Sex differences in trajectories of depression symptoms and associations with 10‐year mortality in patients with stroke: the South London Stroke Register
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Depression is a common neuropsychiatric consequence of stroke. We identified trajectories of depression symptoms in men and women and examined their associations with 10-year all-cause mortality. METHODS: Data were obtained from the South London Stroke Register (1998-2016). Socio-demographic, stroke severity and clinical measures were collected during the acute phase. The Hospital Anxiety and Depression Scale was used to screen for depression at 3 months after stroke and then annually. We used group-based trajectory models to identify trajectories of depression and Cox proportional hazards models to study the risk of mortality in them. RESULTS: We studied 1275 men and 1038 women. Three trajectories of depression symptoms were identified in men: I-M (42.12%), low and stable symptoms; II-M (46.51%), moderate increasing symptoms; and III-M (11.37%), severe persistent symptoms. Four trajectories were identified in women; I-F (29.09%), low symptoms; II-F (49.81%), moderate symptoms; III-F (16.28%), severe symptoms; and IV-F (4.82%), very severe symptoms, all with stable symptoms. The 10-year adjusted mortality hazard ratios in men were: 1.68 [95% confidence interval (CI), 1.38-2.04] and 2.62 (95% CI, 1.97-3.48) for trajectories II-M and III-M, respectively, compared with I-M. In women these were: 1.38 (95% CI, 1.09-1.75), 1.65 (95% CI, 1.23-2.20) and 2.81 (95% CI, 1.90-4.16) for trajectories II-F, III-F and IV-F, respectively, compared with I-F. CONCLUSIONS: Depression trajectories varied independent of sex. Severe symptoms in women were double those in men. Moderate symptoms in men became worse over time. Increased symptoms of depression were associated with higher mortality rates. Data on symptom progression may help a better long-term management of patients with stroke.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".