Background: Patients with diabetes mellitus (DM) are at increased risk of acute coronary syndrome (ACS); however, the factors predicting those at highest risk are not well-understood. We identified demographic and standard risk factors that best predict those at high risk based on a multiple biomarker algorithm.
Methods: We studied adults with DM from a clinical registry who had measures of the PULS score (GD Biosciences, Irvine, CA), a biomarker algorithm identifying endothelial damage and predicting 5-year ACS risk consisting of HGF, sFAS, Fas Ligand, Eotaxin, CTACK, MCP3, Il-16, HbA1c, HDL-C, as well as age, sex, DM, and family history of CHD. We identified the proportion of patients with DM at low (<3.5%), intermediate (3.5-<7.5%), and high (≥7.5%) risk of ACS based on PULS. Stepwise logistic regression providing odds ratios and 95% confidence intervals (CIs) examined the relationship of age, gender, and individual risk factors not part of the PULS algorithm with the likelihood of a high risk PULS score.
Results: There were 668 adults with DM (females: 39.5%, ages 30 to 100, mean age 66.5 years). Of these, 6.0% had a low, 12.9% intermediate, and 81.1% high risk PULS score. In the stepwise logistic regression, independent predictors of a high risk PULS score included age, sex, hypertension, body mass index (BMI), and current smoking (table). Other risk factors and biomarkers, including apolipoprotein A-1 (ApoA1), apolipoprotein B (ApoB), ratio ApoB to ApoA1, total or LDL-cholesterol, triglycerides, very low density lipoprotein cholesterol, lipoprotein (a), systolic or diastolic blood pressure, hs-CRP, and small dense LDL were not associated with a high PULS risk score.
Conclusion: We demonstrated that age, male gender, hypertension, BMI, and current smoking are key factors potentially identifying persons with DM at high risk of ACS based on an algorithm identifying endothelial damage. Further validation through prospective studies with actual ACS events are needed.