Acute Heart Failure Likelihood Score Using Continuous NT-proBNP Modeling
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Solution Overview
Problem
Current methods for diagnosing acute heart failure are challenging due to the uncertainty of natriuretic peptide thresholds and their performance across different age groups and comorbidities, leading to high false negative rates and inconsistent diagnostic performance.
Innovation Solution
A method using a continuous function to combine natriuretic peptide levels with clinical characteristics, such as age, renal function, and body mass index, through statistical models like generalized linear mixed models and extreme gradient boosting, to provide a personalized likelihood score for acute heart failure, allowing for improved rule-in and rule-out thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If natriuretic peptide thresholds are used to diagnose acute heart failure, then diagnostic speed is improved, but diagnostic accuracy deteriorates due to high false negative rates and inconsistent performance across different age groups and comorbidities
Solution Approach 1:
The patent transforms the diagnostic approach by changing from fixed threshold parameters to a continuous probability score that dynamically adjusts based on multiple clinical parameters including age, sex, renal function, and natriuretic peptide levels. This allows the diagnostic system to maintain speed while improving accuracy by adapting to individual patient characteristics rather than applying uniform thresholds.
Solution Approach 2:
The patent combines multiple diagnostic elements (natriuretic peptide levels, age, sex, renal function, and other clinical variables) into a composite probability score. This composite approach integrates diverse data sources to achieve both rapid assessment and high diagnostic accuracy, overcoming the limitations of single-parameter threshold methods.
2Measurement precision
If age-specific NT-proBNP thresholds are applied, then diagnostic accuracy for older patients is improved, but false negative rates remain high in patients with obesity or prior heart failure
Solution Approach 1:
The patent applies local quality by tailoring the diagnostic assessment to specific patient subgroups through the inclusion of interaction terms in the statistical model. Different clinical scenarios (obesity, prior heart failure, age groups) receive customized weighting and interpretation within the unified probability score framework, ensuring locally optimized diagnostic accuracy for each patient population.
Solution Approach 2:
The patent introduces dynamics by creating a flexible, adaptive diagnostic model that can adjust its sensitivity and specificity based on patient characteristics. The probability score dynamically weights different clinical parameters according to their relevance in specific clinical contexts, allowing the system to maintain high reliability across diverse patient populations rather than relying on static thresholds.
3Ease of operation
If a single NT-proBNP threshold is used for all patients, then ease of operation is improved, but diagnostic performance becomes inconsistent across different patient populations
Solution Approach 1:
The patent achieves universality by creating a single unified probability score model that serves multiple diagnostic functions across all patient populations. Rather than requiring separate threshold algorithms for different age groups or comorbidities, the model universally processes all patient data through one integrated statistical framework, maintaining both operational simplicity and diagnostic consistency.
Solution Approach 2:
The patent transforms the simple threshold parameter into a multi-parameter probability score that continuously adjusts diagnostic likelihood based on the combination of clinical variables. This parameter transformation maintains ease of operation through a single calculable score while internally accounting for population-specific variations to ensure consistent diagnostic performance across all patient groups.
Data Source
AI summary
There is provided a method, systems and device to provide an indication of the probability of acute heart failure in a subject/individual. Suitably a device, systems and methods to determine a likelihood score based upon the concentration of natriuretic peptides in blood and at least two other clinical parameters. The method of determining acute heart failure can comprise the steps of combining the level of natriuretic peptide in a sample from an individual with at least two other clinical parameters from the individual in a statistical model to compute the probability of acute heart failure for the individual patient wherein the level of natriuretic peptide is provided as a continuous variable in the model.