Medtronic, Inc.

Kevin T Ousdigian

Paul Gordon Krause

Paul J DeGroot

Vasant Padmanabhan

Karen J Kleckner

Shantanu Sarkar

Bruce D Gunderson

Vinod Sharma

Amisha Somabhai Patel

Julian Sanchez

Karen A Stone

Robert W Stadler

Douglas A Hettrick

Eduardo N Warman

Walter H Olson

Paul J Degroot

Ryan D Wyszynski

Christopher D Koch

Grant Alan Neitzell

Jodi L Redemske

Denise Dirnberger

Yong Kyun Cho

Catherine R Condie

James David Webb

James H Ericksen

Joel R Lauer

David E Ritscher

James E Willenbring

Cygni Chan

Jean K Ringold

Paul Blowers

Cameron J Kaszas

Sean R Landman

Pamela Jamar

Helen W Otto

Hendrikus A Westendorp

Robert B Trojan

Nelson H Soken

Adam C Richardson

Seema Padmanabhan

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.

Acute health event monitoring

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.

Heart failure monitoring

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.

Automatic alert control for acute health event

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.

Electrogram summary

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.

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).

Reducing inappropriate delivery of therapy for suspected non-lethal arrhythmias

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.

Aggregating cardiac resynchronization therapy data

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.

A system includes an episode classification module and a data retrieval module. The episode classification module receives electrograms (EGMs) from N implantable medical devices (IMDs) and determines whether the EGMs are associated with deliveries of therapy by the N IMDs. The episode classification module analyzes at least some of the EGMs and determines whether the deliveries or non-deliveries of therapy by the IMDs were appropriate. The data retrieval module receives a request from a computing device, via a network, that indicates at least two groups of the N IMDs. The data retrieval module provides to the computing device via the network, in response to the request, data for presentation to a user that indicates for each of the groups, at least one of how many of the one or more deliveries or non-deliveries were appropriate, or how many of the one or more deliveries or non-deliveries were inappropriate.

Evaluation of implantable medical device data

Techniques for storing electrograms (EGMS) that are associated with sensed episodes or events that may be non-physiological and, instead, associated with a sensing integrity condition are described. In some examples, a device or system identifies suspected non-physiological NSTs, and stores an EGM for the suspected non-physiological NSTs within an episode log. In some examples, a device or system determines whether to store an EGM for a suspected non-physiological episode or event based on whether an impedance integrity criterion has been satisfied. For example, a device or system may store an EGM for a detected short interval if the impedance integrity criterion has been met. In some examples, a device or system determines whether to buffer EGM data based on whether an impedance integrity criterion or other sensing integrity criterion has been met.

Electrogram storage for suspected non-physiological episodes

A system and method for delivering both anti-tachy pacing (ATP) therapy and high-voltage shock therapy in response to detection of abnormal cardiac rhythms is disclosed. The system controls the time between delivering ATP therapy and the charging of high-voltage capacitors in preparation for shock delivery based on a predetermined set of criteria. In one embodiment, the inventive system operates in an ATP During Capacitor Charging (ATP-DCC) mode wherein all, or substantially all, of the ATP therapy is delivered during charging of the high-voltage capacitors. Based on evaluation of the predetermined set of criteria, the system may switch to an additional ATP Before Capacitor Charging (ATP-BCC) mode, wherein substantially all of the ATP therapy is delivered prior to charging of the high-voltage capacitor. According to one aspect of the invention, the predetermined set of criteria is based, at least in part, on the effectiveness of previously-delivered ATP therapy.

Method and apparatus to control delivery of high-voltage and anti-tachy pacing therapy in an implantable medical device

In general, the invention is directed towards techniques for adaptively prioritizing cardiac episode data in a memory of an implanted medical device (IMD). More specifically, the IMD receives new cardiac episode data, assigns each piece of data a priority value, and stores the data in a memory of the IMD. The IMD can further recalculate initial priority values assigned to stored cardiac episode data in response to subsequent cardiac episode data. In this manner, the prioritization scheme used by the IMD is adaptive, i.e., changes as more contextual information regarding the cardiac episode and subsequent cardiac episodes becomes available. Upon exceeding a memory capacity threshold, the IMD identifies the stored cardiac episode data with a lowest priority from the hierarchical priority relationship, and overwrites the identified portion of the stored cardiac episode data with the new cardiac episode data.

Adaptive memory prioritization for implanted medical devices

Growing community of inventors

Shoreview, MN, United States of America

Kevin T Ousdigian