Development and Pre-Clinical Testing of a Smart Defibrillator Algorithm for Treatment of Cardiac Arrhythmias
Development and Pre-Clinical Testing of a Smart Defibrillator Algorithm for Treatment of Cardiac Arrhythmias
批准号:
10260027
负责人:
MARTIN L. MAYSE
金额:
$25.17万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-07-15 至 2022-06-30
关键词:
AlgorithmsAnimal ModelArrhythmiaAtrial FibrillationBenignCardiacCell DeathComputer ModelsCouplingDataDefibrillatorsDevelopmentDevicesElectric CountershockElectroporationEnergy TherapyEntropyGoalsGrantHealth Care CostsHeartHeart AtriumInjuryLearningLifeMapsMeasuresModelingMyocardial StunningOpticsPainPain ThresholdPalatePatientsPatternPerformancePhasePreclinical TestingPredictive ValueProbabilityRandomized Controlled TrialsRattusResolutionRiskSavingsShockSinusStimulusTimeTissuesUnited StatesVentricularVentricular ArrhythmiaVentricular FibrillationWorkbaseclinically relevantdensityexperiencefeasibility testingimprovedinnovationmortalitymyocardial injuryprospective testsensorspatiotemporalsudden cardiac deathvoltage
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英文摘要
Project Summary / Abstract:
Significance: Each year 300,000 to 400,000 patients experience sudden cardiac death in the United States. For patients
at risk, implantable cardiac defibrillators (ICDs) improve survival, largely through the delivery of high energy shocks to
restore sinus rhythm. While high energy shocks are clearly life-saving, they are not necessarily benign. Patients receiving
high energy shocks have increased mortality and programming the device to reduce the number of shocks delivered can
improve mortality. High energy shocks are associated with myocardial stunning, injury, and cell death. In addition, they
are painful to the patient, are associated with significant healthcare costs, and result in more rapid battery depletion.
Innovation: Arrhythmia Dynamics, LLC is developing the IntelliSync ICD control algorithm which enable ICDs to save lives
while minimizing the use of harmful and damaging high energy shocks. IntelliSync will do this in two ways: 1)
recognizing ventricular arrhythmia episodes which have high probability of terminating on their own without therapy;
and 2) making the delivery of low energy defibrillation more likely to terminate the arrhythmia by optimally timing it to a
period of high baseline synchronization in the ventricular chambers.
Approach: In this grant we propose testing the feasibility of these algorithms in computational and rat models of
ventricular fibrillation. In order to be clinically relevant, the algorithms must function and guide the defibrillator’s
decision quickly. The goal of our IntelliSync algorithm are 2-fold: 1) Analyze the first 6-8 seconds of an arrythmia within 2
seconds, recognize patterns of regional coupling within the heart that herald imminent arrhythmia termination. If
identified, the algorithm would trigger the ICD to wait for VF to terminate on its own, and only deliver therapy after a
time-out period has occurred. 2) Measure patterns of coupling within the heart and time low energy therapy (if
appropriate) to a period of high synchronization when it is more likely to succeed. IntelliSync may also work for atrial
fibrillation (AF) and could make an atrial defibrillator palatable if shocks above the pain threshold could be avoided.
Aim 1 (months 1-6): Optimize algorithm performance in computational models of ventricular fibrillation
Sub-aim 1A: Determine minimum spatiotemporal resolution needed to represent high density intracellular voltage maps.
Sub aim 1B: Identify threshold of change in the RQA variable Entropy which predicts imminent termination.
Sub-aim 1C: Demonstrate that low energy therapies can be effectively timed to periods of greater tissue synchronization.
Aim 2 (months 3-9): Demonstrate feasibility of delivering low energy therapy timed to period of high synchronization
based on real-time calculations in a small animal model of VF
Sub aim 2A: Demonstrate that synchrony measured from limited epicardial sensors are representative of full optical maps
Sub-aim 2B: Establish threshold values for the RQA variable Entropy which identify episodes likely to self-terminate
Sub-aim 2C: Prospectively test threshold value of Entropy from Aim 2B.
Sub-Aim 2D: Demonstrate feasibility of performing real-time RQA calculations to guide delivery of low energy therapy.
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