Multi-Parameter Cardiac Scoring for Acute Event Prevention
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Solution Overview
Problem
Existing implantable medical devices (IMDs) effectively detect and terminate tachyarrhythmias but may negatively impact patients with therapy delivery, and delayed treatment poses risks, while current systems lack accurate prediction of acute cardiac events like ventricular tachyarrhythmia, heart failure decompensation, or ischemia.
Innovation Solution
A medical device system predicts acute cardiac events by determining patient parameter values over time periods, calculating difference metrics and scores, comparing against thresholds, and generating alerts or delivering preventive therapies to avoid such events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If therapy is delivered in response to detection of a cardiac event, then the cardiac event is terminated, but the patient's quality of life is negatively impacted and IMD longevity is reduced
Solution Approach 1:
The system performs preliminary actions by predicting acute cardiac events before they occur and delivering preventive therapy in advance. The processing circuitry determines patient parameter values over multiple time periods, calculates difference metrics, and delivers therapy proactively to prevent the cardiac event from occurring, thereby avoiding the harmful effects of reactive therapy delivery.
2Reliability
If therapy is delivered in response to detection of a cardiac event, then the cardiac event is terminated, but IMD longevity is reduced
Solution Approach 1:
The system delivers preventive therapy in advance based on predicted cardiac events rather than reacting after detection. By determining patient parameter trends over multiple periods and calculating difference metrics that indicate impending events, the system activates therapy proactively, reducing the number of reactive shocks needed and thereby extending IMD longevity.
3Reliability
If current IMD systems are used to detect and respond to cardiac events, then treatment is provided, but treatment timing is delayed and patient risk increases
Solution Approach 1:
The system performs preliminary analysis of patient parameters over multiple time periods to predict acute cardiac events before they occur. The processing circuitry determines parameter values, calculates difference metrics comparing current periods to preceding periods, and activates therapy proactively, eliminating treatment delays associated with post-detection response.
Solution Approach 2:
The system continuously monitors patient parameters and uses feedback from comparing current period values against historical data to detect trends indicating impending cardiac events. This feedback mechanism enables timely preventive therapy delivery by identifying predictive patterns in patient parameter changes before the actual cardiac event occurs.
Data Source
AI summary
In some examples, processing circuitry of a medical device system determines, for each of a plurality of patient parameters, a difference metric for a current period based on a value of a patient parameter determined for the current period and a value of the patient parameter determined for an immediately preceding period, and determines a score for the current period based on a sum of the difference metrics for at least some of the plurality of patient parameters. The processing circuitry determines a threshold for the current period based on scores determined for N periods that precede the current period, compares the score for the current period to the threshold, and determines whether to generate an alert indicating that an acute cardiac event of the patient, e.g., ventricular tachyarrhythmia, is predicted, and/or deliver a therapy configured to prevent the acute cardiac event, based on the comparison.