Functional and Neuroanatomic Correlations in Poststroke Depression
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The purpose of our study was to determine the functional and neuroanatomic correlates of poststroke depressive symptoms. METHODS: Patients with consecutive admissions to a regional stroke center for new-onset unilateral hemispheric stroke who met World Health Organization and National Institute of Neurological and Communicative Disorders and Stroke criteria were eligible for inclusion in a longitudinal study. Acutely, patients underwent CT scanning, and at 3 months and 1 year after stroke, depressive symptoms were assessed by using both the Montgomery-Asberg Depression Rating Scale and the Zung Self-Rating Depression Scale. The Functional Independence Measure (FIM) served as an indication of functional outcome and was obtained at 1 month, 3 months, and 1 year after stroke, along with other demographic information. The Talairach and Tournoux stereotactic atlas was used for the primary determination of CT lesion localization. Lesion proximity to the anterior frontal pole was also measured. RESULTS: Eighty-one patients participated in the longitudinal study. Stepwise linear regression analyses generated a highly significant model (F(3,76)=9.8, R(2)=28%, P<0.0005), with lower 1-month total FIM scores, living at home, and damage to the inferior frontal region predicting higher depression scores at 3 months. Similarly, lower 3-month total FIM scores correlated with higher 3-month depression scores, and lower 1-year total FIM scores correlated with higher 1-year depression scores. CONCLUSIONS: Functional measures correlated with poststroke depression across time and, together with neuroanatomic measures, predicted depressive symptoms longitudinally. Although inferior frontal lesion location, irrespective of side, appeared to play a role as a risk factor in this study, the degree of functional dependence after stroke imparted the greatest risk.
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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) | 0.002 | 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".