Prediction or detection of major adverse cardiac events by sympathetic response disruption

Abstract

The present disclosure relates to systems and techniques for determining the risk of developing a major adverse cardiac event (MACE). An example system includes processing circuitry configured to obtain one or more signals indicative of one or more respective physiological parameters and determine values for the one or more respective physiological parameters. The processing circuitry is configured to determine a slow moving average line (SMA) and a fast moving average line (FMA) for respective values of the respective one or more respective physiological parameters. The processing circuit is configured to determine that a respective difference between the respective FMA and the respective SMA satisfies a respective difference threshold. The processing circuitry is configured to, based on the respective difference satisfying the respective difference threshold, at least one of: a) set a flag indicative of a risk of MACE; or b) generating, for output, an indication of a risk of developing MACE.

Description

[0001] This application claims the benefit of U.S. Provisional Patent Application 63 / 386,581, filed on December 8, 2022, entitled "PREDICTION OR DETECTION OF MAJOR ADVERSE CARDIAC EVENTS VIA DISRUPTION IN SYMPATHETIC RESPONSE". TECHNICAL FIELD

[0002] The present disclosure relates generally to systems and, more particularly, to systems configured to monitor physiological parameters. BACKGROUND

[0003] Some types of systems can be used to monitor one or more physiological parameters of a patient. These systems can include implantable medical devices (IMDs), wearable devices, or other external devices. The systems can include sensors that sense signals associated with such physiological parameters. The systems can utilize the sensed physiological parameters to monitor the health of the patient. SUMMARY

[0004] Major adverse cardiac events (MACE) are typically detected after a person experiences symptoms and seeks medical help. Sometimes, MACE are detected incidentally when imaging a person or evaluating other conditions. For example, patients who experience a myocardial infarction (MI) episode report symptoms days or even weeks before treatment for the event. Since it has been shown that "door-to-balloon" time is critical in percutaneous coronary intervention (PCI) related to patient outcomes, early intervention is desirable to reduce the impact of both short-term and long-term infarcts. Thus, it may be desirable to determine the risk that a person may experience MACE within a time frame, which may enable earlier medical diagnosis and / or treatment and better patient outcomes. Some treatments that can be administered in response to determining that a person may be at risk of experiencing MACE include PCI, aortic valve or mitral valve replacement or repair, etc.

[0005] The system can be configured to monitor one or more physiological parameters of a person to determine the risk that the person may experience a major adverse cardiac event (MACE) within a time frame. For example, for a given physiological parameter, the system can monitor the physiological parameter of the person and determine the person-specific homeostasis of the physiological parameter by determining the slow moving average (SMA) of the physiological parameter. The system can also determine the fast moving average (FMA) of the physiological parameter. The FMA can be, for example, the average of samples of the physiological parameter over a shorter time period than the SMA. Thus, the FMA can be determined based on fewer samples of the physiological parameter than the SMA. For example, the FMA can be based on a subset of the samples of the physiological parameter on which the SMA is based. If the FMA differs from the SMA by more than (or is equal to or more than) a difference threshold, the system can generate a flag or indication indicative of the risk of the patient experiencing a MACE within the time frame for output. In some examples, if the system determines a particular combination of differences between the associated FMA and SMA of two or more physiological parameters and the differences exceed (or are equal to or exceed) their respective difference thresholds, the system can generate a flag or indication indicative of the risk of the patient experiencing a MACE within the time frame for output. As used herein, a physiological parameter is a parameter of a biological nature, as opposed to a parameter of the mechanical nature of a device (e.g., blood flow through a mechanical blood pump) or a parameter based on a parameter of the mechanical nature of a device (e.g., not these parameters).

[0006] In some examples, a system includes: a memory configured to store physiological parameters of a patient; and a processing circuit communicatively coupled to the memory, the processing circuit being configured to: obtain one or more signals indicative of one or more respective physiological parameters; determine respective values of the one or more respective physiological parameters based on the one or more signals; determine a respective slow moving average (SMA) of a first subset of the respective values of the one or more respective physiological parameters; determine a respective fast moving average (FMA) of a second subset of the respective values of the one or more respective physiological parameters; determine that a respective difference between the respective FMA and the respective SMA satisfies a respective difference threshold; and based on the respective difference satisfying the respective difference threshold, perform at least one of the following: a) set a flag indicative of the risk of a major adverse cardiac event (MACE) occurring; or b) generate an indication of the risk of a MACE occurring for output.

[0007] In some examples, a method includes: obtaining, by a processing circuit, one or more signals indicative of one or more respective physiological parameters; determining, by the processing circuit, respective values of the one or more respective physiological parameters based on the one or more signals; determining, by the processing circuit, a respective slow moving average (SMA) of a first subset of the respective values of the one or more respective physiological parameters; determining, by the processing circuit, a respective fast moving average (FMA) of a second subset of the respective values of the one or more respective physiological parameters; determining, by the processing circuit, that a respective difference between the respective FMA and the respective SMA satisfies a respective difference threshold; and based on the respective difference satisfying the respective difference threshold, performing at least one of the following: a) setting, by the processing circuit, a flag indicative of a risk of a major adverse cardiac event (MACE); or b) generating, by the processing circuit, an indication of the risk of MACE for output.

[0008] In some examples, a non-transitory computer-readable storage medium includes instructions that, when executed, cause a processing circuit to: obtain one or more signals indicative of one or more respective physiological parameters; determine respective values of the one or more respective physiological parameters based on the one or more signals; determine a respective slow moving average (SMA) of a first subset of the respective values of the one or more respective physiological parameters; determine a respective fast moving average (FMA) of a second subset of the respective values of the one or more respective physiological parameters; determine that a respective difference between the respective FMA and the respective SMA satisfies a respective difference threshold; and based on the respective difference satisfying the respective difference threshold, perform at least one of the following: a) set a flag indicative of a risk of a major adverse cardiac event (MACE); or b) generate an indication of the risk of MACE for output.

[0009] This Summary is intended to provide an overview of the subject matter described in this disclosure. This Summary is not intended to provide an exclusive or exhaustive interpretation of the systems, devices, and methods described in the following drawings and detailed description. Further details of one or more examples of the disclosure are set forth in the following drawings and detailed description. Other features, objects, and advantages will be apparent from the description, drawings, and claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 Illustrates an environment of an example medical device system incorporating a patient in accordance with one or more techniques of the disclosure.

[0011] Figure 2 is an illustration of Figure 1 an example configuration of an IMD of a medical device system in accordance with one or more techniques described herein.

[0012] Figure 3An example configuration of an IMD that illustrates one or more techniques described herein Figure 1 and Figure 2 is a functional block diagram.

[0013] Figure 4A and Figure 4B are block diagrams of two additional example IMDs that illustrate one or more techniques described herein and that can be substantially similar to Figures 1 to 3 but can include one or more additional features.

[0014] Figure 5 is a block diagram of an example configuration of components of an external device that illustrates one or more techniques of the present disclosure Figure 1 thereof.

[0015] Figure 6 is a block diagram of an example system that illustrates one or more techniques described herein, the system including an access point, a network, an external computing device (such as a server), and one or more other computing devices that can be coupled via the network to Figure 1 the IMD, the external device, and the processing circuitry of FIG. 4.

[0016] Figure 7 is a flowchart of an example MACE prediction technique that illustrates one or more aspects of the present disclosure.

[0017] Throughout the specification and drawings, like reference characters represent like elements. DETAILED DESCRIPTION

[0018] Certain devices (such as implantable medical devices (IMDs), wearable devices, or other devices) can sense and / or monitor physiological parameters of a person (such as a patient). Such physiological parameters can indicate the health state of the person.

[0019] As discussed above, MACE is typically detected after a person experiences symptoms and seeks medical help. However, depending on the nature of the MACE, the event may not exhibit symptoms or may be transient, and may not be confirmed in a clinic / hospital setting at a particular time even after symptoms appear. Thus, a system configured to sense, identify, and / or record cardiac events while a person is ambulatory can assist clinicians in guiding appropriate care.

[0020] MACE can be caused by coronary artery problems, structural problems, and / or conduction problems. Distinguishing the underlying causes of MACE can be time-consuming and expensive because each potential type of cause may require a different type of test. For example, detection of structural heart problems may require expensive or invasive echocardiography. Detection of coronary artery problems may require invasive angiography. Detection of conduction problems may require use of a 12-lead electrocardiogram. Each of these techniques may require capital equipment and / or instrumentation in a hospital or clinical setting.

[0021] Accordingly, there may be a need for a system configured to determine whether a predicted MACE is more likely due to a coronary artery problem, a structural problem, or a conduction problem. There may also be a desire for a system that can do so while a patient is ambulatory. Such a system can be used to avoid unnecessary clinical diagnostic tests or to test the most likely cause first, which can lead to faster diagnosis and / or treatment and reduce unnecessary use of clinical resources.

[0022] This disclosure describes techniques for determining the risk of a person experiencing MACE. In some examples, the techniques can determine the risk of MACE within a specified time range and / or due to a particular type of problem (e.g., a structural problem, a coronary artery problem, and / or a conduction problem). In some examples, the system can generate a flag and / or generate an indication for output, which can include an indication of the risk that a person may experience MACE, for example, within a specified time range. Such a flag or indication can provide an opportunity for early diagnosis and / or treatment of a medical problem, which can improve patient outcomes. In some examples, the flag or indication can indicate the risk of MACE within a time range (such as within x days, y hours, or between a days and b days or between c hours and d hours). In some examples, the system can output the flag or indication (e.g., via a communication circuit and / or a user interface). In this way, the patient and / or clinician can be aware of the risk of MACE and can proactively seek or administer tests and / or treatment, thereby improving patient outcomes.

[0023] Figure 1 An environment of an example medical device system 2 incorporating patient 4 in accordance with one or more techniques of this disclosure is illustrated. Although the techniques described herein are generally described in the context of an ICM, a wearable device, and / or an external device, the techniques of this disclosure can be implemented in any IMD, wearable device, or external device or combination thereof capable of sensing and / or processing one or more physiological parameters of patient 4. Example techniques can be used with an IMD 10 and / or a wearable device 6 (e.g., a wearable patch), which can communicate wirelessly with at least one of an external device 12 and Figure 1 other devices not shown. Processing circuitry 14 is in Figure 1Conceptually illustrated as separate from the IMD 10, the wearable device 6, and the external device 12, but may be the processing circuitry of the IMD 10, the wearable device 6, and / or the external device 12. Generally speaking, the techniques of the present disclosure may be performed by the processing circuitry 14 of one or more devices of the system (such as one or more devices including sensors that provide signals), or the processing circuitry of one or more devices that do not include sensors but still process signals using the techniques described herein. For example, another external device ( Figure 1 not shown in the figure) may include at least a portion of the processing circuitry 14, and the other external device is configured for remote communication with the IMD 10, the wearable device 6, and / or the external device 12 via a network.

[0024] In some examples, the IMD 10 is implanted outside the chest cavity of the patient 4 (e.g., subcutaneously implanted Figure 1 in the chest position illustrated). The IMD 10 may be positioned near the sternum at or just below the heart level of the patient 4, e.g., at least partially within the cardiac silhouette. For other medical conditions, the IMD 10 may be implanted in other suitable locations, such as an interstitial space, the abdominal cavity, the back of the arm, the wrist, etc. In some examples, the IMD 10 takes the form of a LINQ TM Insertable Cardiac Monitor (ICM) commercially available from Medtronic plc, Dublin, Ireland.

[0025] In some examples, the wearable device 6 can be removably attached to the patient 4, such as the skin of the patient 4, by an adhesive, a strap, or other attachment mechanism. For example, the wearable device 6 may take the form of a patch, a watch, a wristband, a headband, a chest strap, a face mask, a finger clip, or a ring, etc. In some examples, the wearable device 6 can be a smart device. In some examples, the wearable device 6 may be positioned near (e.g., above) the heart of the patient 4.

[0026] Clinicians sometimes diagnose patients with medical conditions based on one or more observed physiological signals collected by physiological sensors (such as electrodes, optical sensors, chemical sensors, temperature sensors, acoustic sensors, or motion sensors, etc.). In some cases, clinicians apply non-invasive sensors (e.g., wearable sensors) to patients in order to sense one or more physiological signals while the patients are having a medical appointment at a clinic. However, in some examples, physiological markers (such as those indicating that the patient 4 has a MACE risk) are rare or difficult to observe within a relatively short period of time. Therefore, in these examples, clinicians may not be able to observe the physiological markers required to diagnose patients with medical conditions or effectively treat the patients, while monitoring one or more physiological signals of the patients during the medical appointment process.

[0027] In Figure 1 the illustrated example, the IMD 10 is implanted within patient 4 to continuously record one or more physiological signals that may indicate physiological parameters of patient 4. Such physiological parameters may include, but are not limited to: 1) glucose levels and derived metrics such as time in range; 2) respiratory rate; 3) pulse oximeter parameters such as SpO2 oxygen saturation and / or perfusion index; 4) heart rate and derived metrics such as heart rate variability and / or nocturnal heart rate; 5) blood pressure and derived metrics such as pulse pressure, mean arterial pressure and / or radial artery pressure, and / or central venous pressure; 6) physiological parameters discernible from acoustic signals such as physiological parameters related to blood flow rate and / or pulse wave velocity; and / or 7) activity level. Alterations in such physiological parameters may indicate the risk of MACE occurring over a time period.

[0028] In some examples, the IMD 10 and / or the wearable device 6 includes one or more sensors configured to sense signals indicative of such physiological parameters. For example, such sensors may be configured to detect signals such that the processing circuitry 14 of, for example, the IMD 10 and / or the wearable device 6 can monitor and / or record the physiological parameters of patient 4. For example, in some examples, the IMD 10 and / or the wearable device 6 may include multiple electrodes, one or more optical sensors, accelerometers, temperature sensors, chemical sensors, light sensors, pressure sensors, audio sensors, and / or respiratory sensors. Such sensors may sense one or more physiological parameters indicative of the health state of the patient. In some examples, additional sensors may be located on other devices ( Figure 1 not shown) that may also sense the physiological parameters of patient 4.

[0029] Sensor data may be collected by various devices such as implantable therapy devices, implantable monitoring devices, wearable devices, point-of-care devices, and non-contact sensors or combinations of such sensor platforms in homes or vehicles or other areas that patients frequent. The collected sensor data may be associated with physiological parameters and related to the disease state (e.g., heart failure), comorbidities (e.g., chronic obstructive pulmonary disease (COPD), kidney disease, etc.), or potential problems (e.g., structural, coronary, or conduction) that may lead to MACE of patient 4.

[0030] The processing circuit 14 may be configured to receive, for example, sensing signals indicating physiological parameters of the patient 4 from the IMD 10 and / or the sensing circuits of the wearable device 6. In some examples, the processing circuit 14 may process one or more of the sensing signals and determine a person-specific (e.g., patient 4-specific) homeostasis of one or more biometric parameters of a person. For example, the processing circuit 14 may determine a value that varies over time associated with each of one or more physiological parameters of the patient 4. The processing circuit 14 may determine the SMA of the value of a given physiological parameter. The SMA may be an average, median, or mode of the values of the biometric parameter calculated over a period of time (the SMA period). In some examples, the SMA period may be a range measured in seconds, hours, days, months, or years. In some examples, when determining the SMA for more than one physiological parameter, the SMA period for each of these physiological parameters may be the same. In other examples, when determining the SMA for more than one physiological parameter, the SMA period for at least one of these physiological parameters may be different from the SMA period for at least one of the other physiological parameters.

[0031] The processing circuit 14 may also determine the FMA of the value of a given physiological parameter. In some examples, the FMA may be an average, median, or mode of the values of the biometric parameter calculated over a period of time (the FMA period). The FMA period may be shorter than the SMA period for the same physiological parameter. In some examples, the FMA period may be a range measured in seconds, hours, days, months, or years. In some examples, when determining the FMA for more than one physiological parameter, the FMA period for each of these physiological parameters may be the same. In other examples, when determining the FMA for more than one physiological parameter, the FMA period for at least one of these physiological parameters may be different from the FMA period for at least one of the other physiological parameters.

[0032] For each physiological parameter for which the processing circuit 14 determines the difference between the SMA and the corresponding FMA, the difference threshold may be specific to the physiological parameter. In other words, the difference threshold for one physiological parameter may be different from the difference threshold for another physiological parameter. In some examples, any one of the difference thresholds may be the same as or different from any other difference threshold. In some examples, the difference threshold may be programmable. For example, a clinician may program a given difference threshold. For example, if a clinician is more concerned about acute conditions, the clinician may set a relatively high difference threshold compared to the situation where the clinician is concerned about chronic symptoms, for which the clinician may set a relatively low difference threshold.

[0033] In some examples, the programmability of the difference threshold can be limited to a fixed value (e.g., a value that does not change based on SMA or FMA, such as the standard deviation of SMA or FMA).

[0034] When processing circuit 14 determines that the FMA relative to the SMA for a given physiological parameter varies beyond an associated difference threshold, processing circuit 14 may determine that there is a risk that patient 4 may experience MACE, for example, within a time frame. In some examples, processing circuit 14 may determine that such a MACE risk is significant based on the FMA relative to the SMA varying beyond the associated difference threshold. Significant does not necessarily mean that the risk is greater than a certain percentage, but may mean that the risk is meaningful given the potential patient outcome if any underlying condition of patient 4 is unresolved.

[0035] In some examples, processing circuit 14 may determine that there is a risk that patient 4 may experience MACE based on more than one respective FMA relative to a respective SMA varying beyond a respective difference threshold. For example, processing circuit 14 may determine that multiple respective differences between the respective FMA and the respective SMA satisfy the respective difference threshold. Processing circuit 50 may set respective flags indicating that each of the multiple respective differences satisfies the respective difference threshold. Processing circuit 50 may generate an indication of the risk of MACE for output based on at least two of the respective flags.

[0036] In response to or based on determining that the FMA relative to the SMA for a given physiological parameter varies beyond an associated difference threshold, processing circuit 14 may set a flag and / or generate an indication for output. The flag or the indication may indicate the risk that patient 4 may experience MACE within a time frame (e.g., within seconds, minutes, hours, days, or weeks, etc.). For example, the flag or indication may indicate the MACE risk within a time frame (such as within x days, y hours, or between a days and b days or between c hours and d hours). In some examples, processing circuit 14 may generate the flag periodically (e.g., hourly or daily). Such a flag may indicate that the difference between the FMA and the SMA for a given physiological parameter satisfies or does not satisfy the associated difference threshold. In some examples, processing circuit 14 may output the indication to notify patient 4 and / or the clinician of the risk of MACE.

[0037] In some examples, the processing circuitry 14 may determine that a particular type of problem may lead to a suspected MACE based on which physiological parameter or combination of physiological parameters may have an associated difference between the FMA and the SMA that is greater than (or greater than or equal to) an associated difference threshold for the corresponding physiological parameter. This type of problem may include structural problems, coronary artery problems, and / or conduction problems. For example, a structural problem may be a structural problem with the patient 4's heart itself. A coronary artery problem may be a problem with the vasculature near the patient 4's heart. A conduction problem may be a problem with the patient 4's electrophysiology. Physiological parameters that may indicate, for example, that a MACE may occur within a time range may include, but are not limited to: 1) glucose levels and derived metrics such as time in target range; 2) respiratory rate; 3) pulse oximeter parameters such as SpO2 blood oxygen saturation and perfusion index; 4) heart rate and derived metrics such as heart rate variability and / or nocturnal heart rate; 5) blood pressure and derived metrics such as pulse pressure, mean arterial pressure, and / or radial artery pressure, central venous pressure; 6) physiological parameters that can be discerned from acoustic signals such as physiological parameters related to blood flow rate and / or pulse wave velocity; and / or 7) activity level.

[0038] For example, a large amount of atrial fibrillation may indicate a conduction problem, and thus the conduction problem may be a cause of the MACE risk. A low amount of daily activity or low heart rate variability (HRV) may indicate a coronary artery problem that may be a cause of the MACE risk. Abnormal blood flow (e.g., which may be determined by tracking heart sounds and identifying any harmonics in the resulting waveform that may not typically be present in relatively normal structural anatomy and physiology) may indicate a structural problem that may be a cause of the MACE risk. In some examples, the flag and / or the indication may include an indication of what type of problem the patient 4 may have and / or which physiological parameter may have an FMA that varies from the SMA by more than the difference threshold. In some examples, the flag and / or the indication may include an indication of the difference between the FMA and the SMA and / or an indication of how much the FMA varies relative to the difference threshold.

[0039] The external device 12 can be a handheld computing device having a display that a user can view and an interface for providing input to the external device 12 (e.g., a user input mechanism). For example, the external device 12 can include a display screen (e.g., a liquid crystal display (LCD) or a light emitting diode (LED) display) that presents information to the user. Additionally, the external device 12 can include a touchscreen display, a keypad, buttons, a peripheral pointing device, voice activation, or another input mechanism that allows the user to navigate and provide input through the user interface of the external device 12. If the external device 12 includes buttons and a keypad, the buttons can be dedicated to performing specific functions, e.g., a power button, and the buttons and keypad can be soft keys that change functions depending on the portion of the user interface that the user is currently viewing, or any combination thereof.

[0040] In some examples, the external device 12 can be a separate application within another multifunctional device rather than a dedicated computing device. For example, the multifunctional device can be a cellular phone, a tablet computer, a digital camera, or another computing device that can run an application that enables the external device to operate as described herein.

[0041] When the external device 12 is configured for use by a clinician, the external device 12 can be used to transmit instructions to the IMD 10 and / or the wearable device 6 and receive sensed signals, values of physiological parameters, flags, indications, or other information that can be sensed, processed, or determined by the IMD 10 and / or the wearable device 6. Example instructions can include requests for electrode combinations to be set for sensing and any other information that can be programmed into the IMD 10 and / or the wearable device 6. The clinician can also configure and store the operating parameters of the IMD 10 and / or the wearable device 6 within the IMD 10 and / or the wearable device 6 with the aid of the external device 12. In some examples, the external device 12 helps the clinician configure the IMD 10 and / or the wearable device 6 by providing a system for identifying potentially beneficial operating parameter values.

[0042] Regardless of whether the external device 12 is configured for use by a clinician or a patient, the external device 12 is configured to communicate with the IMD 10 and / or the wearable device 6 via wireless communication and / or wired or optical communication, and optionally with another computing device ( Figure 1 not illustrated). For example, the external device 12 can communicate via near-field communication techniques (e.g., inductive coupling, NFC, or other communication techniques that can operate at ranges less than 10 cm to 20 cm) and far-field communication techniques (e.g., RF telemetry according to the 802.11 or specification set or other communication techniques that can operate at ranges greater than those of the near-field communication techniques). In some examples, the IMD 10 and the wearable device 6 can be configured to communicate with each other via wireless communication.

[0043] In some examples, processing circuitry 14 can include one or more processors configured to implement functionality and / or processing instructions for execution within IMD 10, wearable device 6, and / or external device 12. For example, processing circuitry 14 can be capable of processing instructions stored in a storage device. Processing circuitry 14 can 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 any combination of the foregoing devices or circuits. Thus, processing circuitry 14 can include any suitable structure, whether in hardware, software, firmware, or any combination thereof, to perform the functions attributed to processing circuitry 14 herein.

[0044] Processing circuitry 14 can represent processing circuitry located within any combination of IMD 10, wearable device 6, and / or external device 12. In some examples, processing circuitry 14 can be entirely located within the housing of IMD 10. In other examples, processing circuitry 14 can be entirely located within or on wearable device 6. In other examples, processing circuitry 14 can be entirely located within the housing of external device 12. In other examples, processing circuitry 14 can be located within any combination of IMD 10, wearable device 6, external device 12, and Figure 1 another device or another set of devices not illustrated herein. Thus, the techniques and capabilities attributed to processing circuitry 14 herein can be attributed to any combination of IMD 10, wearable device 6, external device 12, and Figure 1 other devices not illustrated herein.

[0045] Although in one example, IMD 10 takes the form of an ICM, in other examples, IMD 10 takes the form of any one or more of an ICM, a pacemaker, a defibrillator, a cardiac resynchronization therapy device, an implantable pulse generator, an intracardiac pressure measurement device, a ventricular assist device, a pulmonary artery pressure device, or a subcutaneous blood pressure device. Although in one example, wearable device 6 takes the form of a patch, in some examples, wearable device 6 takes the form of any one or more of a pulse oximeter, a fitness tracker device, a watch, a wristband, a headband, a chest strap, a face mask, a finger clip, a ring, etc. The physiological parameters discussed herein can be sensed or determined using one or more of the foregoing devices and an external device such as external device 12.

[0046] Figure 2 is an illustrative conceptual diagram of an example configuration of IMD 10 of medical device system 2 in accordance with one or more techniques described herein. In Figure 1 Figure 2 ​In the example shown, the IMD 10 can be a leadless vascular implantable monitoring device having a housing 15, a proximal electrode 16A, and a distal electrode 16B. The housing 15 can also include a first major surface 18, a second major surface 20, a proximal end 22, and a distal end 24. In some examples, the IMD 10 can include one or more additional electrodes 16C, 16D positioned on one or both of the major surfaces 18, 20 of the IMD 10. The housing 15 encapsulates the electronic circuitry located within the IMD 10 and protects the circuitry contained therein from fluids such as bodily fluids (e.g., blood). In some examples, feedthroughs provide electrical connections for the electrodes 16A to 16D and the antenna 26 to the circuitry within the housing 15. In some examples, the electrode 16B can be formed by an uninsulated portion of the conductive housing 15.

[0047] In Figure 2 the example shown, the IMD 10 is defined by a length L, a width W, and a thickness or depth D. In this example, the IMD 10 is in the form of an elongate 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 the IMD 10 are envisioned, such as those where the relative proportions of the length L, width W, and depth D are different from those Figure 2 described and shown herein. In some examples, the geometry of the IMD 10, such as the width W being greater than the depth D, can be selected to allow the IMD 10 to be inserted subcutaneously into a patient's skin using a minimally invasive procedure and to remain in a desired orientation during insertion. Additionally, the IMD 10 can include a radial asymmetry (e.g., a rectangular shape) along the longitudinal axis of the IMD 10, which can help to maintain the device in a desired orientation after implantation.

[0048] In some examples, the spacing between the proximal electrode 16A and the distal electrode 16B can be in the range from about 30 mm to 55 mm, about 35 mm to 55 mm, or about 40 mm to 55 mm, or more generally from about 25 mm to 60 mm. Generally, the IMD 10 can have a length L of about 20 mm to 30 mm, about 40 mm to 60 mm, or about 45 mm to 60 mm. In some examples, the width W of the major surface 18 can be in the range of about 3 mm to 10 mm and can be any single width or range of widths between about 3 mm and 10 mm. In some examples, the depth D of the IMD 10 can be in the range of about 2 mm to 9 mm. In other examples, the depth D of the IMD 10 can be in the range of about 2 mm to 5 mm and can be any single depth or range of depths from about 2 mm to 9 mm. In any such example, the IMD 10 is compact enough to be implanted in a subcutaneous space within the pectoral muscle region of the patient 4.

[0049] According to an example of the present disclosure, the IMD 10 may have a geometry and size designed for ease of implantation and patient comfort. The volume of the example of the IMD 10 described in the present disclosure may be 3 cubic centimeters (cm 3 ) or less, 1.5 cm 3 or less, or any volume therebetween. Additionally, in the Figure 2 example shown, the proximal end 22 and the distal end 24 are rounded to reduce discomfort and irritation to surrounding tissue once implanted under the skin of the patient 4.

[0050] In the Figure 2 example shown, when the IMD 10 is inserted into the patient 4, the first major surface 18 of the IMD 10 faces outward toward the skin, while the second major surface 20 faces inward toward the muscle tissue of the patient 4. Thus, the first major surface 18 and the second major surface 20 may face in a direction along the sagittal axis of the patient 4 (see Figure 1 ), and due to the size of the IMD 10, this orientation may be generally maintained upon implantation.

[0051] When the IMD 10 is implanted subcutaneously in the patient 4, the proximal electrode 16A and the distal electrode 16B may be used to sense cardiac electrogram (EGM) signals (e.g., electrocardiogram (ECG) signals) or to sense the impedance of tissue, etc. For example, the IMD 10 may utilize signals sensed by the proximal electrode 16A and the distal electrode 16B to determine values of certain physiological parameters (such as respiratory rate, heart rate, heart rate variability, or nocturnal heart rate, etc.). Additionally, in some examples, the communication circuitry of the IMD 10 may use the electrodes 16A, 16B for tissue conductance communication (TCC) with an external device 12 or another device.

[0052] In the Figure 2 example shown, the proximal electrode 16A is in close proximity to the proximal end 22, and the distal electrode 16B is in close proximity 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 may extend from the first major surface 18 around a circular edge 28 or an end surface 30 and extend in a three-dimensional curved configuration onto the second major surface 20. As shown, the proximal electrode 16A is located on the first major surface 18 and is substantially flat and faces outward. However, in other examples not shown herein, both the proximal electrode 16A and the distal electrode 16B may be configured similar to the Figure 2 proximal electrode 16A shown therein, or both may be configured similar to the Figure 2The distal electrode 16B shown in FIG. In some examples, additional electrodes 16C and 16D may be positioned on one or both of the first major surface 18 and the second major surface 20 such that a total of four electrodes are included on the IMD 10. Any of the electrodes 16A - 16D may be formed of a biocompatible conductive material. For example, any of the electrodes 16A - 16D may be formed of stainless steel, titanium, platinum, iridium, or any of their alloys. Additionally, the electrodes of the IMD 10 may be coated with a material such as titanium nitride or fractal titanium nitride, although other suitable materials and coatings for such electrodes may also be used.

[0053] In Figure 2 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 major surface (e.g., the first major surface 18) as the proximal electrode 16A and may be an integral part of the head assembly 32. In other examples, the integrated antenna 26 may be formed on the major surface opposite the proximal electrode 16A, or in other examples, the integrated antenna may be incorporated 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 signals to and / or receive signals from a programmer (e.g., the external device 12) and / or the wearable device 6 via inductive coupling, electromagnetic coupling, tissue conductance, near - field communication (NFC), radio - frequency identification (RFID), or other proprietary or non - proprietary wireless telemetry communication schemes. The antenna 26 may be coupled to a communication circuit of the IMD 10 that can drive the antenna 26 to transmit signals to the external device 12 and / or the wearable device 6 and may transmit signals received from the external device 12 and / or the wearable device 6 to the processing circuit of the IMD 10 via the communication circuit.

[0054] In some examples, the IMD 10 may include a number of features that hold the IMD 10 in place once it is subcutaneously implanted in the patient 4 in order to reduce the chance of the IMD 10 migrating within the patient 4's body. For example, as Figure 2 shown, the housing 15 may include an anti - migration protrusion 34 located near the integrated antenna 26. The anti - migration protrusion 34 may include a plurality of ridges or protrusions extending away from the first major surface 18 and may help prevent longitudinal movement of the IMD 10 after it is implanted within the patient 4's body. In other examples, the anti - migration protrusion 34 may be located on the major surface opposite 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 that 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 located near the proximal electrode 16A. In some examples, the head assembly 32 may include a molded head assembly made of a polymer or plastic material that may be integrated with or separable from the main portion of the IMD 10.

[0055] In Figure 2 the example shown, the IMD 10 includes a light emitter 38, a proximal light detector 40A, and a distal light detector 40B located on the housing 15 of the IMD 10. The light detector 40A may be positioned at a distance S from the light emitter 38, while the distal light detector 40B is located at a distance S + N from the light emitter 38. In other examples, the IMD 10 may include only one of the light detectors 40A, 40B or may include additional light emitters and / or additional light detectors. Although the light emitter 38 and the light detectors 40A, 40B are described herein as being located on the housing 15 of the IMD 10, in other examples, one or more of the light emitter 38 and the light detectors 40A, 40B may be located on the housing of another type of IMD within the patient 4, such as a transvenous, subcutaneous, or extravascular pacemaker or ICD, or connected to such a device via leads.

[0056] As Figure 2 shown, the light emitter 38 may be located on the head assembly 32, although in other examples, one or both of the light detectors 40A, 40B may additionally or alternatively be located on the head assembly 32. In some examples, the light emitter 38 may be located on an intermediate portion of the IMD 10, such as a partial path between the proximal end 22 and the distal end 24. Although the light emitter 38 and the light detectors 40A, 40B are illustrated as being located on the first major surface 18, the light emitter 38 and the light detectors 40A, 40B may alternatively be located on the second major surface 20. In some examples, the IMD may be implanted such that when the IMD 10 is implanted, the light emitter 38 and the light detectors 40A, 40B face inward, toward the muscle of the patient 4, which may help to minimize interference from background light outside the patient 4. The light detectors 40A, 40B may include glass or sapphire windows, such as described below with respect to Figure 4B or may be located beneath a portion of the housing 15 of the IMD 10 made of glass or sapphire or other transparent or translucent material. In some examples, the light detectors 40A, 40B may be configured to sense signals indicative of SpO2 blood oxygen saturation and perfusion rate (e.g., pulse oximetry parameters), respiratory rate, heart rate, heart rate variability, or nocturnal heart rate, etc.

[0057] In some examples, the IMD 10 may include one or more additional sensors, such as one or more motion sensors, glucose sensors, acoustic sensors, or pressure sensors, etc. Figure 2 (not shown in figure). For example, the motion sensor may be a 3D accelerometer configured to generate signals indicative of one or more types of movement of the patient, such as overall body movement (e.g., exercise), patient posture, movement associated with a heartbeat, movement associated with breathing, or movement of the IMD 10 within the body of patient 4. The IMD 10 may use such signals to determine values of physiological parameters (such as respiratory rate, heart rate, heart rate variability, nocturnal heart rate (e.g., lack of movement of patient 4's body may indicate nighttime / sleep, which may be used with movement indicative of a heartbeat to determine nocturnal heart rate) or patient activity level, etc.). In some cases, one or more of the parameters monitored by the IMD 10 (e.g., bioimpedance, respiratory rate, ECG, etc.) may fluctuate in response to changes in one or more such types of movement. For example, changes in parameter values may sometimes be attributable to increased patient movement (e.g., exercise or other physical movement compared to immobility) or to changes in patient posture, rather than to changes in a medical condition. Thus, in some techniques for identifying or tracking the medical condition of patient 4, it may be advantageous to consider such fluctuations when determining whether a change in a parameter indicates a change in a medical condition.

[0058] The IMD 10 may determine values of physiological parameters (such as glucose level) or associated physiological parameters (such as time in range) based on signals from one or more glucose sensors. In some examples, one or more sensors may be disposed on an outer surface of the IMD 10. The IMD 10 may include acoustic sensors, and the IMD 10 may use signals from these acoustic sensors to determine values of physiological parameters (such as respiratory rate, heart rate, heart rate variability, nocturnal heart rate, and / or other physiological parameters distinguishable from acoustic signals, such as physiological parameters related to blood flow rate and / or pulse wave velocity). The IMD 10 may include pressure sensors, and the IMD 10 may use signals from these pressure sensors to determine respiratory rate, blood pressure, and / or blood pressure-derived metrics, such as pulse pressure, mean arterial pressure, and / or radial artery pressure or central venous pressure, etc.

[0059] Figure 3 illustrative of one or more techniques described herein Figure 1 and Figure 2Functional block diagram of an example configuration of the IMD 10. In the example shown, the IMD 10 includes electrodes 16, an antenna 26, a processing circuit 50, a sensing circuit 52, a communication circuit 54, a storage device 56, a switching circuit 58, a sensor 62 including a motion sensor 42 (which may include an accelerometer), and a power source 64. In some examples, Figure 3 An example configuration of the wearable device 6 may be depicted. It should be noted that in some examples, the IMD 10 and / or the wearable device 6 may include fewer or more components than Figure 3 those depicted.

[0060] The processing circuit 50 may include fixed-function circuitry and / or programmable processing circuitry. The processing circuit 50 may include any one or more of a microprocessor, a controller, a DSP, an ASIC, an FPGA, or equivalent discrete or analog logic circuitry. In some examples, the processing circuit 50 may include multiple components (such as any combination of one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs) and other discrete or integrated logic circuitry. The functions attributed to the processing circuit 50 herein may be embodied as software, firmware, hardware, or any combination thereof. In some examples, one or more of the techniques of the present disclosure may be performed by the processing circuit 50.

[0061] The sensing circuit 52 and the communication circuit 54 can be selectively coupled to the electrodes 16A to 16D via a switching circuit 58 controlled by the processing circuit 50. The sensing circuit 52 can monitor signals from the electrodes 16A to 16D to monitor, for example, the electrical activity of the heart. The sensing circuit 52 can also monitor signals from the sensor 62, which can include a motion sensor (which can include an accelerometer), a glucose sensor, an acoustic sensor, an optical sensor, or a pressure sensor, etc. In some examples, the sensing circuit 52 can include one or more filters and amplifiers for filtering and amplifying signals received from one or more of the electrodes 16A to 16D and / or the sensor 62. Such signals can indicate physiological parameters of the patient 4. The processing circuit 50 can process such signals to determine values of various physiological parameters. For example, the processing circuit 50 can monitor signals from the glucose sensor of the sensor 62 to determine values of glucose levels and derived metrics (such as time in range). For example, the processing circuit 50 can monitor signals from the electrodes 16A to 16D, the optical sensor of the sensor 62, the acoustic sensor of the sensor 62, and / or the pressure sensor of the sensor 62 to determine the value of the respiratory rate. The processing circuit 50 can monitor signals from the optical sensor of the sensor 62 to determine values of pulse oximetry parameters (such as SpO2 blood oxygen saturation and perfusion index). The processing circuit 50 can monitor signals from the electrodes 16A to 16D, the optical sensor of the sensor 62, and / or the acoustic sensor of the sensor 62 to determine values of heart rate and derived metrics (such as heart rate variability and / or nocturnal heart rate). The processing circuit 50 can monitor signals from the pressure sensor of the sensor 62 to determine values of blood pressure and derived metrics (such as pulse pressure, mean arterial pressure, and / or radial artery pressure, central venous pressure). The processing circuit 50 can monitor signals from the acoustic sensor of the sensor 62 to determine values of physiological parameters that can be discerned from the acoustic signals (such as physiological parameters related to blood flow rate and / or pulse wave velocity).

[0062] The processing circuit 50 can obtain, for example, one or more signals indicating one or more corresponding physiological parameters from the electrodes 16A to 16D, the sensing circuit 52, and / or the sensor 62. The processing circuit 50 can determine corresponding values of one or more corresponding physiological parameters based on the one or more signals. The processing circuit 50 can determine a corresponding SMA of a first subset of the corresponding values of one or more corresponding physiological parameters and a corresponding FMA of a second subset of the corresponding values of one or more corresponding physiological parameters. The processing circuit 50 can determine that a corresponding difference between the corresponding FMA and the corresponding SMA satisfies a corresponding difference threshold. The processing circuit 50 can, based on the corresponding difference satisfying the corresponding difference threshold, perform at least one of the following: (i) set a flag indicating the risk of a major adverse cardiac event (MACE), or (ii) generate an indication of the risk of MACE for output.

[0063] Such an indication may include a warning of a possible MACE (such as a possible MACE occurring within a time frame). The indication may also include an estimated percentage of the risk of a possible MACE occurring within a time frame. In some examples, the flag or indication may include the type of problem that may cause the warning, such as a structural problem, a coronary artery problem, and / or a conduction problem.

[0064] In some examples, the indication may include an instruction for patient 4 to seek medical help or make an appointment with a clinician, and / or an instruction for the clinician regarding which test the clinician should consider performing on patient 4. In some examples, the indication may include one or more of the following: a value of a physiological parameter, SMA, FMA, a difference threshold, a variance between SMA and FMA, or a variance between the difference between SMA and FMA and the associated difference threshold, etc. In some examples, the processing circuit 50 may control the communication circuit 54 to output the flag / indication 45 (including the indication) to transmit the flag / indication 45 to the external device 12, where the processing circuit of the external device 12 may display or otherwise present the indication to patient 4 and / or the clinician via a user interface.

[0065] The communication circuit 54 may include any suitable hardware, firmware, software, or any combination thereof for communicating with another device (such as the external device 12 or another IMD or sensor, such as a pressure sensing device). Under the control of the processing circuit 50, the communication circuit 54 may receive downlink telemetry from the external device 12 or another device (such as the wearable device 6) by means of an internal antenna or an external antenna (e.g., antenna 26)( Figure 2 ) and transmit uplink telemetry to the external device or the other device. Additionally, the processing circuit 50 may communicate with a networked computing device via an external device (such as the external device 12) and a computer network such as the Medtronic network developed by Medtronic of Dublin, Ireland.

[0066] A clinician or other user may retrieve data from the IMD 10 using the external device 12 or by using another local or networked computing device configured to communicate with the processing circuit 50 via the communication circuit 54. The clinician may also use the external device 12 or another local or networked computing device to program the parameters of the IMD 10.

[0067] In some examples, the storage device 56 includes computer-readable instructions that, when executed by the processing circuitry 50, cause the IMD 10 and the processing circuitry 50 to perform the various functions ascribed herein to the IMD 10 and the processing circuitry 50. The storage device 56 can include any volatile medium, non-volatile medium, magnetic medium, optical medium, or electrical medium, such as random access memory (RAM), ferroelectric RAM (FRAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, or any other digital medium.

[0068] The storage device 56 can also store a difference threshold 47. In some examples, the difference threshold 47 can include a plurality of respective difference thresholds, one difference threshold corresponding to each physiological parameter that can be monitored to determine whether the patient 4 is at risk of developing a MACE. In some examples, the difference threshold is programmable, e.g., by a clinician. In some examples, the difference threshold includes an absolute value and is not derived by the processing circuitry 50 based on other information, such as SMA or FMA.

[0069] The storage device 56 can also store the determined values and / or differences, e.g., stored in the value / difference 41. For example, the storage device 56 can store the respective physiological parameter values in the value / difference 41. The storage device 56 can additionally or alternatively store the determined difference between the respective SMA and the respective FMA and / or the respective difference between the determined difference between the respective SMA and the respective FMA and the respective difference threshold (of the difference threshold 47).

[0070] The storage device 56 can also store the signal 43. For example, any one or each physiological parameter of the signals indicating a physiological parameter (or a portion thereof) can be stored in the signal 43, e.g., for transmission to or retrieval by the external device 12.

[0071] The storage device 56 can also store the flag / indicator 45. For example, any generated flag or indicator can be stored in the flag / indicator 45 for transmission to or retrieval by the external device 12.

[0072] The power source 64 is configured to deliver operating power to the components of the IMD 10. The power source 64 can include a battery and a power generation circuit for generating the operating power. In some examples, the battery is rechargeable to allow for extended operation. In some examples, the recharge is achieved through a near-side inductive interaction between an external charger and an inductive charging coil within the external device 12. The power source 64 can include any one or more of a variety of different battery types, such as nickel-cadmium batteries and lithium-ion batteries. Non-rechargeable batteries can be selected to last for several years, while rechargeable batteries can be inductively charged from the external device, e.g., on a daily or weekly basis.

[0073] Although not described with respect to a separate drawing, the wearable device 6 may include one or more components similar to the components of the IMD 10 of Figure 3 . It should be noted that some types of sensors may be capable of being implemented in the wearable device 6, which may not be practical in the IMD 10. For example, the wearable device 6 may include a girth sensor (e.g., when the wearable device 6 includes a chest strap) or a flow meter (e.g., when the wearable device 6 includes a face mask) that can sense signals indicative of a respiratory rate.

[0074] Figure 4A and Figure 4B illustrates two additional example IMDs that may be substantially similar to the IMD 10 of Figures 1 to 3 but may include one or more additional features. Figure 4A and Figure 4B The components of may not be drawn to scale but may be enlarged to show details. Figure 4A is a block diagram of a top view of an example configuration of the IMD 10A. Figure 4B is a block diagram illustrating a side view of the IMD 10B, which may include an insulating layer as described below.

[0075] Figure 4A is a conceptual diagram of another example IMD 10 that may be substantially similar to the IMD 10A of Figure 1 . In addition to the components illustrated by Figures 1 to 3 , the example of the IMD 10 illustrated by Figure 4A may further 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 house one or more of the internal components of the IMD 10 illustrated by Figure 3 , such as one or more of the internal components of the processing circuit 50, the sensing circuit 52, the communication circuit 54, the storage device 56, the switching circuit 58, the internal components of the sensor 62, and the 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.

[0076] Figure 4B is a conceptual diagram of an example IMD 10B that may include components of the IMD 10 that are substantially similar to Figure 1 . In addition to the components illustrated by Figures 1 to 3 , the example of the IMD 10 illustrated by Figure 4BThe illustrated example of the IMD 10B may also include a wafer-level insulation cover 76, which may help insulate the electrical signals transmitted between the electrodes 16A-16D and / or the photodetectors 40A, 40B on the housing 15B and the processing circuit 50. In some examples, the insulation cover 76 may be positioned over the open housing 15 to form a housing for the components of the IMD 10B. One or more components of the IMD 10B (e.g., the antenna 26, the optical transmitter 38, the photodetectors 40A, 40B, the processing circuit 50, the sensing circuit 52, the communication circuit 54, the switching circuit 58, and / or the power supply 64) may be formed on the bottom side of the insulation cover 76, such as by using flip-chip technology. The insulation cover 76 may be flipped onto the housing 15B. When flipped and placed on the housing 15B, the components of the IMD 10B formed on the bottom side of the insulation cover 76 may be positioned in the gap 78 defined by the housing 15B.

[0077] The insulation cover 76 may be configured not to interfere with the operation of the IMD 10B. For example, one or more of the electrodes 16A-16D may be formed or placed on top of the insulation cover 76 and electrically connected to the switching circuit 58 through one or more vias (not shown) formed through the insulation cover 76. The insulation cover 76 may be formed of sapphire (i.e., corundum), glass, parylene, and / or any other suitable insulating material. The transmittance of sapphire for wavelengths in the range of approximately 300 nm to approximately 4000 nm may be greater than 80%, and it may have a relatively flat profile. In the case of variations, different transmissions at different wavelengths may be compensated, for example, by using a ratio metric method. In some examples, the insulation cover 76 may have a thickness of about 300 microns to about 600 microns. The housing 15B may be formed of titanium or any other suitable material (e.g., a biocompatible material) and may have a thickness of about 200 microns to about 500 microns. These materials and dimensions are merely examples, and other materials and other thicknesses are also possible for the devices of the present disclosure.

[0078] Figure 5 is a block diagram illustrating an example configuration of components of an external device 12 according to one or more techniques of the present disclosure. In Figure 5 the example, the external device 12 includes a processing circuit 80, a communication circuit 82, a storage device 84, a user interface 86, and a power supply 88. In some examples, the external device 12 may include Figure 5 additional components not depicted in Figure 5 or fewer components than those depicted.

[0079] In one example, processing circuitry 80 may include one or more processors configured to implement functionality and / or processing instructions for execution within external device 12. For example, processing circuitry 80 may be capable of processing 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 circuitry. Thus, processing circuitry 80 may include any suitable structure, whether hardware, software, firmware, or any combination thereof, to perform the functions attributed to processing circuitry 80 herein. In some examples, processing circuitry 80 may execute one or more of the techniques of the present disclosure.

[0080] Processing circuitry 80 may receive a flag and / or indication from IMD 10 and / or wearable device 6 indicating the risk of MACE occurring within a time frame. In some examples, for instance, when processing circuitry 80 receives such a flag, processing circuitry 80 may generate an indication for output. Such an indication may include a warning that MACE may occur within the time frame. The indication may also include an estimated percentage of the risk that MACE may occur within the time frame. In some examples, the flag or indication may include the type of problem that may cause a warning, such as a structural problem, a coronary artery problem, and / or a conduction problem. For example, processing circuitry 80 may control user interface 86 to display or otherwise present the indication to patient 4 and / or a clinician.

[0081] In some examples, rather than receiving the flag and / or the indication from IMD 10 and / or wearable device 6, processing circuitry 80 may obtain values of one or more respective physiological parameters and determine a respective SMA of a first subset of respective values of the one or more respective physiological parameters and a respective FMA of a second subset of respective values of the one or more respective physiological parameters. Processing circuitry 80 may determine that a respective difference between the respective FMA and the respective SMA meets a respective difference threshold. In some examples, processing circuitry 80 may, based on the respective difference meeting the respective difference threshold, perform at least one of the following: (i) set a flag indicating the risk of a major adverse cardiac event (MACE) occurring, or (ii) generate an indication of the risk of MACE occurring for output. In some examples, processing circuitry 80 may obtain the respective SMA and the respective FMA from IMD 10, rather than determining the respective SMA of the first subset of respective values of the one or more respective physiological parameters and the respective FMA of the second subset of respective values of the one or more respective physiological parameters.

[0082] In some examples, the indication may include instructions for the patient 4 to seek medical help or make an appointment with a clinician, and / or instructions for the clinician regarding which tests the clinician should consider performing on the patient 4. In some examples, the indication may include one or more of the following: the value of a physiological parameter, SMA, FMA, differential threshold, variance between SMA and FMA, or variance between the difference between SMA and FMA and the associated differential threshold, etc.

[0083] The communication circuit 82 may include any suitable hardware, firmware, software, or any combination thereof for communicating with another device, such as the IMD 10 or the wearable device 6. Under the control of the processing circuit 80, the communication circuit 82 may receive downlink telemetry from the IMD 10 or another device, such as the wearable device 6, and transmit uplink telemetry to the IMD or the other device. For example, the communication circuit 82 may receive a flag and / or warning regarding the MACE risk from the IMD 10 and / or the wearable device 6.

[0084] The storage device 84 may be configured to store information within the external device 12 during operation. The storage device 84 may include a computer-readable storage medium or a computer-readable storage device. In some examples, the storage device 84 includes one or more of short-term memory or long-term memory. The storage device 84 may include, for example, RAM, dynamic random access memory (DRAM), static random access memory (SRAM), magnetic disks, optical disks, flash memory, or various forms of electrically programmable memory (EPROM) or EEPROM. In some examples, the storage device 84 is used to store data indicating instructions for execution by the processing circuit 80. The storage device 84 may be used by software or an application running on the external device 12 to temporarily store information during program execution.

[0085] The storage device 84 may also store information that the external device 12 may receive from the IMD 10. For example, the communication circuit 82 may receive information from the IMD 10, and the processing circuit 80 may store the information in the storage device 84.

[0086] For example, the storage device 84 may store the differential threshold 87, which may correspond to Figure 3 the differential threshold 47. In this way, the user of the external device 12 may be able to view, for example, one or more of the differential thresholds 47 via the user interface 86 and program one or more of the differential thresholds for, for example, uploading to the differential threshold 47 of the IMD 10.

[0087] The storage device 84 may also store the value / difference 81, which may correspond to Figure 3 the value / difference 41. The storage device 84 may also store the signal 83, which may correspond to Figure 3signal 43. The storage device 56 may also store a flag / indicator 85, which may correspond to the flag / indicator 45.

[0088] Data exchanged between the external device 12, the IMD 10, and / or the wearable device 6 may include operating parameters. The external device 12 may transmit data including computer-readable instructions that, when implemented by the IMD 10 and / or the wearable device 6, may control the IMD 10 and / or the wearable device 6 to change one or more operating parameters and / or export the collected data. For example, the processing circuit 80 may transmit instructions to the IMD 10 that request the IMD 10 to export the collected data (e.g., corresponding to sensed physiological parameters, SMA, FMA, comparison results (including differences and / or variances), flags, indicators, data of suspected types of problems leading to MACE risk, or other data discussed herein). In turn, the external device 12 may receive the data collected from the IMD 10 and store the collected data in the storage device 84. Additionally or alternatively, the processing circuit 80 may export instructions to the IMD 10 and / or the wearable device 6 that request the IMD 10 and / or the wearable device 6 to update one or more operating parameters of the IMD 10 and / or the wearable device 6.

[0089] A user such as a clinician, patient 4, or caregiver may interact with the external device 12 through the user interface 86. The user interface 86 includes a display (such as an LCD or LED display or other type of screen) (not shown), and the processing circuit 80 may use the display to present information related to the IMD 10 and / or the wearable device 6 (e.g., generated indicators). Additionally, the user interface 86 may include an input mechanism for receiving input from the user. The input mechanism may include, for example, any one or more of buttons, a keypad (e.g., an alphanumeric keypad), a peripheral pointing device, a touch screen, or another input mechanism that allows the user to navigate through the user interface presented by the processing circuit 80 of the external device 12 and provide input.

[0090] The power supply 88 is configured to deliver operating power to the components of the external device 12. The power supply 88 may include a battery and a power generation circuit for generating operating power. In some examples, the battery is rechargeable to allow for extended operation. Recharging may be achieved by electrically coupling the power supply 88 to a dock or plug connected to an alternating current (AC) outlet. Additionally, recharging may be achieved through proximal inductive interaction between an external charger and an inductive charging coil within the external device 12. In other examples, conventional batteries (e.g., nickel-cadmium or lithium-ion batteries) may be used. Additionally, the external device 12 may be directly coupled to an AC outlet for operation.

[0091] Figure 6is a block diagram of an example system illustrating one or more techniques described herein. The example system includes an access point 90, a network 92, an external computing device such as a server 94, and one or more other computing devices 100A through 100N, which may be coupled to the IMD 10, the wearable device 6, the external device 12, and / or the processing circuitry 14 via the network 92. Although Figure 6 not shown, the wearable device 6 may operate similarly to the IMD 10 as described with respect to Figure 6 in a system that includes the wearable device 6. In this example, the IMD 10 may communicate with the external device 12 via a first wireless connection and with the access point 90 via a second wireless connection using the communication circuitry 54. In Figure 6 the example, the access point 90, the external device 12, the server 94, and the computing devices 100A through 100N are interconnected and may communicate with each other via the network 92.

[0092] The access point 90 may include a device connected to the network 92 via any one of a variety of connections such as a telephone dial-up, digital subscriber line (DSL), fiber optic, or cable modem connection. In other examples, the access point 90 may be coupled to the network 92 via different forms of connections including a wired connection or a wireless connection. In some examples, the access point 90 may be a user device that may be co-located with the patient, such as a tablet or a smart phone. As discussed above, the IMD 10 may be configured to transmit data such as values / differences 41, signals 43, and / or flags / indications 45 or other data collected by the IMD 10 to the external device 12. Additionally, the access point 90 may interrogate the IMD 10, such as periodically or in response to a command from the patient or the network 92, to retrieve information such as physiological parameter values determined by the processing circuitry 50 of the IMD 10 or other operational or patient data from the IMD 10. The access point 90 may then transmit the retrieved data to the server 94 via the network 92.

[0093] In some cases, the server 94 may be configured to provide a secure storage site for data (such as values / differences 41, signals 43, and / or flags / indications 45 and / or other information related to the patient 4) that has been collected from the IMD 10 and / or the external device 12. In some cases, the server 94 may aggregate the data in a web page or other document for viewing by trained professionals such as clinicians via the computing devices 100A through 100N. Figure 6 One or more aspects of the illustrated system may be implemented using general network technologies and functionality similar to the general network technologies and functionality provided by a Medtronic network developed by Medtronic, Inc. of Dublin, Ireland.

[0094] The server 94 may include processing circuitry 96. The processing circuitry 96 may include fixed-function circuitry and / or programmable processing circuitry. The processing circuitry 96 may include any one or more of a microprocessor, a controller, a DSP, an ASIC, an FPGA, or equivalent discrete or analog logic circuitry. In some examples, the processing circuitry 96 may include multiple components (such as any combination of one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs) and other discrete or integrated logic circuitry. The functionality attributed to the processing circuitry 96 herein may be embodied as software, firmware, hardware, or any combination thereof. In some examples, the processing circuitry 96 may perform one or more of the techniques described herein.

[0095] The server 94 may include a memory 98. The memory 98 includes computer-readable instructions that, when executed by the processing circuitry 96, cause the IMD 10 and the processing circuitry 96 to perform the various functions attributed to the IMD 10 and the processing circuitry 96 herein. The memory 98 may include any volatile medium, non-volatile medium, magnetic medium, optical medium, or dielectric medium, such as RAM, ROM, NVRAM, EEPROM, flash memory, or any other digital medium.

[0096] In some examples, one or more of computing devices 100A through 100N (e.g., device 100A) can be a tablet or other smart device located at a clinician, through which the clinician can program the IMD 10 and / or the external device 12, receive warnings from and / or interrogate the IMD and the external device. For example, the clinician can receive an indication of the risk of MACE for patient 4 and / or access values / differences 41, signals 43, flags / indications 45, or difference thresholds 47, etc., such as when patient 4 is between clinician visits or when the IMD 10 determines the risk of MACE. In some examples, the clinician can input instructions for a medical intervention for patient 4 into an application in device 100A, such as based on an indication of the output and / or data associated with the indication and / or based on other patient data known to the clinician. Then, device 100A can transmit the instructions for the medical intervention to another one of computing devices 100A through 100N located within patient 4 or a caregiver of patient 4 (e.g., device 100B). For example, such instructions for a medical intervention can include instructions to change a medication dose, timing, or selection, schedule a clinician visit, take their liquid medication, or seek medical attention. In additional examples, device 100B can output an indication (such as issue a warning to patient 4) to patient 4 based on the risk of MACE, which can enable patient 4 to proactively seek medical attention before receiving the instructions for the medical intervention. In this way, patient 4 can take action on their own as needed to address their medical condition, which can help improve the clinical outcome for patient 4.

[0097] Figure 7 is a flowchart illustrating example MACE prediction techniques in accordance with one or more aspects of the present disclosure. Although the discussion herein is with respect to the IMD 10 and the processing circuitry 50 of the IMD 10, it should be noted that Figure 7 the techniques can be performed by any device or combination of devices described herein capable of performing such techniques. For example, the processing circuitry 14 can perform the techniques attributed herein to the processing circuitry 50.

[0098] The processing circuitry 50 can obtain one or more signals (700) indicative of one or more respective physiological parameters. For example, the processing circuitry 50 can receive one or more signals indicative of one or more respective physiological parameters from the sensing circuitry 52. The processing circuitry 50 can determine respective values (702) of the one or more respective physiological parameters based on the one or more signals. For example, the processing circuitry 50 can determine values of a physiological parameter over time based on the signals received from the sensing circuitry 52.

[0099] Processing circuitry 50 may determine a respective SMA (704) of a respective first subset of values of one or more respective physiological parameters. For example, processing circuitry 50 may average the values of the physiological parameters sampled over a first relatively long time period to determine the respective SMA.

[0100] Processing circuitry 50 may determine a respective FMA (706) of a respective second subset of values of one or more respective physiological parameters. For example, processing circuitry 50 may average the values of the physiological parameters sampled over a second relatively short time period. For example, the SMA period may be longer than the FMA period, and the first subset of values may include the second subset of values. In some examples, the samples used to determine the SMA may include the samples used to determine the FMA plus additional samples, since the SMA includes samples over a longer time period. As an example, the SMA may be determined based on 100 samples of the values of the physiological parameter, and the FMA may be determined based on 10 samples of the values of the physiological parameter, and the 10 samples used to determine the FMA are among the 100 samples used to determine the SMA.

[0101] Processing circuitry 50 may determine that a respective difference between the respective FMA and the respective SMA satisfies a respective difference threshold (708). For example, processing circuitry 50 may determine the difference between the FMA and the corresponding SMA for a given physiological parameter. Processing circuitry 50 may determine whether the difference between the FMA and the SMA satisfies the difference threshold. For example, if the difference is greater than the difference threshold, or in other examples, if the difference is greater than or equal to the difference threshold, then the difference may satisfy the difference threshold. In some examples, each respective difference threshold among one or more respective difference thresholds is programmable. For example, a clinician may program any one of the respective difference thresholds, for example, based on the medical history of patient 4, to adjust the time period during which a MACE may occur, etc.

[0102] Processing circuitry 50 performs at least one of the following based on the respective difference satisfying the respective difference threshold: set a flag indicating the risk of a MACE occurring, or generate an indication of the risk of a MACE occurring for output (710). For example, processing circuitry 50 may generate a flag and / or an indication indicating the risk of a MACE occurring in patient 4 within a time range. The indication may include a warning of a possible MACE (such as a possible MACE within the time range). The indication may also include an estimated percentage of the risk of a possible MACE within the time range. In some examples, the flag or indication may include the type of problem that may cause the warning, such as a structural problem, a coronary artery problem, and / or a conduction problem.

[0103] In some examples, the indication may include instructions for the patient 4 to seek medical help or make an appointment with a clinician, and / or instructions for the clinician regarding which test the clinician should consider performing on the patient 4. In some examples, the indication may include one or more of the following: the value of a physiological parameter, SMA, FMA, differential threshold, variance between SMA and FMA, or variance between the difference between SMA and FMA and the associated differential threshold, etc.

[0104] In some examples, the processing circuit 50 may determine that a plurality of respective differences between the respective FMA and the respective SMA satisfy the respective differential threshold. The processing circuit 50 may set respective flags indicating that each of the plurality of respective differences satisfies the respective differential threshold. The processing circuit 50 may generate an indication of the risk of MACE for output based on at least two of the respective flags. For example, the processing circuit 50 may determine the risk of MACE based on more than one respective difference satisfying the respective differential threshold.

[0105] In some examples, one or more of the respective physiological parameters include at least one of the following: glucose level, glucose time in range, respiratory rate, SpO2 blood oxygen saturation, blood oxygen perfusion index, heart rate, heart rate variability, nighttime heart rate, blood pressure, pulse pressure, mean arterial pressure, radial artery pressure, central venous pressure, pulse wave velocity, or activity level.

[0106] In some examples, the system includes one or more respective sensors configured to sense one or more respective physiological parameters. In some examples, one or more of the respective sensors include at least one of an implantable sensor or a wearable sensor.

[0107] In some examples, the processing circuit 50 is further configured to determine a type of problem associated with the risk of MACE based on the respective difference satisfying the respective differential threshold, wherein the indication of the risk of MACE includes an indication of the type of problem. In some examples, the type of problem includes at least one of a coronary problem, a structural problem, or a conduction problem.

[0108] In some examples, the indication includes a time range of the MACE risk. In some examples, the corresponding SMA includes an average, median, or mode of the corresponding physiological parameter within an SMA period, which is a range measured in seconds, hours, days, months, or years. In some examples, the corresponding FMA includes an average, median, or mode of the corresponding physiological parameter within an FMA period, which is a range measured in seconds, hours, days, months, or years. In some examples, the SMA is determined within the SMA period, and the FMA is determined within the FMA period, and wherein the FMA period is shorter than the SMA period. In some examples, the SMA period is longer than the FMA period.

[0109] The techniques described in this disclosure may be implemented, at least in part, in the form of hardware, software, firmware, or any combination thereof. For example, aspects of these techniques may be implemented in one or more processors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic QRS circuits, as well as any combination of such components, which are embodied in an external device (such as a clinician or patient programmer, simulator, or other device). The terms "processor" and "processing circuit" generally may refer to any of the foregoing 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.

[0110] For aspects implemented in software, at least some of the functionality attributable to the systems and devices described in this disclosure may be embodied as instructions on a computer-readable storage medium (such as RAM, FRAM, DRAM, SRAM, magnetic disk, optical disk, flash memory, or various forms of EPROM or EEPROM). The executable instructions support one or more aspects of the functionality described in this disclosure.

[0111] In addition, in some aspects, the functionality described herein may be provided within dedicated hardware and / or software modules. Describing different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be implemented by separate hardware or software components. Instead, the functionality associated with one or more modules or units may be performed by separate hardware or software components, or integrated within common or separate hardware or software components. Additionally, these techniques may be implemented entirely in one or more circuits or logic elements. The techniques of this disclosure may be implemented in various devices or apparatuses, including IMDs, external programmers, combinations of IMDs and external programmers, integrated circuits (ICs), or a set of ICs, and / or discrete circuits residing within IMDs and / or external programmers.

[0112] This disclosure includes the following non-limiting examples.

[0113] Example 1. A system, the system comprising: a memory configured to store physiological parameters of a patient; and a processing circuit communicatively coupled to the memory, the processing circuit being configured to: obtain one or more signals indicative of one or more respective physiological parameters; determine respective values of the one or more respective physiological parameters based on the one or more signals; determine a respective slow moving average (SMA) of a first subset of the respective values of the one or more respective physiological parameters; determine a respective fast moving average (FMA) of a second subset of the respective values of the one or more respective physiological parameters; determine that a respective difference between the respective FMA and the respective SMA satisfies a respective difference threshold; and based on the respective difference satisfying the respective difference threshold, perform at least one of the following: a) set a flag indicative of a risk of a major adverse cardiac event (MACE); or b) generate an indication of the risk of MACE for output.

[0114] Example 2. The system according to Example 1, wherein the processing circuit is further configured to: determine that a plurality of respective differences between the respective FMA and the respective SMA satisfy the respective difference threshold; set respective flags indicative of each of the plurality of respective differences satisfying the respective difference threshold; and generate an indication of the risk of MACE for output based on at least two of the respective flags.

[0115] Example 3. The system according to Example 1 or Example 2, wherein the one or more respective physiological parameters include at least one of the following: glucose level, time in glucose target range, respiratory rate, SpO2 blood oxygen saturation, perfusion index, heart rate, heart rate variability, nocturnal heart rate, blood pressure, pulse pressure, mean arterial pressure, radial artery pressure, central venous pressure, pulse wave velocity, or activity level.

[0116] Example 4. The system according to any one of Examples 1 to 3, the system further comprising one or more respective sensors configured to sense the one or more respective physiological parameters.

[0117] Example 5. The system according to Example 4, wherein the one or more respective sensors include at least one of the following: an implantable sensor or a wearable sensor.

[0118] Example 6. The system according to any one of Examples 1 to 5, wherein the processing circuit is further configured to determine a type of problem associated with the risk of the MACE based on the respective difference satisfying the respective difference threshold, wherein the indication of the risk of the MACE includes an indication of the type of problem.

[0119] Example 7. The system according to Example 6, wherein the problem type includes at least one of the following: coronary artery problems, structural problems, or conduction problems.

[0120] Example 8. The system according to any one of Examples 1 to 7, wherein the indication includes a time range of the risk of the MACE.

[0121] Example 9. The system according to any one of Examples 1 to 8, wherein the corresponding SMA includes an average value, a median value, or a mode value of the corresponding physiological parameter within an SMA period, and the SMA period is a range measured in seconds, hours, days, months, or years.

[0122] Example 10. The system according to any one of Examples 1 to 9, wherein the corresponding FMA includes an average value, a median value, or a mode value of the corresponding physiological parameter within an FMA period, and the FMA period is a range measured in seconds, hours, days, months, or years.

[0123] Example 11. The system according to any one of claims 1 to 10, wherein the SMA is determined within an SMA period, and the FMA is determined within an FMA period, and wherein the FMA period is shorter than the SMA period.

[0124] Example 12. A method, the method comprising: obtaining, by a processing circuit, one or more signals indicating one or more corresponding physiological parameters; determining, by the processing circuit, corresponding values of the one or more corresponding physiological parameters based on the one or more signals; determining, by the processing circuit, a corresponding slow moving average (SMA) of a first subset of the corresponding values of the one or more corresponding physiological parameters; determining, by the processing circuit, a corresponding fast moving average (FMA) of a second subset of the corresponding values of the one or more corresponding physiological parameters; determining, by the processing circuit, that a corresponding difference between the corresponding FMA and the corresponding SMA satisfies a corresponding difference threshold; and based on the corresponding difference satisfying the corresponding difference threshold, performing at least one of the following: a) setting, by the processing circuit, a flag indicating a risk of a major adverse cardiac event (MACE); or b) generating, by the processing circuit, an indication of the risk of MACE occurrence for output.

[0125] Example 13. The method according to Example 12, the method further comprising: determining, by the processing circuit, that a plurality of corresponding differences between the corresponding FMA and the corresponding SMA satisfy the corresponding difference threshold; setting, by the processing circuit, corresponding flags indicating that each of the plurality of corresponding differences satisfies the corresponding difference threshold; and generating, by the processing circuit, an indication of the risk of MACE occurrence for output based on at least two of the corresponding flags.

[0126] Example 14. The method according to Example 12 or Example 13, wherein the one or more corresponding physiological parameters include at least one of the following: glucose level, time in the glucose target range, respiratory rate, SpO2 blood oxygen saturation, blood oxygen perfusion index, heart rate, heart rate variability, nocturnal heart rate, blood pressure, pulse pressure, mean arterial pressure, radial artery pressure, central venous pressure, pulse wave velocity, or activity level.

[0127] Example 15. The method according to any one of Examples 12 to 14, the method further comprising sensing the one or more corresponding physiological parameters by one or more corresponding sensors.

[0128] Example 16. The method according to Example 15, wherein the one or more corresponding sensors include at least one of the following: an implantable sensor or a wearable sensor.

[0129] Example 17. The method according to any one of Examples 12 to 16, the method further comprising determining, by the processing circuit, a type of problem associated with the risk of occurrence of the MACE based on the corresponding difference satisfying the corresponding difference threshold, wherein the indication of the risk of occurrence of the MACE includes an indication of the type of problem.

[0130] Example 18. The method according to Example 17, wherein the type of problem includes at least one of the following: a coronary artery problem, a structural problem, or a conduction problem.

[0131] Example 19. The method according to any one of Examples 12 to 18, wherein the indication includes a time range of the risk of the MACE.

[0132] Example 20. The method according to any one of Examples 12 to 19, wherein the corresponding SMA includes an average value, a median value, or a mode value of the corresponding physiological parameter within an SMA period, and the SMA period is a range measured in seconds, hours, days, months, or years.

[0133] Example 21. The method according to any one of Examples 12 to 20, wherein the corresponding FMA includes an average value, a median value, or a mode value of the corresponding physiological parameter within an FMA period, and the FMA period is a range measured in seconds, hours, days, months, or years.

[0134] Example 22. The method according to any one of Examples 12 to 21, wherein the SMA is determined within an SMA period, and the FMA is determined within an FMA period, and wherein the FMA period is shorter than the SMA period.

[0135] Example 23. A non-transitory computer-readable storage medium storing instructions which, when executed, cause a processing circuit to: obtain one or more signals indicative of one or more respective physiological parameters; determine respective values of the one or more respective physiological parameters based on the one or more signals; determine a respective slow moving average (SMA) of a first subset of the respective values of the one or more respective physiological parameters; determine a respective fast moving average (FMA) of a second subset of the respective values of the one or more respective physiological parameters; determine that a respective difference between the respective FMA and the respective SMA satisfies a respective difference threshold; and based on the respective difference satisfying the respective difference threshold, perform at least one of the following: a) set a flag indicative of a risk of a major adverse cardiac event (MACE); or b) generate an indication of the risk of MACE for output.

[0136] Various embodiments have been described. These and other examples are within the scope of the appended claims.

Claims

1. A system, the system comprising: a memory configured to store physiological parameters of a patient; and a processing circuit communicatively coupled to the memory, the processing circuit being configured to: obtain one or more signals indicative of one or more respective physiological parameters; determine respective values of the one or more respective physiological parameters based on the one or more signals; determine a respective slow moving average (SMA) of a first subset of the respective values of the one or more respective physiological parameters; determine a respective fast moving average (FMA) of a second subset of the respective values of the one or more respective physiological parameters; determine that a respective difference between the respective FMA and the respective SMA meets a respective difference threshold; and based on the respective difference meeting the respective difference threshold, perform at least one of the following: a) set a flag indicative of a risk of a major adverse cardiac event (MACE); or b) generate an indication of the risk of MACE for output.

2. The system according to claim 1, wherein the processing circuit is further configured to: determine that a plurality of respective differences between the respective FMA and the respective SMA meet the respective difference threshold; set respective flags indicative of each of the plurality of respective differences meeting the respective difference threshold; and generate an indication of the risk of MACE for output based on at least two of the respective flags.

3. The system according to claim 1 or claim 2, wherein the one or more respective physiological parameters include at least one of the following: glucose level, time in a glucose target range, respiratory rate, SpO2 blood oxygen saturation, perfusion index, heart rate, heart rate variability, nocturnal heart rate, blood pressure, pulse pressure, mean arterial pressure, radial artery pressure, central venous pressure, pulse wave velocity, or activity level.

4. The system according to any one of claims 1 to 3, the system further comprising one or more respective sensors configured to sense the one or more respective physiological parameters.

5. The system according to claim 4, wherein the one or more respective sensors include at least one of the following: an implantable sensor or a wearable sensor.

6. The system according to any one of claims 1 to 5, wherein the processing circuit is further configured to determine a type of problem associated with the risk of the MACE based on the respective difference meeting the respective difference threshold, wherein the indication of the risk of the MACE includes an indication of the type of problem.

7. The system according to claim 6, wherein the type of problem includes at least one of the following: a coronary problem, a structural problem, or a conduction problem.

8. The system according to any one of claims 1 to 7, wherein the indication includes a time range of the risk of the MACE.

9. The system according to any one of claims 1 to 8, wherein the corresponding SMA comprises an average, median or mode of the corresponding physiological parameter over an SMA period, the SMA period being a range measured in seconds, hours, days, months or years.

10. The system according to any one of claims 1 to 9, wherein the corresponding FMA comprises an average, median or mode of the corresponding physiological parameter over an FMA period, the FMA period being a range measured in seconds, hours, days, months or years.

11. The system according to any one of claims 1 to 10, wherein the SMA is determined over an SMA period and the FMA is determined over an FMA period, and wherein the FMA period is shorter than the SMA period.

12. A method, the method comprising: obtaining, by a processing circuit, one or more signals indicative of one or more corresponding physiological parameters; determining, by the processing circuit, corresponding values of the one or more corresponding physiological parameters based on the one or more signals; determining, by the processing circuit, a corresponding slow moving average (SMA) of a first subset of the corresponding values of the one or more corresponding physiological parameters; determining, by the processing circuit, a corresponding fast moving average (FMA) of a second subset of the corresponding values of the one or more corresponding physiological parameters; determining, by the processing circuit, that a corresponding difference between the corresponding FMA and the corresponding SMA meets a corresponding difference threshold; and based on the corresponding difference meeting the corresponding difference threshold, performing at least one of the following: a) setting, by the processing circuit, a flag indicative of a risk of a major adverse cardiac event (MACE) occurring; or b) generating, by the processing circuit, an indication of the risk of MACE occurring for output.

13. The method according to claim 12, the method further comprising: determining, by the processing circuit, that a plurality of corresponding differences between a corresponding FMA and a corresponding SMA meet the corresponding difference threshold; setting, by the processing circuit, corresponding flags indicative of each of the plurality of corresponding differences meeting the corresponding difference threshold; and generating, by the processing circuit, an indication of the risk of MACE occurring for output based on at least two of the corresponding flags.

14. The method according to claim 12 or claim 13, wherein the one or more corresponding physiological parameters comprise at least one of the following: glucose level, time in glucose target range, respiratory rate, SpO2 blood oxygen saturation, perfusion index, heart rate, heart rate variability, nocturnal heart rate, blood pressure, pulse pressure, mean arterial pressure, radial artery pressure, central venous pressure, pulse wave velocity or activity level.

15. A non-transitory computer-readable storage medium storing instructions that, when executed, cause a processing circuit to: obtain one or more signals indicative of one or more corresponding physiological parameters; determine corresponding values of the one or more corresponding physiological parameters based on the one or more signals; determine a corresponding slow moving average (SMA) of a first subset of the corresponding values of the one or more corresponding physiological parameters; Determine a respective fast moving average (FMA) of the respective second subset of the one or more respective physiological parameters; Determine that a respective difference between the respective FMA and the respective SMA satisfies a respective difference threshold; and Based on the respective difference satisfying the respective difference threshold, perform at least one of the following: a) Set a flag indicating a risk of a major adverse cardiac event (MACE); or b) Generate an indication of the risk of MACE for output.

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