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Biopsychosocial Phenogroups in Individuals with Coronary Artery Disease and their Associated Cardiovascular Mortality
Insights
This study identified four distinct patient groups with stable coronary artery disease (CAD), revealing that cardiac autonomic dysfunction and ischemic cardiomyopathy significantly increase mortality risk. These findings highlight the need for personalized CAD management strategies.
Area of Science:
- Cardiology
- Clinical Medicine
- Public Health
Background:
- Stable coronary artery disease (CAD) patients exhibit diverse clinical profiles impacting prognosis.
- Psychosocial, metabolic, and cardiovascular factors vary among stable CAD patients.
- Understanding patient heterogeneity is crucial for predicting cardiovascular disease (CVD) outcomes.
Purpose of the Study:
- To identify distinct clinical phenogroups within stable CAD patient populations.
- To assess the association between identified phenogroups and mortality risk (CVD-specific and all-cause).
- To inform personalized treatment strategies for stable CAD.
Main Methods:
- Pooled data from 949 stable CAD participants.
- Applied model-based clustering using markers of autonomic dysfunction, psychosocial burden, myocardial injury, LV dysfunction, and blood pressure.
- Estimated hazard ratios (HRs) to determine associations between phenogroups and mortality.
Main Results:
- Identified four distinct phenogroups with varying sociodemographic and clinical characteristics.
- Phenogroups 1 (cardiac autonomic dysfunction) and 3 (ischemic cardiomyopathy) showed a 2-10 fold higher risk of CVD-specific and all-cause mortality compared to the low-risk group.
- Phenogroup 4 (high psychosocial burden) exhibited a non-significant increased risk (1.4-2.3 fold) for mortality.
Conclusions:
- Novel phenogroups in stable CAD patients are associated with clinically significant differences in mortality risk.
- Results support a holistic approach to CAD evaluation and management.
- Personalized therapies, including behavioral interventions, may improve patient outcomes.
Background:
Patients with stable coronary artery disease (CAD) represent a clinically heterogeneous group, with varying psychosocial, metabolic, and cardiovascular profiles that may differentially influence prognosis. We sought to identify distinct clinical phenogroups among patients with stable CAD and to evaluate their associations with cardiovascular disease (CVD)-specific and all-cause mortality.
Methods:
We pooled data from 949 participants with stable CAD enrolled in two related studies. To identify distinct clinical phenogroups, we applied a model-based clustering approach using markers of autonomic dysfunction, psychosocial stress burden, myocardial injury and obstructive burden, left ventricular (LV) systolic dysfunction, and blood pressure. All variables were assessed at study enrollment. Hazard ratios (HRs) were estimated to examine the associations between the derived phenotypes and both CVD-specific and all-cause mortality.
Results:
The mean (SD) age of participants was 60 (±10) years; 34% were women and 41% were Black. We identified four phenogroups with differing sociodemographic and clinical profiles. Compared with phenogroup 2 (low-risk factor burden group), phenogroups 1 (cardiac autonomic dysfunction group) and 3 (ischemic cardiomyopathy group) had a 2 to 10-fold higher risk of CVD-specific and all-cause mortality over a median 5 years of follow-up. These associations remained strong and statistically significant in cluster 3 even after adjustment for demographic factors. Phenogroup 4 (high psychosocial burden group) showed a more modest but consistent 1.4 to 2.3-fold higher risk of CVD-specific and all-cause mortality compared with phenogroup 2, though this did not reach statistical significance.
Conclusions:
Our study identified novel phenogroups of CAD patients with clinically meaningful differences in risk for CVD-specific and all-cause mortality. Although more studies are warranted for this first-in-kind study, these results support a holistic model of CAD evaluation, with the promise of improving outcomes through targeted, personalized therapies that include behavioral interventions.
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