School-based Streptococcal A Sore-throat Treatment Programs and Acute Rheumatic Fever Amongst Indigenous Māori: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Acute rheumatic fever (ARF) predominantly affects indigenous Māori schoolchildren in Bay of Plenty region, and more so male Māori students, especially when socioeconomically deprived. We evaluated the effectiveness of strategies for reducing ARF with group A streptococcal pharyngitis treatment in 2011-18. METHODS: We retrospectively assessed outcomes of 3 open cohorts of Māori schoolchildren receiving different interventions: Eastern Bay rural Cohort 1, mean deprivation decile 9.80, received school-based sore-throat programs with nurse and general practice (GP) support; Eastern Whakatane township/surrounds Cohort 2, mean deprivation 7.25, GP management; Western Bay Cohort 3, mean deprivation 5.98, received predominantly GP care, but 3 highest-risk schools received school-based programs. Cases were identified from ICD10 ARF-coded hospital discharges, notifications to Ministry of Health, and a secondary-prevention penicillin database. Primary outcomes were first-presentation ARF cohorts' incidence preintervention (2000-10) and postintervention (2011-18) with cases over annual school rolls' Māori students-year denominators. RESULTS: Overall, ARF in Maori schoolchildren declined in the cohorts with school-based programs. Cohort 1 saw a postintervention (2011-18) decline of 60%, 148 to 59/100,000/year, rate ratio (RR) = 0.40(CI 0.22-0.73) P = 0.002. Males' incidence declined 190 to 78 × 100,000/year RR = 0.41(CI 0.19-0.85) P = 0.013 and females too, narrowing gender disparities. Cohort 3 ARF incidence decreased 48%, 50 to 26/100,000/year RR = 0.52(CI 0.27-0.99) P = 0.044. In contrast, ARF doubled in Cohort 2 students with GP-only care without school-based programs increasing 30 to 69/100,000/year RR = 2.28(CI 0.99-5.27) P = 0.047, especially for males 39/100,000/year to 107/100,000/year RR = 2.71(CI 1.00-7.33) P = 0.0405. CONCLUSIONS: School-based programs with indigenous Māori health workers' sore-throat swabbing and GP/Nurse support reduced first-presentation ARF incidence in Māori students in highest-risk settings.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".