Postoperative outcomes for Indigenous Peoples in Canada: a systematic review
Bibliographic record
Abstract
Background: Substantial health inequities exist for Indigenous Peoples in Canada. The remote and distributed population of Canada presents unique challenges for access to and use of surgery. To date, the surgical outcome data for Indigenous Peoples in Canada have not been synthesized. Methods: We searched 4 databases to identify studies comparing surgical outcomes and utilization rates of adults of First Nations, Inuit or Métis identity with non-Indigenous people in Canada. Independent reviewers completed all stages in duplicate. Our primary outcome was mortality; secondary outcomes included utilization rates of surgical procedures, complications and hospital length of stay. We performed meta-analysis of the primary outcome using random effects models. We assessed risk of bias using the ROBINS-I tool. Results: Twenty-eight studies were reviewed involving 1 976 258 participants (10.2% Indigenous). No studies specifically addressed Inuit or Métis populations. Four studies, including 7 cohorts, contributed adjusted mortality data for 7135 participants (5.2% Indigenous); Indigenous Peoples had a 30% higher rate of death after surgery than non-Indigenous patients (pooled hazard ratio 1.30, 95% CI 1.09–1.54; I2 = 81%). Complications were also higher for Indigenous Peoples, including infectious complications (adjusted OR 1.63, 95% CI 1.13–2.34) and pneumonia (OR 2.24, 95% CI 1.58–3.19). Rates of various surgical procedures were lower, including rates of renal transplant, joint replacement, cardiac surgery and cesarean delivery. Interpretation: The currently available data on postoperative outcomes and surgery utilization rates for Indigenous Peoples in Canada are limited and of poor quality. Available data suggest that Indigenous Peoples have higher rates of death and adverse events after surgery, while also encountering barriers accessing surgical procedures. These findings suggest a need for substantial re-evaluation of surgical care for Indigenous Peoples in Canada to ensure equitable access and to improve outcomes. Protocol registration: PROSPERO-CRD42018098757
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".