Implanted LAP Waveform Analysis for Early CHF Prediction
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Solution Overview
Problem
Existing hemodynamic management techniques for congestive heart failure (CHF) rely on mean pressure measurements, which may not provide accurate and reliable information for assessing patient status, determining suitable treatments, and monitoring treatment effectiveness, leading to potential mismanagement and hospitalizations.
Innovation Solution
A system using an implanted device to measure Left Atrial Pressure (LAP) and derive periodic waveforms, estimating parameters such as ventricle and atrial waves, and analyzing trends in these waveforms to predict cardiac conditions, providing proactive treatment and improving measurement accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mean pressure measurements are used for hemodynamic management, then the measurement system is simple, but the measurement precision and reliability are insufficient
Solution Approach 1:
The patent segments the mean pressure measurement into multiple distinct waveform parameters (V wave peak, A wave peak, deceleration time, acceleration time, ejection time) that can be independently analyzed. This segmentation allows for more precise hemodynamic assessment by examining specific phases of the cardiac cycle rather than relying on a single averaged value, thereby improving measurement precision without requiring a fundamentally more complex device architecture.
Solution Approach 2:
The patent transitions from one-dimensional mean pressure measurement to multi-dimensional waveform analysis by incorporating temporal dimensions (different phases of cardiac cycle) and amplitude dimensions (peak values, time intervals). This dimensional expansion provides richer hemodynamic information and improves diagnostic precision while using the same implanted pressure sensor, avoiding the need for additional complex measurement devices.
2Reliability
If waveform parameter analysis is implemented, then early prediction of CHF exacerbations is enabled, but the data processing complexity increases
Solution Approach 1:
The patent performs preliminary analysis of waveform parameters continuously in the background, calculating V wave peak, A wave peak, deceleration time, acceleration time, and ejection time for each cardiac cycle. By pre-processing this data and maintaining running averages, the system prepares hemodynamic trends in advance, enabling reliable CHF exacerbation prediction when thresholds are exceeded, without requiring complex real-time processing at the moment of prediction.
Solution Approach 2:
The patent implements feedback mechanisms where calculated waveform parameters are compared against established thresholds, and when abnormalities are detected, alerts are generated and treatment recommendations are provided. This feedback loop continuously monitors hemodynamic status and adjusts predictions based on trending data, improving prediction reliability while using rule-based algorithms that keep processing complexity manageable through automated decision-making protocols.
Data Source
AI summary
A method includes receiving a plurality of measurements of blood pressure acquired in a heart (28) of a patient (30). A periodic waveform of the blood pressure is derived from the measurements, and one or more parameters (Vpeak 45, Apeak 43, RVL, RAL, mean LAP, rise rate, fall rate, rise time, fall time) of one or more components (AW, VW, RP) of the periodic waveform, respectively, are estimated. Occurrence of a cardiac condition in the patient is predicted based on the estimated one or more parameters.