day) can represent multiple values ​​determined during that period, such as the mean, median, or other statistical representation of the values ​​determined during that period. As an example, each parameter value in a sequence of parameter values ​​can represent the daily average of the parameter. In other examples, each parameter value in a sequence of parameter values ​​can represent the first parameter value measured within a given time period or the last parameter value measured within a given time period. In some examples, the resolution of periodic measurements can be changed automatically or manually from daily to hourly or minutely, based on data from previous measurements or interventions received by the patient.

[0091] Processing circuit 14 can determine whether the parameter value sequence 720 indicates that patient 4 has improved or worsened in response to a treatment plan delivered to patient 4 during a period when parameter value sequence 720 is collected by IMD 10. In some examples, the start time of the treatment plan is closer to the time when parameter value 720E is collected by IMD 10 than the corresponding time for any other parameter value in parameter value sequence 720E. For example, the treatment plan may begin on the same day that parameter value 720E is collected by IMD 10. In some cases, processing circuit 14 can receive data indicating the time when the treatment plan begins. Subsequently, processing circuit 14 can determine that parameter value 720E of parameter value sequence 720 represents the parameter value closest to the time when the treatment plan begins.

[0092] To determine whether patient 4 is experiencing improvement or worsening of one or more conditions and / or symptoms in response to the treatment plan, processing circuit 14 can determine whether the parameter value sequence 720 has changed significantly from a period before the start of the treatment plan to a period after the start of the treatment plan and / or a period after the end of the treatment plan. Processing circuit 14 can select a first set of parameter values ​​722 and a second set of parameter values ​​724. For example... Figure 7 As shown, the processing circuit 14 can select a first set of parameter values ​​722 including parameter values ​​720A, 720B, 720C, and 720D, each of which is collected by the IMD 10 before parameter value 720E corresponding to the start of the treatment plan. Additionally, the processing circuit 14 can select a second set of parameter values ​​724 including parameter values ​​720I, 720J, and 720K, each of which is collected by the IMD 10 after parameter value 720E corresponding to the start of the treatment plan. In this way, the processing circuit 14 can determine whether a clinically significant change can be detected from the first set of parameter values ​​722 to the second set of parameter values ​​722, the clinically significant change indicating whether the patient 4 is experiencing improvement or deterioration.

[0093] For example, processing circuit 14 can determine reference parameter value 732 based on parameter value sequence 720. In some cases, processing circuit 14 can calculate reference parameter value 732 as the mean of a first set of parameter values ​​722. In some cases, processing circuit 14 can calculate reference parameter value 732 as the median of the first set of parameter values ​​722. In some cases, processing circuit 14 can calculate reference parameter value 732 as any statistical representation of the first set of parameter values ​​722. In this way, reference parameter value 732 can represent a baseline of the corresponding parameter tracked by parameter value sequence 720 while patient 4 is experiencing one or more conditions and before patient 4 receives treatment. In some cases, processing circuit 14 can receive information including user selection of reference parameter value 732. In some examples, processing circuit 14 receives information indicating the time corresponding to an event (e.g., the start time of a treatment plan). Furthermore, processing circuit 14 can select the parameter value that is temporally closest to the reference time as the reference parameter value. In some examples, the processing circuit 14 may output a sequence of parameter values ​​720 for display by a user interface, and further, the processing circuit 14 may receive information including the user's selection of a reference parameter value 732.

[0094] In some examples, to determine whether patient 4 is experiencing an improvement or deterioration in their medical condition, processing circuit 14 can identify a target parameter value 734 and determine whether the sequence of parameter values ​​720 significantly tends to be closer to the target parameter value 734 over a period of time after the start of the treatment plan applied to patient 4, compared to a period of time before the start of the treatment plan. In some cases, processing circuit 14 can determine the target parameter value 734 based on a reference parameter value 732. For example, processing circuit 14 can calculate the target parameter value 734 by subtracting an increment value 736 from the reference parameter value 732. In some examples, processing circuit 14 can calculate the target parameter value 734 by determining the product of the reference parameter value 732 and a predetermined score, and then determine the increment value 736 by subtracting the target parameter value 734 from the reference parameter value 732. In some examples, processing circuit 14 receives information including the target parameter value 734. For example, processing circuit 14 can output the sequence of parameter values ​​720 for display by a user interface, and further, processing circuit 14 can receive information including the user's selection of the target parameter value 734.

[0095] In one or more examples where the processing circuit 14 calculates the target parameter value 734 by subtracting the increment value 736 from the reference parameter value 732, the increment value 736 may represent a different predetermined value corresponding to each parameter. For example, when parameter value 720 represents subcutaneous impedance, increment value 736 can be in the range of 50 ohms (Ω) to 300 Ω (e.g., 250 Ω); when parameter value 720 represents respiratory rate, increment value 736 can be in the range of 1 breath per minute to 5 breaths per minute (e.g., 3 breaths per minute); when parameter value 720 represents nocturnal heart rate, increment value 736 can be in the range of 1 heartbeat per minute to 7 heartbeats per minute (e.g., 5 heartbeats per minute); when parameter value 720 represents ventricular rate during atrial fibrillation, increment value 736 can be in the range of 20 heartbeats per minute to 80 heartbeats per minute (e.g., 60 heartbeats per minute); and when parameter value 720 represents atrial fibrillation load, increment value 736 can be in the range of 0.5 hours to 3 hours (e.g., 2 hours).

[0096] Processing circuit 14 can determine whether patient 4 is experiencing improvement or deterioration of medical condition or physiological parameters based on parameter value sequence 720 (e.g., a first set of parameter values ​​722 and a second set of parameter values ​​724), reference parameter value 732, and target parameter value 734. In some examples, processing circuit 14 selects the second set of parameter values ​​724 based on the time when the treatment plan begins. For example, processing circuit 14 can select the second set of parameter values ​​724 to include parameter value 720I collected by IMD 10 four days after parameter value 720E, parameter value 720J collected by IMD 10 five days after parameter value 720E, and parameter value 720K collected by IMD 10 six days after parameter value 720E. Thus, three parameter values ​​(i.e., parameter value 720F, parameter value 720G, and parameter value 720H) separate the parameter value 720E corresponding to the start of the treatment plan from the second set of parameter values ​​724. The selection of parameter values ​​720I, 720J, and 720K as the second set of parameter values ​​724 by the processing circuit 14 can be beneficial, as this allows for a time gap between the start of the treatment plan and the second set of parameter values ​​724 used by the processing circuit 14 to determine whether the treatment plan improves or worsens the patient 4's medical condition or physiological parameters.

[0097] In some examples, processing circuit 14 can calculate parameter change values ​​based on a first set of parameter values ​​732 and a second set of parameter values ​​734. Additionally, processing circuit 14 can determine whether the parameter change values ​​indicate that one or more conditions and / or one or more symptoms of patient 4 have improved or worsened. In some cases, processing circuit 14 can use Equation 1 to calculate parameter change values.

[0098]

[0099] exist Figure 7 In the example, the value Δ x This indicates an increment of 736. x 5 indicates a difference of 740A, value x 6 represents the difference 740B, and the value... x 7 indicates a difference of 740C.

[0100] In some examples, processing circuitry 14 can determine whether the set of parameter values ​​720 indicates improvement or deterioration in patient 4 by comparing the parameter change value with a threshold parameter change value. If the parameter change value is greater than the threshold parameter change value, processing circuitry 14 can determine that the set of parameter values ​​720 indicates improvement or deterioration in patient 4, and if the parameter change value is not greater than the threshold parameter change value, processing circuitry 14 can determine that the set of parameter values ​​720 does not indicate improvement or deterioration in patient 4. In some examples, the threshold parameter change value is in the range of 0.5 to 0.9 (e.g., 0.7), but this is not required. The threshold parameter change value can include any value or range of values.

[0101] In some examples, processing circuit 14 can determine whether patient 4 has improved or deteriorated by determining whether more than one set of parameter values ​​corresponding to more than one parameter indicates an improvement or deterioration in patient 4's medical condition or physiological parameters. For example, IMD 10 can collect a set of parameter values ​​corresponding to each of patient 4's subcutaneous impedance, respiratory rate, heart rate, AF load, ventricular rate during AF, or any combination thereof. Processing circuit 14 can calculate the parameter change value corresponding to each parameter in the set and compare each corresponding parameter change value to a threshold parameter change value. Based on multiple parameter change values ​​corresponding to a parameter being greater than the threshold parameter change value, processing circuit 14 can determine whether patient 4's medical condition has improved or deteriorated.

[0102] In some examples, the first set of parameter values ​​722 and the second set of parameter values ​​724 are fixed to four and three parameter values, respectively, but this is not required. The first set of parameter values ​​722 and the second set of parameter values ​​724 can include any number of parameter values. In some examples, the last parameter value of the first set of parameter values ​​722 is fixed to the last parameter value collected by IMD 10 before the parameter value corresponding to the start of the treatment plan (e.g., parameter value 720E), but this is not required. The last parameter value of the first set of parameter values ​​722 can be any parameter value collected by IMD 10 before the parameter value corresponding to the start of the treatment plan. In some examples, the processing circuit 14 can reverse-select the first set of parameter values ​​722 from the last parameter value of the first set of parameter values ​​722. The processing circuit 14 can select the second set of parameter values ​​724 to include any set of parameter values ​​720 collected by IMD 10 after the start of the treatment plan. In the example where the second set of parameter values ​​724 includes three parameter values, the processing circuit 14 can select the last parameter value of the second set of parameter values ​​724 as a parameter value that follows a maximum of three parameters after the parameter value corresponding to the start of the treatment plan. Figure 7 In the example, the processing circuit 14 selects the last parameter value of the second set of parameter values ​​724 as the parameter value six parameters after the parameter value corresponding to the start of the treatment plan.

[0103] Figure 8 Figure 800 shows a sequence of parameter values ​​820A-820K and a second set of differences 842A-842C according to one or more techniques described herein. The sequence of parameter values ​​820A-820K (collectively referred to as "parameter values ​​820") includes a first set of parameter values ​​822 and a second set of parameter values ​​824. Additionally, Figure 800 shows a reference parameter value 832, a target parameter value 834, an increment value 836, and a second difference 842A-842C (collectively referred to as "difference 842"). Figure 8 Can be with Figure 7 They are basically the same, except that the second set of difference values ​​842 represents the difference between the reference parameter value 832 and the corresponding parameter value in the second set of parameter values ​​824. Figure 7 The first set of differences 740 represents the difference between the target parameter value 734 and the corresponding parameter value of the second set of parameters 724.

[0104] In some examples, processing circuit 14 can calculate parameter change values ​​based on a first set of parameter values ​​832 and a second set of parameter values ​​834. Additionally, processing circuit 14 can determine whether the parameter change values ​​indicate that one or more conditions and / or one or more symptoms of patient 4 have improved or worsened. In some cases, processing circuit 14 can use Equation 2 to calculate parameter change values.

[0105]

[0106] exist Figure 8 In the example, the value Δ x This indicates an increment of 836, a value... X 5 represents the difference 842A, value X 6 represents the difference of 842B, and the value... X 7 represents the difference 842C.

[0107] Figure 9 This is a graph 900 showing a sequence of impedance parameter values ​​920A-920N measured by an IMD 10 over a period of time according to one or more techniques described herein. The sequence of impedance parameter values ​​920A-920N (collectively referred to as "impedance parameter values ​​920") includes a first parameter value group 922 and a second parameter value group 924.

[0108] Each impedance parameter value of impedance parameter 920 can be recorded by IMD 10 on the corresponding day of day 912. For example, IMD 10 can record impedance parameter value 920A on the first day, impedance parameter value 920B on the second day, impedance parameter value 920C on the third day, and so on. In some examples, each impedance parameter value of impedance parameter 920 can be recorded at the same time each day. That is, any given impedance parameter value 920 can be recorded 24 hours after the consecutive impedance parameter values ​​in impedance parameter value 920. In some examples, impedance parameter value 920 can be recorded by IMD 10 at intervals other than once a day (e.g., once per hour, twice per hour, twice a day, once every two days, or any other interval).

[0109] In some examples, the trigger event may occur near the time when IMD 10 collects the impedance parameter value 920G. Processing circuitry 14 may determine that impedance parameter value 920G is closer to the trigger event than any other impedance parameter value of impedance parameter value 920. Processing circuitry 14 may receive a timestamp indicating the time when the trigger event occurred. For example, the trigger event may represent a user instruction to start a treatment plan or change a treatment plan. Alternatively, the trigger event may represent the time when processing circuitry 14 determines that patient 4 is at high risk of experiencing a condition (e.g., at high risk of experiencing heart failure). For example, IMD 110 may calculate a heart failure risk score corresponding to patient 4. If the heart failure risk score increases above a threshold heart failure risk score, processing circuitry 14 may trigger the trigger event and select impedance parameter value 920G as the parameter value closest to the time when the heart failure risk score increases above the threshold heart failure risk score.

[0110] In some examples, processing circuitry 14 may select a first set of parameter values ​​922 and a second set of parameter values ​​924 from impedance parameter values ​​920 in response to determining that impedance parameter value 920G corresponds to a trigger event. For example, processing circuitry 14 may select the first set of parameter values ​​922 to include four impedance parameter values ​​(e.g., impedance parameter values ​​920C-920F) preceding the impedance parameter value 920G corresponding to the trigger event. In this way, the first set of parameter values ​​922 may represent “reference” parameter values ​​indicating the baseline impedance prior to the occurrence of the reference event. Processing circuitry 14 may select the second set of parameter values ​​924 to include three consecutive impedance parameter values ​​ending with seven parameter values ​​collected by IMD 10 after the end of the first set of parameter values ​​922. In other words, processing circuitry 14 may select the second set of parameter values ​​920K to 920M to include impedance parameter values ​​920K to 920M. The second set of parameter values ​​924 may represent “evaluation” parameter values ​​that processing circuitry 14 may compare with the reference parameter values ​​of the first set of parameter values ​​922.

[0111] In some examples, processing circuitry 14 selects a first set of parameter values ​​922 and a second set of parameter values ​​924 based on the current number of days since the analysis of impedance parameter value 920. For example, when the current number of days represents the number of days since the IMD 10 measured impedance parameter value 920M, processing circuitry 14 may select the second set of parameter values ​​924 to include a consecutive set of parameter values ​​ending with the impedance parameter value collected by the IMD 10 on the current number of days. In the example of Figure 900, processing circuitry 14 selects the second set of parameter values ​​920K to 920M, where impedance parameter value 920M was collected by the IMD 10 on the current number of days. Processing circuitry 14 may select the first set of parameter values ​​922 to include a consecutive set of parameter values ​​ending several days (e.g., 7 days) prior to the current number of days. In the example of Figure 900, the processing circuit 14 can select the first parameter value group 922 to include impedance parameter values ​​920C to 920F, wherein the impedance parameter value 920F is collected by IMD 10 seven days prior to the current day.

[0112] Selecting the first parameter value group 922 and the second parameter value group 924 based on the current number of days allows the processing circuit 14 to determine whether an impedance change has occurred from the baseline impedance one week prior to the current number of days to the impedance immediately preceding the current number of days. In this way, the first parameter value group 922 and the second parameter value group 924 can represent a rolling window of parameter values ​​that change based on the current number of days. For example, as the current number progresses from the day when impedance parameter value 920M was collected at IMD 10 to the day when impedance parameter value 920N was collected at IMD 10, the processing circuit 14 can update the first parameter value group 922 to include impedance parameter values ​​920D to 920G, and the processing circuit 14 can update the second parameter value group 924 to include impedance parameter values ​​920L to 920N.

[0113] In the case of impedance, an increase in the impedance parameter value in response to a triggering event can indicate a significant improvement in the patient's condition. For parameters other than impedance (e.g., respiratory rate, nocturnal heart rate, and AF load), a decrease in the parameter value in response to a triggering event can indicate a significant improvement in the patient's condition.

[0114] Figure 10 This is a graph 1000 that shows the impedance parameter value sequence 1020A-1020N, ​​baseline impedance 1030, and evaluation impedance 1032 according to one or more techniques described herein. The impedance parameter value sequence 1020A-1020N (collectively referred to as "impedance parameter values ​​1020") includes a first parameter value group 1022 and a second parameter value group 1024. Figure 10 Chart 1000 can be compared with Figure 9 The chart is basically the same as the one in chart 900, except that chart 1000 includes baseline impedance 1030, evaluation impedance 1032 and impedance difference 1034.

[0115] In some examples, processing circuit 14 can calculate baseline impedance 1030 by calculating the mean of the first parameter value group 1022, determining the median of the first parameter value group 1022, or determining another statistical representation of the first parameter value group 1022. Processing circuit 14 can calculate assessment impedance 1032 by calculating the mean of the second parameter value group 1024, determining the median of the second parameter value group 1024, or determining another statistical representation of the second parameter value group 1024. Subsequently, processing circuit 14 can calculate the difference 1034 between baseline impedance 1030 and assessment impedance 1032. If the difference 1034 is greater than a threshold impedance difference, processing circuit 14 can determine whether the patient's condition has improved. In one example, the threshold impedance difference is 50 ohms (Ω), meaning that assessment impedance 1032 must be at least 50 Ω higher than baseline impedance 1030 for processing circuit 14 to determine that the patient's condition has improved.

[0116] Figure 11This is a graph 1100 showing the impedance parameter value sequence 1120A-1120N according to one or more techniques described herein. The impedance parameter value sequence 1120A-1120N (collectively referred to as "impedance parameter values ​​1120") includes a first parameter value group 1122 and a second parameter value group 1124.

[0117] Each impedance parameter value of impedance parameter 1120 can be recorded by IMD 10 on the corresponding day of day 1112. For example, IMD 10 can record impedance parameter value 1120A on the first day, impedance parameter value 1120B on the second day, impedance parameter value 1120C on the third day, and so on. In some examples, each impedance parameter value of impedance parameter 1120 can be recorded at the same time each day. That is, any given impedance parameter value of impedance parameter 1120 can be recorded 24 hours after consecutive impedance parameter values ​​in impedance parameter 1120. In some examples, impedance parameter value 1120 can be recorded by IMD 10 at intervals other than once a day (e.g., once per hour, twice per hour, twice a day, once every two days, or any other interval).

[0118] Chart 1100 can be compared with Figure 9 The diagram 900 is essentially the same, except that the first parameter value group 1122 and the second parameter value group 1124 are closer together. In some examples, the processing circuit 14 can select the first parameter value group 1122 and the second parameter value group 1124 based on user input. For example, the processing circuit 14 can receive user input indicating the number of days after which intervention begins when collecting impedance parameter values ​​1120H at IMD 10. Subsequently, the processing circuit 14 can select the first parameter value group 1122 and the second parameter value group 1124 based on the selected start date.

[0119] Figure 12 This is a graph 1200 showing parametric curves 1238 regarding the deterioration threshold 1242 and the improvement threshold 1246 according to one or more techniques described herein. Parametric curve 1238 represents parameters 1210 measured by IMD 110 over multiple days 1212. (As...) Figure 12 As shown, parameter curve 1238 increases from day 0 to day 6.

[0120] The deterioration threshold 1242 represents the threshold at which the processing circuit 14 determines whether parameter 1210 indicates a deterioration in the patient's condition. For example, the baseline parameter value 1244 may represent the baseline value of parameter 1210. In some examples, the baseline parameter value 1244 may represent the mean of a group of parameter values ​​prior to the triggering event. In some examples, the baseline parameter value 1244 may represent the value of parameter 1210 at the time the triggering event occurs. If the parameter decreases below the deterioration threshold 1242, the processing circuit 14 can determine that the parameter indicates a deterioration in the patient's condition. Alternatively, if the parameter increases above the improvement threshold 1246, the processing circuit 14 can determine that the parameter indicates an improvement in the patient's condition. For example, as shown in graph 1200, parameter curve 1238 has a value of 1252 on day 5 and a value of 1254 on day 6. Value 1252 is below the improvement threshold 1246, and value 1254 is above the improvement threshold 1246. Therefore, the processing circuit 14 can determine that parameter curve 1238 indicates an improvement in the patient's condition on day 6.

[0121] Although the magnitudes of the deterioration threshold 1242 and the improvement threshold 122 are shown to be substantially the same, in some examples, the magnitudes of the deterioration threshold 1242 and the improvement threshold 1246 may differ. That is, in some examples, the difference between the baseline parameter value 1244 and the deterioration threshold 1242 may be different from the difference between the baseline parameter value 1244 and the improvement threshold 1246. In other examples, the difference between the baseline parameter value 1244 and the deterioration threshold 1242 may be the same as the difference between the baseline parameter value 1244 and the improvement threshold 1246.

[0122] Figure 13 This is a flowchart illustrating an example operation of determining whether one or more of a patient's symptoms or physiological parameters have improved or worsened based on a user's selection of a reference time, according to one or more techniques of this disclosure. About Figures 1 to 6 The IMD 10, external device 12, and processing circuitry 14 are used to describe this. Figure 13 .However, Figure 13 The technology can be implemented by different components of the IMD 10, external device 12, and processing circuitry 14, or by an additional or alternative medical device system. Processing circuitry 14 in... Figure 1 The processing circuitry is conceptually shown separately from IMD 10 and external device 12, but may be the processing circuitry of IMD 10 and / or external device 12. Typically, the techniques disclosed herein can be performed by the processing circuitry 14 of one or more devices in the system, such as one or more devices including sensors that provide signals, or processing circuitry of one or more devices that do not include sensors but still use the techniques described herein to analyze signals. For example, another external device ( Figure 1(Not depicted) may include at least a portion of processing circuitry 14, the other external device being configured to communicate remotely with IMD 10 and / or external device 12 via a network.

[0123] IMD 10 generates a signal (1302) indicating parameters of patient 4. In some examples, the parameters may include patient 4's subcutaneous impedance, patient 4's respiratory rate, patient 4's heart rate, patient 4's AF load, or patient 4's ventricular rate during AF. Processing circuitry 14 receives a portion (1304) of a signal including multiple parameter values. In some examples, the multiple parameter values ​​may represent a sequence of parameter values ​​collected by IMD 10 at a predetermined frequency (e.g., one parameter value per day, one parameter value per hour, or any other frequency).

[0124] Processing circuit 14 can receive data (1306) indicating a user's selection or indication of a reference time. In some examples, the reference time may represent the start time of the treatment plan applied to patient 4. Processing circuit 14 can receive data indicating the user's selection from IMD 10, external device 12, or another external device. Processing circuit 14 can identify a reference parameter value based on a first set of parameter values ​​from a plurality of parameter values ​​(1308). In some examples, the first set of parameter values ​​is collected by IMD 10 prior to the reference time. In some examples, processing circuit 14 can calculate the reference parameter value as the mean or median of the first set of parameter values. Processing circuit 14 can calculate a parameter change value based on a second set of parameter values ​​from a plurality of parameter values ​​and based on the reference parameter value (1310). Subsequently, processing circuit 14 can determine whether the patient has improved or worsened based on the parameter change value (1312).

[0125] Figure 14 This is a flowchart illustrating an example operation for determining, based on a scrolling window, whether one or more of a patient's symptoms or physiological parameters have improved or worsened, according to one or more techniques of this disclosure. About Figures 1 to 6 The IMD 10, external device 12, and processing circuitry 14 are used to describe this. Figure 14 .However, Figure 14 The technology can be implemented by different components of the IMD 10, external device 12, and processing circuitry 14, or by an additional or alternative medical device system. Processing circuitry 14 in... Figure 1The processing circuitry is conceptually shown separately from IMD 10 and external device 12, but may be the processing circuitry of IMD 10 and / or external device 12. Typically, the techniques disclosed herein can be performed by the processing circuitry 14 of one or more devices in the system, such as one or more devices including sensors that provide signals, or processing circuitry of one or more devices that do not include sensors but still use the techniques described herein to analyze signals. For example, another external device ( Figure 1 (Not depicted) may include at least a portion of processing circuitry 14, the other external device being configured to communicate remotely with IMD 10 and / or external device 12 via a network.

[0126] IMD 10 generates a signal (1402) indicating parameters of patient 4. In some examples, the parameters may include patient 4's subcutaneous impedance, patient 4's respiratory rate, patient 4's heart rate, patient 4's AF load, or patient 4's ventricular rate during AF. Processing circuitry 14 receives a portion (1404) of a signal including multiple parameter values. In some examples, the multiple parameter values ​​may represent a sequence of parameter values ​​collected by IMD 10 at a predetermined frequency (e.g., one parameter value per day, one parameter value per hour, or any other frequency).

[0127] Processing circuit 14 can identify a reference parameter value based on a first set of parameter values ​​from a plurality of parameter values ​​(1406). In some examples, processing circuit 14 can calculate the reference parameter value as the mean, median, or another statistical representation of the first set of parameter values. Processing circuit 14 can calculate a parameter change value based on a second set of parameter values ​​from a plurality of parameter values ​​and based on the reference parameter value (1408). In some examples, processing circuit 14 can select the first set of parameter values ​​and the second set of parameter values ​​based on a scrolling window. That is, the first set of parameter values ​​and the second set of parameter values ​​are updated over time, and a predetermined number of parameter values ​​separate the first set of parameter values ​​from the second set of parameter values. Subsequently, processing circuit 14 can determine whether the patient has improved or worsened based on the parameter change value (1410).

[0128] The techniques described in this disclosure can be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, aspects of the techniques can be implemented within one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic QRS circuits, and any combination of such components, implemented in external devices such as physician or patient programmers, stimulators, or other devices. The terms "processor" and "processing circuitry" generally refer to any of the aforementioned logic circuits (alone or in combination with other logic circuits), or any other equivalent circuit (alone or in combination with other digital or analog circuits).

[0129] For aspects implemented in software, at least some of the functions belonging to the systems and devices described in this disclosure can be implemented as instructions on a computer-readable storage medium, such as RAM, DRAM, SRAM, magnetic disk, optical disk, flash memory, or EPROM or EEPROM. The instructions can be executed to support one or more aspects of the functions described in this disclosure.

[0130] Furthermore, in some aspects, the functionality described herein can be provided within dedicated hardware and / or software modules. Describing different features as modules or units is intended to highlight functional differences and does not imply that such modules or units must be implemented by different hardware or software components. Rather, the functionality associated with one or more modules or units can be performed by different hardware or software components, or integrated within common or different hardware or software components. Additionally, the technology can be fully implemented in one or more circuit or logic elements. The technology disclosed herein can be implemented in a wide range of devices or apparatuses, including IMDs, external programmers, combinations of IMDs and external programmers, integrated circuits (ICs) or IC sets, and / or discrete circuitry residing in IMDs and / or external programmers.

Claims

1. A medical device system, comprising: A medical device, the medical device including one or more sensors configured to generate signals indicative of parameters for a patient; as well as Processing circuit, the processing circuit being configured to: Receive data instructing the user to select a reference time, wherein the reference time represents the start time of the treatment plan applied to the patient; Multiple parameter values ​​of the parameter are determined based on a portion of the signal corresponding to a period of time including the reference time, wherein each of the multiple parameter values ​​represents a measurement of the parameter within a corresponding time interval during the period of time; The reference parameter value is identified based on the first set of parameter values ​​that occurred before the reference time among the plurality of parameter values; The parameter change value is calculated based on a second set of parameter values ​​occurring after the reference time from among the plurality of parameter values; and based on the reference parameter values. Based on the parameter change value, it is determined whether the patient has improved or worsened in response to the treatment plan administered to the patient. In order to calculate the change in the parameter, the processing circuit is configured as follows: Identify a set of differences, wherein each difference in the set of differences represents the difference between a corresponding parameter value of the second set of parameter values ​​and the reference parameter value; and The parameter change is calculated based on the set of differences. In order to calculate the parameter change value based on the set of differences, the processing circuit is configured as follows: Determine the sum of the set of differences; Determine the incremental value representing the difference between the reference parameter value and the target parameter value; and The parameter change is calculated by determining the ratio of the sum of the set of differences to the increment value.

2. The medical device system as described in claim 1, wherein, In order to identify the reference parameter value, the processing circuit is configured to calculate the reference parameter value as the mean of the first set of parameter values.

3. The medical device system as described in claim 1, wherein, In order to identify the reference parameter value, the processing circuit is configured to calculate the reference parameter value as the median of the first set of parameter values ​​or another statistical representation of the first set of parameter values.

4. The medical device system as described in claim 1, wherein, To determine whether the patient has experienced the improvement or the deterioration, the processing circuit is configured to: The parameter change value is compared with the first threshold parameter change value and the second threshold parameter change value; When the change in the parameter is greater than the change in the first threshold parameter, it is determined that the patient has experienced the improvement. When the change in the parameter is less than the change in the second threshold parameter, it is determined that the patient has experienced the deterioration. as well as When the change in the parameter is greater than or equal to the change in the second threshold parameter and less than or equal to the change in the first threshold parameter, it is determined that the patient has neither experienced the improvement nor the deterioration.

5. The medical device system as described in claim 4, wherein, The change in the first threshold parameter is in the range of 0.5 to 0.

9.

6. The medical device system as described in claim 5, wherein, The first threshold parameter was changed by 0.

7.

7. The medical device system as claimed in claim 1, wherein, The plurality of parameter values ​​represent a sequence of parameter values, and the processing circuit is configured to select the second set of parameter values ​​as consecutive parameter values ​​in the sequence of parameter values ​​starting from a predetermined number of parameter values ​​after the reference time.

8. The medical device system as claimed in claim 7, wherein, The second set of parameter values ​​includes three consecutive parameter values, wherein the three parameter values ​​separate the second set of parameter values ​​from the reference time.

9. The medical device system as claimed in claim 1, wherein, Each of the plurality of parameter values ​​corresponds to a specific time interval in the time interval sequence.

10. The medical device system of claim 9, wherein, Each of the plurality of parameter values ​​represents a set of parameter value components collected during the corresponding time interval, and wherein, in order to determine the plurality of parameter values, the processing circuit is configured to calculate each of the plurality of parameter values ​​based on the corresponding set of parameter value components.

11. The medical device system of claim 9, wherein, The duration of each time interval in the time interval sequence is defined as one day.

12. A medical device system, comprising: Device for generating signals that indicate parameters of a patient; A device for receiving data instructing a user to select a reference time, wherein the reference time represents the time at which a treatment plan is administered to a patient begins; A means for determining a plurality of parameter values ​​of the parameter based on a portion of the signal corresponding to a period of time including the reference time, wherein each of the plurality of parameter values ​​represents a measurement of the parameter within a corresponding time interval during the period of time; A means for identifying a reference parameter value based on a first set of parameter values ​​that occurred before the reference time among the plurality of parameter values; A means for calculating a parameter change value based on a second set of parameter values ​​occurring after the reference time from among the plurality of parameter values; and based on the reference parameter values; and A device for determining, based on the change in the parameter value, whether the patient has improved or worsened in response to the treatment plan administered to the patient. The device for calculating the change value of the parameter further includes: A means for identifying a set of differences, wherein each difference in the set of differences represents the difference between a corresponding parameter value of the second set of parameter values ​​and the reference parameter value; and A means for calculating the change in the parameter based on the set of differences. The apparatus for calculating the parameter change value based on the set of differences further includes: A means for determining the sum of the set of differences; A means for determining an incremental value representing the difference between the reference parameter value and the target parameter value; and A means for calculating the parameter change value by determining the ratio of the sum of the set of differences to the increment value.

13. A non-transitory computer-readable medium comprising instructions for causing one or more processors to: Generate signals that indicate parameters for the patient; Receive data instructing the user to select a reference time, wherein, The reference time indicates the time at which the treatment plan applied to the patient begins; Multiple parameter values ​​of the parameter are determined based on a portion of the signal corresponding to a period of time including the reference time, wherein each of the multiple parameter values ​​represents a measurement of the parameter within a corresponding time interval during the period of time; The reference parameter value is identified based on the first set of parameter values ​​that occurred before the reference time among the plurality of parameter values; The parameter change value is calculated based on a second set of parameter values ​​occurring after the reference time from among the plurality of parameter values; and based on the reference parameter values. Based on the parameter change value, it is determined whether the patient has improved or worsened in response to the treatment plan administered to the patient. In order to calculate the changed value of the parameter, the computer-readable medium includes instructions for causing one or more processors to: Identify a set of differences, wherein each difference in the set of differences represents the difference between a corresponding parameter value of the second set of parameter values ​​and the reference parameter value; and The parameter change is calculated based on the set of differences. In order to calculate the parameter change value based on the set of differences, the computer-readable medium includes instructions for causing one or more processors to: Determine the sum of the set of differences; Determine the incremental value representing the difference between the reference parameter value and the target parameter value; and The parameter change is calculated by determining the ratio of the sum of the set of differences to the increment value.

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