A longitudinal study of depressive symptom trajectories and risk factors in congestive heart failure

BackgroundDepression is prevalent among patients with congestive heart failure (CHF) and is associated with increased mortality and healthcare utilization. However, most research has focused on high-income countries, leaving a gap in knowledge regarding the relationship between depression and CHF in low-to-middle-income countries (LMICs). This study aimed to delineate depressive symptom trajectories and identify potential risk factors for poor outcomes among CHF patients. MethodsLongitudinal data from 783 patients with CHF from public hospitals in Karachi, Pakistan was analyzed. Depressive symptom severity was assessed using the Beck Depression Inventory (BDI). Baseline and 6-month follow-up BDI scores were clustered through Gaussian Mixture Modeling to identify distinct depressive symptom subgroups and extract trajectory labels. Further, a random forest algorithm was utilized to determine baseline demographic, clinical, and behavioral predictors for each trajectory. ResultsFour depressive symptom trajectories were identified: good prognosis, remitting course, clinical worsening, and persistent course. Risk factors associated with persistent depressive symptoms included lower quality of life and the New York Heart Association (NYHA) class 3 classification of CHF. Protective factors linked to a good prognosis included less disability and a non-NYHA class 3 classification of CHF. ConclusionsBy identifying key characteristics of patients at heightened risk of depression, clinicians can be aware of risk factors and better identify patients who may need greater monitoring and appropriate follow-up care. Clinical Perspective What is new?O_LITo the best of our knowledge, this is the first study to use machine learning techniques to investigate depressive symptom trajectories in CHF patients from an LMIC. C_LIO_LIFour distinct depressive symptom trajectories were identified, ranging from good prognosis to persistent depressive symptoms. C_LIO_LIThis study highlights protective and risk factors associated with these trajectories based on patients demographics and clinical presentations at baseline. C_LI What are the clinical implications?O_LIPersonalized interventions based on identified protective factors for high-risk CHF patients could enhance both mental health and cardiovascular outcomes. C_LIO_LIEarly detection and management of depression, particularly in patients with poor quality of life or advanced heart failure, may help reduce healthcare utilization and mortality. C_LIO_LIThis study emphasizes the importance of routine depression screening in CHF patients, especially in LMICs, to enhance overall patient care and outcomes. C_LI