Multi-Metabolite Diagnostic Kit for Coronary Heart Disease
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Solution Overview
Problem
Current diagnostic methods for stable angina and myocardial infarction lack specific biomarkers, making early detection and differentiation challenging, especially for stable angina, which shares different risk factors with acute coronary syndrome.
Innovation Solution
A multi-biomarker platform analyzing specific levels of metabolites such as tryptophan, homoserine, fatty acids, and lysophosphatidylcholines, along with clinical parameters like white blood cell count and C-reactive protein, to predict and diagnose coronary heart disease, including stable angina and myocardial infarction through blood testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional single-biomarker methods are used for diagnosis, then the diagnostic process is simple, but the diagnosis precision and early detection capability are insufficient
Solution Approach 1:
The patent combines multiple biomarkers (metabolites including amino acids, fatty acids, lysophosphatidylcholines, phosphatidylcholines, and clinical parameters) into a single integrated diagnostic panel. This merging approach allows simultaneous measurement of multiple disease-related indicators, improving diagnostic precision for stable angina and myocardial infarction while maintaining a unified testing system rather than requiring separate tests for each marker.
Solution Approach 2:
The diagnostic kit is designed to serve multiple functions: it can detect various types of coronary heart disease (stable angina, myocardial infarction), differentiate between disease states, and provide early detection capabilities. The same platform measures diverse metabolite classes and clinical parameters, making it a universal diagnostic tool for cardiovascular disease rather than a disease-specific or marker-specific test.
2Reliability
If no specific biomarkers are used, then the diagnostic method is simple, but the ability to differentiate stable angina from myocardial infarction is poor
Solution Approach 1:
The patent segments the diagnostic approach by categorizing biomarkers into distinct functional groups: metabolites (amino acids like tryptophan and homoserine, fatty acids, lysophosphatidylcholines, phosphatidylcholines) and clinical parameters (white blood cell count, C-reactive protein, cholesterol, glucose, hemoglobin A1c). This segmentation allows the system to evaluate different biological pathways independently while integrating results for comprehensive disease differentiation, improving reliability without requiring an undifferentiated mix of markers.
Solution Approach 2:
The diagnostic system monitors changes in multiple biochemical parameters simultaneously. By measuring the levels of various metabolites and clinical parameters and analyzing their patterns of change, the system can differentiate between stable angina and myocardial infarction. Each biomarker provides information about different aspects of disease pathophysiology, and their combined analysis enhances differentiation accuracy.
3Loss of time
If early diagnosis is pursued, then patient survivability improves, but the availability of specific biomarkers for early detection is limited
Solution Approach 1:
The patent enables preliminary detection of coronary heart disease by measuring metabolite levels that change in the early stages of disease development, before classic symptoms appear. The biomarker panel includes metabolites known to be altered in early atherosclerosis and cardiac stress, allowing the system to detect disease presence and risk before irreversible damage occurs, facilitating preventive treatment.
Data Source
AI summary
The present disclosure relates to a method and a diagnostic kit for diagnosing stable angina and acute myocardial infarction early through simple blood testing and checking of clinical parameters. Unlike conventional diagnostic methods, stable angina can be diagnosed as distinguished from acute myocardial infarction according to the present disclosure by using one diagnostic platform based on the change in the in-vivo levels of biological metabolites having different metabolic pathways and clinical parameters as well as medications affecting the onset and progress of the disease through multivariable analysis.