Cardiac Pacemakers, Inc.

Shelley Marie Cazares

Dan Li

Kevin John Stalsberg

Haresh G Sachanandani

Jaeho Kim

Robert J Sweeney

Jon Peterson

Yayun Lin

Carlos Alberto Ricci

Alok S Sathaye

Krzysztof Z Siejko

Gerrard Merrill Carlson

Kent Lee

Jonathan T Kwok

Yi Zhang

Christopher Dale Johnson

William H Sauer

Andrew P Kramer

Quan Ni

Joseph M Bocek

Aaron R McCabe

Yanting Dong

Julie A Thompson

Eric G Lovett

Donald Lee Hopper

Abhilash Patangay

Tamara Colette Baynham

Benjamin Ettori

This document discusses, among other things, systems and methods to enable physician labels on a remote server and use labels to verify and improve algorithm results. A method comprises using patient data in an automated analysis to obtain a result; receiving a message from the user, wherein the message is related to the result; and using at least a portion of the message to automatically modify the analysis.

Method and system to enable physician labels on a remote server and use labels to verify and improve algorithm results

This document discusses, among other things, systems and methods for predicting heart failure decompensation using within-patient diagnostics. A method comprises detecting an alert status of each of one or more sensors; calculating an alert score by combining the detected alerts; and calculating a composite alert score, the composite alert score being indicative of a physiological condition and comprising a combination of two or more alert scores.

Within-patient algorithm to predict heart failure decompensation

A system and method for remotely evaluating patient compliance status is presented. Compliance to a course of treatment is periodically checked through qualitative inquiry of a patient under remote management. Physiometry of the patient, that indicates emotional state, is remotely monitored contemporaneously with the qualitative state. Patient status is evaluated, including at least one of corroborating the compliance and identifying an emotional imbalance, based upon the indicated emotional state of the patient.

System and method for remotely evaluating patient compliance status

Cardiac systems and methods provide for discriminating between supraventricular tachyarrhythmia and ventricular tachyarrhythmia based on a determination that the patient's supraventricular rhythm exhibits rate dependency. One approach involves determining if a patient's supraventricular rhythm exhibits rate dependent morphology. If the patient's supraventricular rhythm is determined to exhibit rate dependent morphology, an implantable device classifies a detected tachyarrhythmia episode based on one or more templates selected from a plurality of rate-indexed templates stored in the device. Determining if the supraventricular rhythm exhibits rate dependent morphology may also include determining one or more rates at which the rate dependent morphology occurs.

Arrhythmia discrimination based on determination of rate dependency

This document discusses, among other things, systems and methods for using one or more inter-relations between within-patient detection methods and between-patient stratifier methods. A method comprises obtaining results of a first physiological assessment, wherein the first physiological assessment includes a between-patient assessment; and using the results to adjust one or more parameters of a second physiological assessment, wherein the second physiological assessment includes a within-patient assessment.

Inter-relation between within-patient decompensation detection algorithm and between-patient stratifier to manage HF patients in a more efficient manner

An implantable cardiac device is configured to classify cardiac arrhythmias using a plurality of arrhythmia discrimination algorithms. Data is provided that is associated with a plurality of cardiac arrhythmic episodes for which a cardiac electrical therapy was delivered or withheld by the implantable medical device based on the plurality of arrhythmia discrimination algorithms. A metric for each of the arrhythmic episodes is computed. The metric defines a measure by which the implantable cardiac device properly classified the arrhythmia. Potentially misclassified arrhythmic episodes of the plurality of cardiac arrhythmic episodes for which cardiac electrical therapy was inappropriately delivered or withheld are algorithmically identified using the metric.

Method and apparatus for identifying potentially misclassified arrhythmic episodes

An implantable cardiac function management device including a programmable controller can be used to include a user-specifiable therapy control parameter set. The therapy control parameter set may then be configured to include at least one therapy control parameter that is user-configurable to automatically switch from a first parameter value to a second parameter value at a time that occurs between separate user programming sessions of the device. Various attributes of physiological measures may allow for refinement of the parameter sets to adapt to changed conditions of the subject. Methods of use are also presented.

Method and apparatus to implement multiple parameter sets in an implantable device

An indication of an actual or potential heart failure condition is computed. One example includes monitoring a first heart rate preceding a first onset of a first sinus tachyarrhythmia episode. Upon detecting the first sinus tachyarrhythmia episode, the indication is automatically provided using information about the first heart rate and how quickly the first onset occurs.

Apparatus and method for heart failure indication based on heart rate, onset and tachyarrhythmia

This document discusses, among other things, systems and methods for using between-patient comparisons for risk stratification of future heart failure decompensation. A method comprises receiving patient data of a current patient, the patient data collected by a patient monitoring device; determining a reference group related to the patient; determining a reference group dataset selected from the reference group, wherein the dataset includes patient data that is of a similar type received from the patient monitoring device; generating a model of the reference group dataset; and automatically comparing the received physiological data to a model to derive an index for the patient.

Between-patient comparisons for risk stratification of future heart failure decompensation

A cardiac rhythm management (CRM) system delivers anti-tachyarrhythmia therapies and uses patient-specific and/or tachyarrhythmia event-specific information to automatically set and adjust one or more arrhythmia detection durations. In one embodiment, the CRM system initializes and updates the one or more arrhythmia detection durations using patient-specific information such as medical history and recent medical trends. In another embodiment, the CRM dynamically adjusts the one or more arrhythmia detection durations using the patient's hemodynamic performance. One example of such an arrhythmia detection duration is a sustained rate duration (SRD) that starts when a tachyarrhythmia such as a supraventricular tachyarrhythmia is detected. An anti-tachyarrhythmia therapy is delivered only if the tachyarrhythmia sustains throughout the SRD.

Method and apparatus for automated adjustment of arrhythmia detection duration

Methods and systems for arranging and labeling cardiac episodes based on acquired cardiac episode data are described. Cardiac episodes are algorithmically arranged based on one or more discriminating features of the episode data. A user is presented with at least one episode selected from the arrangement of cardiac episodes. The user inputs a label that characterizes the selected episode. The label is algorithmically appended to the data of the selected episode and to other episodes of the arrangement of cardiac episodes based on the discriminating features.

Systems and methods for arranging and labeling cardiac episodes

Approaches for determining threshold values for one or more arrhythmia rate zones and/or the number of rate zones are described. A probability function for heart rate is determined using collected and measured heart rate values. One or more heart rate probability values are selected. Thresholds for arrhythmia rate zones are determined from the probability function based on the selected probability values. Determining the rate zone thresholds may involve determining a threshold for a lower rate limit and/or determining one or more tachyarrhythmia rate zone thresholds. The number of rate zones may also be determined based on the probability function.

Methods and devices for determination of arrhythmia rate zone thresholds

Methods and systems for identifying tachyarrhythmia episode types and delivering therapy to mitigate the identified tachyarrhythmia episode types are described. Electrogram signals of cardiac activity are sensed and stored by an implantable cardiac device. Tachyarrhythmia episodes are detected and tachyarrhythmia episode types are identified based on characteristics of the electrogram signals. In preparation for performing ablation, a tachyarrhythmia episode is induced. The features of the induced tachyarrhythmia episode are compared to characteristics of the identified episode types. A similarity between the induced tachyarrhythmia episode and at least one of the episode types identified from the stored electrogram signals is indicated to facilitate performing the ablation.

Therapy delivery for identified tachyarrhythmia episode types

Cardiac arrhythmias are classified based on the morphology of the arrhythmia episode beats. Templates are formed using morphological features of the cardiac beats of the episode. The arrhythmia episode is classified as a monomorphic tachyarrhythmia or polymorphic tachyarrhythmia based on the one or more templates. The arrhythmia episode may be classified based on a number templates formed from the arrhythmia episode. The templates are formed by determining a measure of similarity between morphological features of a cardiac beat to a template. The similarities can be determined based on a pairing rule that determines which beat morphologies are compared. Selection of therapy for treating the arrhythmia episode may depend on the historical success of a therapy at mitigating previous arrhythmias of the same type as the arrhythmia episode.

Discriminating polymorphic and monomorphic cardiac rhythms using template generation

This document discusses, among other things, methods and systems for facilitating automated device programming at changeout. A method comprises receiving, from a first device, physiological data at a temporary storage device; and processing the received physiological data, wherein the processing includes determining if a first signal processing function was used by the first device and substantially offsetting the first signal processing function if the first signal processing function was used by the first device; and processing the resultant physiological data to be compatible with a second device. The method further comprising providing the processed resultant physiological data to the second device.

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Washington, DC, United States of America

Shelley Marie Cazares