Abstract: Example devices, systems, and techniques are disclosed for providing guidance of a treatment of a patient. An example device includes processing circuitry and memory comprising instructions that, when executed by the processing circuitry, cause the processing circuitry to determine that a device detected an acute health event of a patient or delivery of cardiopulmonary resuscitation to the patient, and analyze sensed patient data in response to the determination. The instructions cause the processing circuitry to provide information for guidance of a treatment of the patient based on the analysis.

Abstract: Devices, systems, and techniques are disclosed for verifying the occurrence of an acute health event. An example device includes communication circuitry configured to receive a communication indicative of an acute health event of a patient and memory communicatively coupled to the communication circuitry and being configured to store the indication of the acute health event. The device includes processing circuitry communicatively coupled to the communication circuitry and the memory. The processing circuitry is configured to, in response to the communication, verify the acute health event and based on the verification of the acute health event, send an alert regarding the acute health event.

Abstract: An example device of a patient includes an antenna configured to wirelessly receive communication from a medical device; and processing circuitry coupled to the antenna and configured to: determine that the received communication indicates that a patient is experiencing an acute health event; in response to the determination, determine one or more physical states of the patient based on sensed data from one or more sensors; confirm that the patient is not experiencing the acute health event based on the determined one or more physical states; and output information based on the confirmation that the patient is not experiencing the acute health event.

Abstract: Techniques for transmitting diagnostic information stored in an implantable medical device (IMD) based on patient hospitalization are described. For example, the IMD may transmit higher resolution diagnostic information to a clinician and/or an external device during a hospitalization period to aid the clinician in evaluating heart failure treatment and when discharge is proper. This higher resolution diagnostic information may include one or more patient metrics automatically generated and transmitted by the IMD at least once every two hours. During a post-hospitalization period, the IMD may transmit lower resolution diagnostic information to a clinician that indicates a risk level of re-hospitalization. The lower resolution diagnostic information may include the risk level and/or patient metrics once a day, for example. In this manner, the IMD transmitted diagnostic information may be tailored to the specific heart failure monitoring needed by the patient.

Abstract: An example device of a patient includes an antenna configured to wirelessly receive communication from a medical device; and processing circuitry coupled to the antenna and configured to: determine that the received communication indicates that a patient is experiencing an acute health event; in response to the determination, determine one or more physical states of the patient based on sensed data from one or more sensors; confirm that the patient is not experiencing the acute health event based on the determined one or more physical states; and output information based on the confirmation that the patient is not experiencing the acute health event.

Abstract: This disclosure is directed to systems and techniques for detecting change in patient health and if a change in patient health is detected, direct a medical device to generate for display output indicating the detection of the change in patient health. An example medical system or technique applies a model to values of configurable settings that are programmed into detection logic of a medical device; based on the application, determine whether modified values of the configurable settings, when implemented by the detection logic, would change a determination, by the medical device, regarding whether sensed physiological activity is indicative of cardiac episode for a patient; and in response to a determination that the modified values would change the determination regarding whether the sensed physiological activity is indicative of the cardiac episode for the patient, generate output data indicative of the modified values for the configurable settings for the medical device.

Abstract: This disclosure is directed to a medical system and technique for a filter-based approach to arrhythmia detection. In one example, the medical system comprises one or more sensors configured to sense physiological parameter(s); sensing circuitry configured to generate patient data based on the sensed physiological parameter(s), the patient data comprising signal data to represent cardiac activity of the patient; and processing circuitry configured to: detect a cardiac arrhythmia for the patient based on a classification of the signal data in accordance with a machine learning model, wherein the machine learning model comprises filter(s) for at least one portion of the signal data, wherein the at least one filter corresponds to a feature set that maps to the cardiac activity represented by the portion(s) of the signal data; and generate for display output data indicative of a positive detection of the cardiac arrhythmia.

Abstract: This disclosure describes techniques for bypassing an algorithm configured to determine a likelihood of episode data being a false indication of a cardiac episode. A medical device system includes processing circuitry configured to receive episode data and determine, based on satisfaction of one or more bypass conditions of a set of bypass conditions, whether to bypass the algorithm. Responsive to bypassing the algorithm, the processing circuitry stores the episode data as a true indication of the cardiac episode.

Abstract: A system comprises processing circuitry and memory comprising program instructions that, when executed by the processing circuitry, cause the processing circuitry to: apply a first set of rules to first patient parameter data for a first determination of whether sudden cardiac arrest of a patient is detected; determine that a one or more context criteria of the first determination are satisfied; and in response to satisfaction of the context criteria, apply a second set of rules to second patient parameter data for a second determination of whether sudden cardiac arrest of the patient is detected. At least the second set of rules comprises a machine learning model, and the second patient parameter data comprises at least one patient parameter that is not included in the first patient parameter data.

Abstract: A system comprising processing circuitry configured to receive a wirelessly-transmitted message from a medical device, the message indicating that the medical device detected an acute health event of the patient. In response to the message, the processing circuitry is configured to determine a location of the patient, determine an alert area based on the location of the patient, and control transmission of an alert of the acute heath event of the patient to any one or more computing devices of one or more potential responders within the alert area.

Abstract: An example device of a patient includes an antenna configured to wirelessly receive communication from a medical device; and processing circuitry coupled to the antenna and configured to: determine that the received communication indicates that a patient is experiencing an acute health event; in response to the determination, determine one or more physical states of the patient based on sensed data from one or more sensors; confirm that the patient is not experiencing the acute health event based on the determined one or more physical states; and output information based on the confirmation that the patient is not experiencing the acute health event.

Abstract: Techniques for transmitting diagnostic information stored in an implantable medical device (IMD) based on patient hospitalization are described. For example, the IMD may transmit higher resolution diagnostic information to a clinician and/or an external device during a hospitalization period to aid the clinician in evaluating heart failure treatment and when discharge is proper. This higher resolution diagnostic information may include one or more patient metrics automatically generated and transmitted by the IMD at least once every two hours. During a post-hospitalization period, the IMD may transmit lower resolution diagnostic information to a clinician that indicates a risk level of re-hospitalization. The lower resolution diagnostic information may include the risk level and/or patient metrics once a day, for example. In this manner, the IMD transmitted diagnostic information may be tailored to the specific heart failure monitoring needed by the patient.

Abstract: Techniques for transmitting diagnostic information stored in an implantable medical device (IMD) based on patient hospitalization are described. For example, the IMD may transmit higher resolution diagnostic information to a clinician and/or an external device during a hospitalization period to aid the clinician in evaluating heart failure treatment and when discharge is proper. This higher resolution diagnostic information may include one or more patient metrics automatically generated and transmitted by the IMD at least once every two hours. During a post-hospitalization period, the IMD may transmit lower resolution diagnostic information to a clinician that indicates a risk level of re-hospitalization. The lower resolution diagnostic information may include the risk level and/or patient metrics once a day, for example. In this manner, the IMD transmitted diagnostic information may be tailored to the specific heart failure monitoring needed by the patient.

Abstract: Example techniques, systems, and devices select one or more portions of EGM signal data for presentation based on an identified cardiac episode type of the EGM signal data. For example, one or more processors are configured to receive cardiac electrogram (EGM) signal data collected from a medical device associated with a patient. The EGM signal data may include a detected cardiac episode identified as one of a plurality of episode types. The one or more processors may also be configured to select, based on the identified one of the plurality of episode types, one or more portions of the EGM signal data associated with the detected cardiac episode, and output the selected one or more portions of the EGM signal data.

Abstract: The present disclosure is directed to an electrogram summary. In various examples, a subset of cardiac episodes are selected and displayed based on a set of summary rules. The subset of cardiac episodes includes at least one episode from each of a plurality of episode categories with at least one cardiac episode. In some examples, the order in which the cardiac episodes selected are displayed is based on the set of summary rules. The electrogram summary may include images or information regarding each of the selected cardiac episodes.

Abstract: An implantable medical device (IMD) identifies suspected non-lethal ventricular arrhythmia, and takes one or more actions in response to the identification to avoid or delay delivery of a defibrillation or cardioversion shock. The IMD employs number of intervals to detect (NID) thresholds for detection of ventricular arrhythmias. When a NID threshold is met, the IMD determines whether the ventricular rhythm is a suspected non-lethal rhythm despite satisfying a NID threshold. In some embodiments, the IMD increases the NID threshold, i.e., extends the time for detection, in response to identifying a rhythm as a suspected non-lethal rhythm, and monitors subsequent ventricular beats to determine if the increased NID threshold is met before detecting a ventricular arrhythmia and delivering therapy. The IMD can determine whether a rhythm is a suspected non-lethal arrhythmia by, for example, comparing the median ventricular cycle length (VCL) to the median atrial cycle length (ACL).

Abstract: Example techniques, systems, and devices select one or more portions of EGM signal data for presentation based on an identified cardiac episode type of the EGM signal data. For example, one or more processors are configured to receive cardiac electrogram (EGM) signal data collected from a medical device associated with a patient. The EGM signal data may include a detected cardiac episode identified as one of a plurality of episode types. The one or more processors may also be configured to select, based on the identified one of the plurality of episode types, one or more portions of the EGM signal data associated with the detected cardiac episode, and output the selected one or more portions of the EGM signal data.

Abstract: Cardiac resynchronization therapy (CRT) performance data for a number of patients in which an implantable medical device (IMD) is implanted is aggregated and reports of the aggregated data are generated, e.g., for review by organizations or individual clinicians treating the patients. In one example, a method includes collecting CRT performance data correlated to cardiac rhythm event data for a first group of patients in which an IMD configured to deliver CRT is implanted, aggregating, with a computing device, the CRT performance data correlated to the cardiac rhythm event data for a second group of patients from among the first group of patients, and generating, with the computing device, a report comprising the aggregation of the CRT performance data correlated to the cardiac rhythm event data for the second group of patients.

Abstract: The present disclosure is directed to generating and displaying an electrogram (EGM) summary for use by physicians or other clinicians. An implantable medical device (IMD) transmits EGM signal data for a number of cardiac episodes to an external computing device. The external computing device selects a subset of the cardiac episodes for which information or images are displayed to the user. In various examples, cardiac episodes may be selected for display based at least in part on a retrospective analysis classification of the cardiac episode.

Abstract: An implantable medical device (IMD) identifies suspected non-lethal ventricular arrhythmia, and takes one or more actions in response to the identification to avoid or delay delivery of a defibrillation or cardioversion shock. The IMD employs number of intervals to detect (NID) thresholds for detection of ventricular arrhythmias. When a NID threshold is met, the IMD determines whether the ventricular rhythm is a suspected non-lethal rhythm despite satisfying a NID threshold. In some embodiments, the IMD increases the NID threshold, i.e., extends the time for detection, in response to identifying a rhythm as a suspected non-lethal rhythm, and monitors subsequent ventricular beats to determine if the increased NID threshold is met before detecting a ventricular arrhythmia and delivering therapy. The IMD can determine whether a rhythm is a suspected non-lethal arrhythmia by, for example, comparing the median ventricular cycle length (VCL) to the median atrial cycle length (ACL).