Abstract:

Objective: This study aimed to identify the latent profiles of early postoperative symptom burden among patients with acute coronary syndrome (ACS) following percutaneous coronary intervention (PCI) and to examine the differences in clinical characteristics across these profiles. Method: A convenience sample of 261 ACS patients after PCI was recruited from a tertiary hospital in Chongqing, China. Data were collected using a demographic and clinical information questionnaire, the Cardiac Symptom Survey, and the Seattle Angina Questionnaire (SAQ). Latent profile analysis (LPA) was conducted to identify subgroups of symptom burden. Univariate analyses and multivariate logistic regression were used to determine factors associated with profile membership. Results: Four distinct symptom-burden profiles emerged: a low-symptom group (54.8%), a low-dyspnea/high-chest-tightness group (14.6%), a high-dyspnea/low-chest-tightness group (14.9%), and a high-symptom group (15.7%). Significant differences among the four groups were observed in age, educational level, number of stents implanted, Killip classification, and the SAQ domains of physical limitation and angina frequency (all ps < .05). Multivariate logistic regression indicated that age lower than 65 years was an independent protective factor for belonging to the low-symptom group (OR = 0.195, 0.239), whereas lower educational attainment (primary school or below) was an independent risk factor for higher symptom burden (OR = 2.939). Killip class I was protective for membership in the high-dyspnea/low-chest-tightness group (OR = 0.354). The number of stents implanted did not independently predict profile membership. Conclusion: Younger age (< 65 years) and Killip class I serve as protective factors for lower symptom burden following PCI among patients with ACS, whereas low educational level increases symptom burden risk. Symptom burden in this population is heterogeneous, underscoring the need for stratified management and precision-based clinical interventions tailored to distinct symptom profiles.