Review: depression is associated with an increased risk of stroke in adults
Bibliographic record
Abstract
self-reported scales, and stroke was assessed by death certifi cates or medical records. Most of the studies accounted for age (25 studies), body mass index (14 studies), alcohol intake (nine studies), physical activity (seven studies), and comorbidities (for example diabetes, hypertension and coronary heart disease; 23 studies) in their analyses. Depression was associated with a signifi cantly increased risk of stroke overall (31 studies; HR 1.45, 95% CI, 1.29 to 1.63; heterogeneity p<0.001). Depression was also associated with a signifi cantly increased risk of fatal stroke and ischaemic stroke (fatal stroke: eight studies, HR 1.55, 95% CI 1.25 to 1.93; heterogeneity p=0.31; ischaemic stroke: six studies, HR 1.25, 95% CI 1.11 to 1.40; heterogeneity p=0.34). The associations between depression and non-fatal stoke or haemorrhagic stroke were not signifi cant (non-fatal stroke: three studies, HR 1.21, 95% CI 0.91 to 1.62; heterogeneity p=0.62; haemorrhagic stroke: two studies, HR 1.16, 95% CI 0.80 to 1.70; heterogeneity p=0.65). Depression was estimated to be associated with an additional 106 cases for total stroke, 53 cases for ischaemic stroke and 22 cases for fatal stroke per 100 000 individuals per year in the USA. An estimated 3.9% of strokes in the USA (273 000 strokes) were estimated to be attributable to depression. CONCLUSIONS Depression is associated with a signifi cant increase in the risk of stroke in adults in prospective cohort studies. NOTES Most studies did not have information on depression treatment and antidepressant medication use. Funnel plots indicated a possible publication bias for total stroke, but adding the imputed missing studies to the meta-analysis did not affect the signifi cance of the association between depression and stroke (HR 1.28, 95% CI 1.12 to 1.47).
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".