E.1 Clinical outcomes of ischemic stroke in indigenous populations – a systematic review and metanalysis
Bibliographic record
Abstract
Background: The burden and outcome of stroke in indigenous populations is less well understood. This review evaluates ischemic stroke outcomes in indigenous populations as compared to the general population in the context of recent advances in ischemic stroke therapy. Methods: The OVID Medline and EMBASE databases were searched for this review. Clinical outcome was measured using standardized outcome scale (eg. mRS) at 90 days following stroke intervention in indigenous as compared to non-indigenous adult populations. Results: 897 studies were identified, with 4 studies included in the final analysis. A total of (n=68895) patients were included who underwent thrombolysis. Study populations from Australia, New Zealand, United States and Canada comprised of (n=2012) indigenous patients. Mortality was significantly higher in indigenous populations as compared to non-indigenous (Odds Ratio-1.28, 95% CI-1.12; 1.46). The odds ratios of atrial fibrillation (1.26, 95% CI-1.12;– 1.41), diabetes (1.43, 95% CI- 1.27; 1.62), hypertension (1.33, 95% CI- 1.17; 1.51) and IHD (0.71, 95% CI- 0.62; 0.81) in indigenous patients was significantly higher than in non-indigenous patients. Conclusions: Indigenous populations undergoing stroke therapy are at a significantly increased risk of mortality as compared to non-indigenous populations. Comorbidities including diabetes, atrial fibrillation and hypertension are more prevalent in indigenous populations.
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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 | 0.014 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.021 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".