Heart Failure Risk Scoring With Biomarker Lookup Weighting
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Solution Overview
Problem
Existing methods for predicting heart failure hospitalization risk are cumbersome, require complex modeling, and provide only broad risk categories without adequate gradations, burdening healthcare providers and lacking in accuracy.
Innovation Solution
A method using implantable medical devices to collect and analyze cardiac and thoracic data, calculating HFH risk through a lookup table based on data observations within defined evaluation periods, providing increased gradations of risk and weighting recent data more heavily for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional methods (probability distribution functions, reference group modeling) are used for risk prediction, then comprehensive analysis is achieved, but device complexity and ease of operation deteriorate due to cumbersome procedures
Solution Approach 1:
The patent uses a lookup table that stores pre-computed risk scores derived from historical data and statistical models. Instead of performing complex probability distribution function calculations in real-time, the system copies pre-analyzed patterns into a table structure that can be queried directly, replacing complex computational processes with simple table lookups based on patient characteristics and biomarker values
Solution Approach 2:
The patent performs risk model calculations and statistical analysis in advance during the table-building phase. All complex computations involving reference group comparisons and probability distributions are completed beforehand, with results stored in the lookup table. This preliminary action eliminates the need for complex real-time calculations during actual risk assessment
2Ease of operation
If broad risk categories are used for simplicity, then ease of operation improves, but measurement precision deteriorates due to lack of risk gradations
Solution Approach 1:
The patent transforms the risk output from broad categorical classifications into a continuous numerical risk score scale. The lookup table generates graded risk scores that reflect varying degrees of risk probability, allowing for fine-grained differentiation between patient risk levels while maintaining the simplicity of a table-based query system
3Ease of operation
If equal weighting is applied to all historical data, then ease of operation improves, but measurement precision deteriorates due to inability to capture recent risk trends
Solution Approach 1:
The patent applies different weighting factors to different time periods or data points within the lookup table structure. Recent biomarker measurements and risk factors are assigned higher weights in the calculations, while historical data receives progressively lower weights. This local differentiation of data quality importance allows the system to capture evolving risk trends while maintaining the streamlined lookup table approach
Data Source
AI summary
Provided is a method, system and/or apparatus for determining prospective heart failure event risk. Acquired from a device memory are a heart failure patient's current and preceding risk assessment periods. Counting detected data observations in the current risk assessment period for a current risk assessment total amount and counting detected data observations in the preceding risk assessment period for a preceding risk assessment period total amount. Associating the current risk assessment and preceding risk assessment total amounts with a lookup table to acquire prospective risk of heart failure (HF) event for the preceding risk assessment period and the current risk assessment period. Employing weighted sums of the prospective risk of the HF event for the preceding risk assessment period and the current risk assessment period to calculate a weighted prospective risk of the HF event for a patient. Displaying on a graphical user interface the weighted prospective risk of the HF event for the patient.