Depressive Symptoms Profiles and Cognitive Outcomes After Stroke
Bibliographic record
Abstract
INTRODUCTION: Post-stroke depressive symptoms are heterogeneous and variably associated with other psycho-cognitive features. We employed cluster analysis to identify distinct profiles of post-stroke depressive symptomatology and their association with cognitive performance. METHODS: We included consecutive patients undergoing neuropsychiatric evaluation 6 months after stroke. Cluster analysis incorporated the Center for Epidemiologic Studies Depression Scale, along with the apathy and anxiety items from the Neuropsychiatric Inventory questionnaire. Baseline clinical/neuroimaging variables and 6-months cognitive outcomes were compared across profiles. RESULTS: We included 189 patients with acute cerebrovascular events (median age 75.4 years, 62% male, 80% ischemic strokes). Three profiles emerged: (A) low-depressive symptoms (n = 108), (B) moderate-depressive symptoms plus anxiety (n = 41), (C) high-depressive symptoms plus apathy (n = 40). Regarding baseline predictors of 6-month depressive symptoms profiles, patients with high-depressive symptoms plus apathy exhibited lower Montreal Cognitive Assessment scores at baseline (16.0 vs. 21.5; adjusted odds ratio [adj.OR] per 1-point increase 0.91, 95% confidence interval [95% CI] 0.83-0.99) compared to patients with low-depressive symptoms; moderate-depressive symptoms plus anxiety patients had less cortical atrophy compared to both low-depressive symptoms (adj.OR 0.92, 95% CI 0.86-0.99) and high-depressive symptoms plus apathy (adj.OR 0.89, 95% CI 0.81-0.97) profiles. Regarding 6-month cognitive performance, high-depressive symptoms plus apathy patients showed higher rates of post-stroke dementia and attention/executive function impairment compared with the two other groups (both p < 0.05), and higher rates of language impairment compared with low-depressive symptoms profile (p < 0.05). CONCLUSION: By integrating apathy and anxiety in our model, depressive symptoms after stroke emerged as heterogeneous neuropsychiatric syndromes, showing different baseline predictors and distinctive cognitive patterns.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".