Front Cardiovasc Med. 2026 Jul 20;13:1841870. doi: 10.3389/fcvm.2026.1841870. eCollection 2026.
ABSTRACT
BACKGROUND: The first 2-3 months after discharge for acute or decompensated chronic heart failure (HF) constitute a “vulnerable phase” marked by high risks of rehospitalization and death. Symptom fluctuations during this period may be associated with adverse outcomes, yet evidence on post-discharge symptom trajectories is limited. This study applied a latent class trajectory model to characterize KCCQ symptom evolution and its association with early cardiovascular events.
METHODS: In this prospective cohort study, 1,109 patients with chronic HF admitted to a tertiary hospital in Nanchang, China (August 2020-July 2025), completed the Kansas City Cardiomyopathy Questionnaire (KCCQ) at six time points: day 3 after admission, at discharge, and 1, 2, 3, and 6 months post-discharge. Symptom trajectories were identified using latent class trajectory modeling. Associations between trajectory groups and major adverse cardiovascular events (MACEs) were analyzed using multivariable logistic regression, and an exploratory mediation analysis was conducted to examine whether trajectory patterns partly accounted for the association between KCCQ scores and MACEs.
RESULTS: During follow-up, 207 patients (18.7%) experienced MACEs. Latent class trajectory analysis identified four distinct groups: persistently declining, slowly improving, stable-moderate, and stable-high. Relative to the stable-moderate group, patients in the persistently declining group had higher odds of MACEs (OR = 2.242, 95% CI: 1.073-4.718, P = 0.032). The exploratory mediation analysis suggested a statistically significant indirect association through trajectory patterns (β=-0.007, P < 0.001).
CONCLUSIONS: Symptom recovery after HF hospitalization is heterogeneous and was associated with cardiovascular outcomes. Persistently worsening symptoms predict the highest risk, while stable or improving trajectories indicate favorable recovery. Tracking KCCQ trajectories may support early risk stratification and personalized management during the vulnerable phase.
PMID:42548830 | PMC:PMC13429835 | DOI:10.3389/fcvm.2026.1841870
