Ophthalmologic care for Indigenous Canadians
Bibliographic record
Abstract
Introduction Indigenous Canadians (IC) experience inequities in eye care. Identification of these inequities may inform the development of culturally appropriate interventions. Methods For this review, a literature search of Ovid Medline, Ovid Embase, CINAHL – EBSCO and Scopus from inception to January 24, 2024 was conducted. Studies were screened by two independent reviewers, and conflicts were resolved through discussion with a third reviewer. Results IC have a greater burden but lower likelihood of being screened for diabetic retinopathy (DR). Barriers to DR care include poor access and racism; enablers include supportive interactions, culturally sensitive programming, and the inclusion of Indigenous staff. IC have less access to cataract surgery and post-operative follow-up due to geographic, economic, and cultural factors. Inuit people have the highest global rates of angle-closure glaucoma. Tele-glaucoma may reduce the time to treatment for open-angle glaucoma. Compared to non-IC, uveitis in IC occurs at a younger age, is more often bilateral and granulomatous with pan-uveal involvement, in part because Vogt Koyanagi Harada is more common in IC. Uncorrected refractive errors , conjunctival papilloma , epiblepharon, and spheroidal keratopathy may disproportionally affect IC. Conclusions Barriers to ophthalmic care for IC persist in both rural and urban settings. Health care should be culturally appropriate, integrated with primary care and incorporate tele-ophthalmology if needed. Holistic care at Indigenous-led centres is ideal.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".