Ninety‐Day Stroke Recurrence in Minor Stroke: Systematic Review and Meta‐Analysis of Trials and Observational Studies
Bibliographic record
Abstract
Background Risk of recurrence after minor ischemic stroke is usually reported with transient ischemic attack. No previous meta‐analysis has focused on minor ischemic stroke alone. The objective was to evaluate the pooled proportion of 90‐day stroke recurrence for minor ischemic stroke, defined as a National Institutes of Health Stroke Scale severity score of ≤5. Methods and Results Published papers found on PubMed from 2000 to January 12, 2021, reference lists of relevant articles, and experts in the field were involved in identifying relevant studies. Randomized controlled trials and observational studies describing minor stroke cohort with reported 90‐day stroke recurrence were selected by 2 independent reviewers. Altogether 14 of 432 (3.2%) studies met inclusion criteria. Multilevel random‐effects meta‐analysis was performed. A total of 6 randomized controlled trials and 8 observational studies totaling 45 462 patients were included. The pooled 90‐day stroke recurrence was 8.6% (95% CI, 6.5–10.7), reducing by 0.60% (95% CI, 0.09–1.1; P =0.02) with each subsequent year of publication. Recurrence was lowest in dual antiplatelet trial arms (6.3%, 95% CI, 4.5–8.0) when compared with non‐dual antiplatelet trial arms (7.2%, 95% CI, 4.7–9.6) and observational studies 10.6% (95% CI, 7.0–14.2). Age, hypertension, diabetes, ischemic heart disease, or known atrial fibrillation had no significant association with outcome. Defining minor stroke with a lower National Institutes of Health Stroke Scale threshold made no difference – score ≤3: 8.6% (95% CI, 6.0–11.1), score ≤4: 8.4% (95% CI, 6.1–10.6), as did excluding studies with n<500%–7.3% (95% CI, 5.5–9.0). Conclusions The risk of recurrence after minor ischemic stroke is declining over time but remains important.
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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 | 0.028 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.042 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".