Abstract
Abstract
Aim
Patients with stable coronary artery disease (CAD) are clinically heterogeneous and exhibit differential treatment responses. We aimed to identify distinct CAD phenogroups based on psychosocial, autonomic, and cardiovascular characteristics and to examine their risk of adverse cardiovascular events.
Methods
We pooled data from 949 participants with stable CAD enrolled in two related studies. Phenogroups were derived using Gaussian mixture model clustering applied to 12 prespecified markers readily obtainable in ambulatory clinical settings: autonomic dysfunction, psychosocial stress, myocardial injury, obstructive CAD burden, left ventricular ejection fraction, and blood pressure. Hazard ratios (HRs) were estimated to examine the associations between the derived phenogroups and composite major adverse cardiovascular events (MACE), cardiovascular disease (CVD)-specific, and all-cause mortality.
Results
The mean age was 60±10 years; 34% were women and 41% were Black. Four phenogroups were identified: phenogroup 1 (n=257), the “low-risk cluster”; phenogroup 2 (n=387, most prevalent), the “psychosocial stress-angina cluster”; phenogroup 3 (n=142), the “autonomic dysfunction cluster”; and phenogroup 4 (n=163), the “ischemic cardiomyopathy cluster”. Compared with the low-risk cluster, the ischemic cardiomyopathy cluster had the highest risk of composite MACE (HR, 2.93; 95% CI, 1.80- 4.78), followed by the autonomic dysfunction cluster (MACE HR, 2.07; 95% CI, 1.21- 3.53) and the psychosocial stress-angina cluster (HR, 1.65; 95% CI, 1.04- 2.61). Similar associations were observed for CVD-specific and all-cause mortality.
Conclusions
Psychosocial and autonomic factors, when combined with cardiovascular risk characteristics, result in clinically meaningful CAD phenogroups with varying risk of adverse cardiovascular events that may help guide personalized interventions.