Acute rheumatic fever in First Nations communities in northwestern Ontario: Social determinants of health "bite the heart".
Bibliographic record
Abstract
OBJECTIVE: To document a case series of 8 young First Nations patients diagnosed with acute rheumatic fever (ARF), a preventable disease that resulted in the death of 2 patients, in northwestern Ontario in the context of late diagnosis, overcrowded housing, and inadequate public health response. DESIGN: Retrospective case series over an 18-month period. SETTING: Remote First Nations communities in northwestern Ontario. PARTICIPANTS: Eight patients with ARF. MAIN OUTCOME MEASURES: Incidence, mortality, residual rheumatic heart disease, time to diagnosis, barriers to diagnosis and treatment, housing situation of patients, patient demographic characteristics (age, sex), and investigation results. RESULTS: The incidence of ARF in this population was 21.3 per 100,000, which is 75 times greater than the overall Canadian estimated incidence. The average patient age was 9.4 years. Most cases developed joint findings, and 5 of the surviving patients had rheumatic heart disease when they received echocardiography. The average time to diagnosis was 88 days. Two 4-year-old children died from ARF. Most patients lived in inadequate and crowded housing. CONCLUSION: This rare disease still exists in remote First Nations communities. These communities demonstrate an incidence equal to that in aboriginal communities in Australia and New Zealand, which have among the highest international incidence of ARF. Primordial prevention, including improved on-reserve housing, is urgently needed. Case detection and ongoing surveillance for primary and secondary prophylaxis requires a well resourced regional strategy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".