Cardiac Pacemakers, Inc.

Massachusetts Institute of Technology

The Brigham and Women's Hospital, Inc.

Lonza Walkersville, Inc.

Cardiac Pacamakers, Inc.

Yi Zhang

Pramodsingh Hirasingh Thakur

Qi An

Aaron R McCabe

Viktoria A Averina

Jeffrey E Stahmann

John D Hatlestad

Marina V Brockway

Julie A Thompson

Ramesh Wariar

Yinghong Yu

Carlos Alberto Ricci

Kenneth C Beck

Yousufali H Dalal

Krzysztof Z Siejko

Kent Lee

Scott A Meyer

Abhilash Patangay

Robert J Sweeney

Quan Ni

Imad Libbus

Douglas R Daum

Paul Allan Haefner

Aaron Lewicke

Carlos Haro

Joseph M Pastore

Jiang Ding

Avram Scheiner

Anthony V Caparso

Tamara Colette Baynham

M Jason Brooke

Alok S Sathaye

Jonathan T Kwok

Geng Zhang

Allan Charles Shuros

Gerrard Merrill Carlson

Shantha Arcot-Krishnamurthy

Richard Fogoros

Richard O Kuenzler

Jesse W Hartley

Dan Li

David J Yonce

Yunlong Zhang

Yachuan Pu

Jon Peterson

Rodney W Salo

Joseph M Bocek

Bryan Allen Clark

Haruhiko Harry Asada

Lili Liu

Kevin John Stalsberg

Shelley Marie Cazares

Natalie Artzi

Zheng Lin

Bruce H KenKnight

Michael John Kane

Jaeho Kim

David L Perschbacher

Scott Thomas Mazar

Aiden Flanagan

Yatheendhar D Manicka

Ronald W Heil, Jr

Barun Maskara

Yanting Dong

Elazer Reuven Edelman

Donald Lee Hopper

Bin Mi

Xuan K Wei

Eric A Mokelke

Yayun Lin

Jonathan Bennett Shute

Arjun D Sharma

Haresh G Sachanandani

Eytan Abraham

Paul F Emerson

Rezwan Ahmed

Jason Humphrey

Jonathan Walter Krueger

Gezheng Wen

Ron Heil

Michael J Pederson

Yonatan Levinson

Boo-Ho Yang

Regina Kelmansky

Marc Mier Cervantes

Weiguang Shao

Gerard M Carlson

Jianjun Yuan

Kui Wang

Donald I Hopper

Aaron Mccabe

Systems and methods for detecting worsening cardiac conditions such as worsening heart failure events are described. A system may include sensor circuits to sense physiological signals and signal processors to generate from the physiological signals first and second signal metrics. The system may include a risk stratifier circuit to produce a cardiac risk indication. The system may use at least the first signal metric to generate a primary detection indication, and use at least the second signal metric and the risk indication to generate a secondary detection indication. The risk indication may be used to modulate the second signal metric. A detector circuit may detect the worsening cardiac event using the primary and secondary detection indications.

Systems and methods for detecting worsening heart failure

Systems and methods for monitoring patients for risk of worsening heart failure (WHF) are discussed. A patient management system includes a sensor circuit to receive respiration measurements, and an input device to receive patient dyspnea descriptor indicating dyspnea symptom severity. The system includes a risk analyzer circuit to trend the respiration measurement over time, and to generate a WHF risk indicator using both the trended respiration measurement and the received dyspnea descriptor. A control circuit controls the receiver circuit to receive the dyspnea descriptor in response to the trended respiration measurement satisfying a specific condition. The system can present the WHF risk indicator to a user or a process, or deliver or adjust a HF therapy based on the WHF risk indicator.

Worsening heart failure stratification

This document discusses, among other things, systems and methods to determine an alert state for each of a plurality of patients using received physiologic information, determine an event rate for the plurality of patients for a specific alert state, and adjust a composite HF risk determination for the plurality of patients using the determined event rate.

Heart failure event rate assessment

Systems and methods for assessing a patient's risk of renal dysfunction are described. A system may include sensor circuits to sense physiological signals and processors to generate signal metrics from the physiological signals. The system may generate a primary renal risk indication using a first signal metric, and a secondary renal risk indication using at least a second signal metric. The system may generate a composite renal risk indication and estimate a glomerular filtration rate or a chronic kidney disease stage using at least the primary and secondary risk indications. The composite renal risk indication, which indicative of a degree of renal dysfunction, may be presented to a clinician, or provided to a detector for detecting worsening heart failure.

Renal dysfunction risk stratification

Provided are methods of controlling disassociation of cells from a carrier, compositions, and methods of collecting cells. The methods of controlling disassociation of cells from a carrier may include contacting a polymeric carrier with one or more digesting agents to disassociate at least a portion of a plurality of cells from the polymeric carrier. The polymeric carrier may be crosslinked with a crosslinker including at least one of a redox sensitive moiety, a UV light sensitive moiety, a pH sensitive moiety, and a temperature sensitive moiety.

Polymeric carriers and methods

Systems and methods for treating a medical condition such as worsening heart failure (WHF) are described. A medical system may sense one or more physiological signals, and generate from the sensed physiological signals a signal metric trend indicating a progression of heart failure. A detector may detect a physiological event leading to WHF. A therapy control circuit may generate a therapy titration protocol using the generated signal metric trend. The therapy titration protocol includes a temporal profile of therapy dosage relative to a target dosage. The therapy control circuit may adjust the target dosage based on patient response. Therapies may be administered by a clinician or automatically delivered to the patient according to the therapy titration protocol.

Systems and methods for therapy titration in heart failure

Systems and methods provide for assessing the heart failure status of a patient and, more particularly, to generating a trend parameter based on a distribution of the patient's respiration rate. Systems and methods provide for detecting, using an implantable device or a patient-external device, patient respiration and computing a respiration rate based on the detected patient respiration. A distribution of the respiration rate is calculated, and a trend parameter based on the respiration rate distribution is generated. The trend parameter is indicative of a patient's heart failure status. An output signal indicative of the patient's heart failure status may be generated based on the trend parameter.

System and method for generating a trend parameter based on respiration rate distribution

Devices and methods for improving device therapy such as cardiac resynchronization therapy by determining a value for a device parameter are described. An ambulatory medical device (AMD) can include a sensor circuit to sense a physiological signal and generate two or more signal metrics, and detect an event of worsening cardiac condition using the two or more signal metrics. In response to the detection of worsening cardiac condition, the AMD can determine, for a stimulator, a value of at least one stimulation parameter based on temporal responses of two or more signal metrics. The temporal responses include near-term and long-term responses to the stimulation. The AMD can program the stimulator with the determined parameter value, and generate stimulation according to the determined parameter value to stimulate target tissue.

Multi-sensor based cardiac stimulation

Systems and methods for sensing respiration from a subject are discussed. An embodiment of a respiration monitoring system may include a respiration analyzer circuit to select a physiologic signal from a plurality of signals of different types indicative of respiration, such as between first and second physiologic signals that are respectively detected using first and second detection algorithms, and to compute one or more respiration parameters using the selected signal. The system may select or adjust a respiration detection algorithm for detecting the respiration parameters. The physiologic signal, or the respiration detection algorithm, may each be selected based on a signal characteristic or a patient condition. A cardiopulmonary event may be detected using the computed respiration parameter.

Systems and methods for dynamic respiration sensing

Systems and methods for assessing hemodynamic status of a patient experiencing atrial tachyarrhythmia such as an atrial fibrillation (AF) episode are disclosed. A system can comprise an atrial tachyarrhythmia detection circuit configured to detect an AF episode, a hemodynamic sensor circuit configured to sense at least one hemodynamic signal, and a hemodynamic status analyzer circuit that can calculate one or more signal metrics using the sensed hemodynamic signal during the AF episode. The hemodynamic status analyzer circuit can categorize the hemodynamic status of the patient into one of two or more categorical hemodynamic status levels which indicate elevated hemodynamic impact of the detected AF episode. A user interface can provide to an end-user a presentation of the categorized hemodynamic status level during AF.

Systems and methods for evaluating hemodynamic response to atrial fibrillation

An apparatus comprises a respiration sensing circuit configured for coupling electrically to a plurality of electrodes and for sensing a respiration signal representative of respiration of a subject; a signal processing circuit electrically coupled to the respiration sensing circuit and configured to extract a respiration parameter from a sensed respiration signal and determine a signal performance metric for the sensed respiration signal using the respiration parameter; and a control circuit. The control circuit is configured to: initiate sensing of a plurality of respiration signals using different electrode combinations of the plurality of electrodes and determining of the signal performance metric for the sensed respiration signals; and enable an electrode combination from the plurality of electrodes and for use in monitoring respiration of the subject according to the signal performance metric.

Minute volume sensor optimization using quadripolar leads

In one example, a method of monitoring a sustained activity of a human or animal subject for the purpose of determining a risk group includes detecting a physical activity signal from the subject, determining a magnitude of the detected physical activity signal, initiating a timer in response to determining the magnitude of the physical activity signal exceeding an activity level threshold, triggering storing at least one value associated with the physical activity signal only when the magnitude of the physical activity signal exceeds the activity level threshold and the timer is greater than a duration threshold, and determining, using the processor circuit, an indication of the subject's cardiovascular disease based on the stored value.

Activity level determination for risk stratification

A system and method for automatically analyzing heart failure in a patient, including collecting physiological data from a patient using at least a first sensor and a second sensor to collect two or more sensor measurements, and calculating a first composite value based on at least a first sensor measurement wherein the first composite value is an indication of a likelihood that the patient's heart failure status has changed. If the first composite value is outside of a first specified range, then a second composite value is calculated based on at least a second sensor measurement, wherein the second composite value is an indication of a likelihood that the patient's heart failure status has changed. If the second composite value is outside of a second specified range, then an alert of change in heart failure status is generated.

Heart failure detection with a sequential classifier

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Plymouth, MN, United States of America

Yi Zhang