Modeling Long-Term Depression Trajectories After Spinal Cord Injury Using Irregularly Sampled Assessments and Rehabilitation Baseline Predictors

Abstract

Purpose

To identify and characterize latent trajectories of depression using growth mixture modeling (GMM) applied to irregularly timed assessments spanning up to 20 years post-injury, examine baseline rehabilitation variables significantly associated with trajectory membership, and determine predictors of sustained depressive burden.

Methods

This retrospective observational cohort study included adults with traumatic or non-traumatic spinal cord injury admitted for inpatient rehabilitation within 3 months post-injury (2005–2023), with follow-up extending until May 2025. Depressive symptoms were assessed using the Hospital Anxiety and Depression Scale (HADS-D) at admission, discharge, and follow-up, totaling 3,258 assessments (n = 679 patients). GMM identified latent trajectories while accommodating irregularly spaced assessments. Predictors of trajectory membership were analyzed through multivariable regression with quantified model discrimination.

Results

A 3-class GMM solution provided optimal fit (entropy=0.75). Most participants (81.6%) followed a stable low-depression trajectory (Class 1). A borderline depression trajectory (Class 2; 8.4%) remained persistently elevated, while a probable depression trajectory (Class 3; 10.0%) displayed delayed worsening peaking at 5–7 years post-injury. Class 3 included a significantly higher proportion of non-traumatic injuries (63%) and females (44.1%), with most patients (85.3%) showing no depressive symptoms during rehabilitation, but later exhibiting a marked increase in depressive burden. Logistic regression predicting Class 2 achieved good discrimination (AUC=0.81; 95% CI, 0.65–0.97), identifying baseline depressive symptoms, tetraplegia, female sex, and primary level of education as significant predictors.

Conclusions

Irregularly sampled follow-ups revealed distinct depression trajectories, including delayed-onset risk. Findings emphasize early rehabilitation-based screening and long-term monitoring to target follow-up and psychological support.

Keywords

spinal cord injuries depression longitudinal studies latent class analysis regression analysis retrospective studies

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