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Published on: August 9, 2024
Usefulness of a Coronary Artery Disease Predictive Algorithm to Predict Global Risk for Cardiovascular Disease and
Masood Younus1, Wenjun Fan1, Douglas S Harrington2
1Heart Disease Prevention Program, Division of Cardiology University of California, Irvine School of Medicine, Irvine, California.
Insights
A new algorithm, CADPA, identifies patients at high risk for acute coronary syndrome (ACS) who are missed by traditional assessments. This predictive tool uses biomarkers to find individuals who may benefit from early intervention.
Area of Science:
- Cardiovascular Disease Research
- Biomarker Discovery
- Predictive Analytics in Medicine
Background:
- Traditional cardiovascular disease risk assessments often misclassify patients, failing to identify those at high risk for acute coronary syndrome (ACS).
- A significant portion of individuals deemed low or intermediate risk are, in reality, susceptible to ACS.
Purpose of the Study:
- To evaluate a novel coronary artery disease predictive algorithm (CADPA) for its accuracy in identifying patients at discordantly high risk for ACS.
- To assess the predictive value of specific biomarkers related to endothelial damage and repair in cardiovascular risk stratification.
Main Methods:
- The study examined the CADPA, incorporating 9 biomarkers (e.g., hepatocyte growth factor, interleukin-16, Fas Ligand) and clinical factors (age, gender, diabetes, family history).
- Patients were categorized by global risk assessment and then re-evaluated using CADPA to identify discordantly high-risk individuals.
- Statistical analysis determined the predictive power of individual biomarkers for discordance.
Main Results:
- CADPA identified 34% of low-risk and 72% of intermediate-risk patients as having a discordantly high risk for ACS.
- Discordantly high-risk patients were predominantly male and older.
- Interleukin-16, Fas Ligand, hepatocyte growth factor, soluble FAS, cutaneous T cell-attracting chemokine, and eotaxin were significant predictors of discordance.
Conclusions:
- The CADPA algorithm effectively identifies a high-risk ACS patient subgroup missed by conventional methods.
- This endothelial injury biomarker-based approach offers potential for improved cardiovascular risk stratification.
- Further prospective studies are needed to validate CADPA's causal relation to cardiovascular events and its clinical utility.
Abstract:
Traditional global risk assessment for cardiovascular disease fails to identify a significant percentage of the population initially classified at low or intermediate risk of cardiovascular disease that are actually at high risk for acute coronary syndrome (ACS). We examined a coronary artery disease predictive algorithm (CADPA) that includes 9 biomarkers involved in the pathogenesis of atherosclerosis initiated by endothelial damage and repair (hepatocyte growth factor, soluble FAS, Fas ligand, eotaxin, cutaneous T cell-attracting chemokine, monocyte chemotactic protein-3, interleukin-16, hemoglobin A1c, high-density lipoprotein-cholesterol), in addition to age, gender, diabetes, and family history of myocardial infarction that more accurately predicts 5-year risk of ACS to identify the patient population at discordantly high risk. We found that 34% of patients at low risk by global risk assessment and 72% of patients at intermediate risk by global risk assessment were actually at discordantly high risk for ACS. This patient population was disproportionately male and older in age. The biomarkers (per standard deviation) that most predicted the odds (95% confidence levels) of discordance were interleukin-16 (2.59 [2.21 to 3.03]), Fas Ligand (0.50 [0.43 to 0.57]), hepatocyte growth factor (1.72 [1.50 to 1.98]), soluble FAS (2.19 [1.86 to 2.58]), cutaneous T cell-attracting chemokine (0.46 [0.40 to 0.53]), and eotaxin (1.78 [1.56 to 2.03]), in addition to age, HbA1c, low-density lipoprotein-cholesterol, and glycated hemoglobin. In conclusion, although future prospective study validation is needed to establish a causal relation between CADPA and cardiovascular events, our study defines a patient population considered low to intermediate risk by conventional clinical evaluation, but who is at discordantly high risk indicated by the endothelial injury serum biomarker algorithm CADPA and may benefit from further evaluation and medical management.
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