Person-centered analysis of psychological traits to explain heterogeneity in patient-reported outcomes of coronary artery disease- the THORESCI study.

BACKGROUND

Heterogeneity in the prognosis of coronary artery disease (CAD) patients may be explained by relatively stable individual psychological differences. Therefore, we studied multiple personality and coping traits using a person-centered approach, and examined the predictive value of this approach for patient-reported outcomes.

METHOD

657 CAD patients (age = 66.39 ± 10.6; 79% men) completed multiple self-report questionnaires focusing on demographics, negative affectivity and social inhibition (DS14), neuroticism and extraversion (EPQ), resilience (DRS-15), and coping styles (CISS) after undergoing percutaneous coronary intervention. Depressive symptoms (PHQ-9), anxiety (GAD-7), and treatment adherence (MOS) were assessed at 6 months follow-up. Clinical information was extracted from patients' medical records.

RESULTS

A step-3 latent class analysis identified four subgroup profiles: Low distress (31%), Passive coping (21%), Active coping (20%), and High distress (28%). For all patient-reported outcomes, overall significant differences between the subgroups were observed (p-values < .05). The High distress profile was associated with the highest levels of emotional distress (d's > .94), and lowest levels of positive mood (d = -1.02) and treatment adherence (d = -2.75) at follow-up. Patients with an Active coping profile also experienced increased emotional distress (d's > .50), but participated in cardiac rehabilitation most often (d = .13), and reported high levels of positive mood (d = -1.02). Patients with a Passive coping profile displayed few emotional problems after six months (d's < .30), but participation to cardiac rehabilitation was relatively low (d = .04).

CONCLUSIONS

This study revealed four distinct psychological latent subgroups, which were predictive of patient-reported outcomes. The results indicate that a person-centered approach is useful in explaining heterogeneity in recovery from PCI, and may enhance personalized medicine in patients with CAD.