Depression is prevalent among patients with congestive heart failure (CHF) and is associated with increased mortality and healthcare use. However, most research on this association has focused on high-income countries, leaving a gap in knowledge regarding the relationship between depression and CHF in low-to-middle-income countries.

To identify changes in depressive symptoms and potential risk factors for poor outcomes among CHF patients.

Longitudinal data from 783 patients with CHF from public hospitals in Karachi, Pakistan, were analysed. Depressive symptom severity was assessed using the Beck Depression Inventory. Baseline and 6-month follow-up Beck Depression Inventory scores were clustered using Gaussian mixture modelling to identify separate depressive symptom subgroups and extract trajectory labels. Further, a random forest algorithm was used to determine baseline demographic, clinical and behavioural predictors for each trajectory.

Four separate patterns of depressive symptom changes were identified: ‘good prognosis’, ‘remitting course’, ‘clinical worsening’ and ‘persistent course’. Key factors related to these classifications included behavioural and functional factors such as quality of life and disability, as well as the clinical severity of CHF. Specifically, poorer quality of life and New York Heart Association (NYHA) class 3 symptoms were linked to persistent depressive symptoms, whereas patients with less disability and without NYHA class 3 symptoms were more likely to exhibit a good prognosis.

By examining the progression of depressive symptoms, clinicians can better understand the factors influencing symptom development in patients with CHF and identify those who may require closer monitoring and appropriate follow-up care.