Trajectory classes of post-stroke depression severity and their baseline predictors: A multi-cohort replication study

Area of Science:

• Neurology
• Psychiatry
• Epidemiology

Background:

• Post-stroke depression (PSD) impacts one-third of stroke survivors, worsening outcomes.
• Current PSD research often treats it as binary, missing symptom variability.
• Understanding PSD trajectories is crucial for effective rehabilitation and patient care.

Purpose of the Study:

• To identify consistent longitudinal depression trajectories post-stroke.
• To examine baseline predictors associated with different PSD trajectories.
• To reveal heterogeneity in PSD symptom patterns across diverse cohorts.

Main Methods:

• Latent class growth analysis applied to three independent Stroke and Cognition Consortium (STROKOG) cohorts (n=750).
• Depressive symptoms assessed using Geriatric Depression Scale (GDS-15) and Hamilton Depression Rating Scale (HAMD-17).
• Analyses conducted within cohorts and on pooled datasets to ensure replicability.

Main Results:

• A consistent three-class trajectory solution emerged: No Depression, Mild Remitting, and Moderate (stable or improving).
• No Depression class comprised 58-83% of participants.
• Mild Remitting (14-29%) and Moderate (4-13%) classes showed varying symptom persistence and resolution patterns.

Conclusions:

• Post-stroke depression exhibits a robust three-trajectory structure across diverse settings and measures.
• Baseline cognitive impairment predicts mild, remitting depression.
• Identifying early clinical factors (cognition, sex, vascular risks) can target interventions for persistent PSD.