Systematic Review: Estimation of global burden of non‐suppurative sequelae of upper respiratory tract infection: rheumatic fever and post‐streptococcal glomerulonephritis
Bibliographic record
Abstract
OBJECTIVES: To establish the incidence of post-streptococcal glomerulonephritis (PSGN) and acute rheumatic fever, the prevalence of rheumatic heart disease (RHD), and to estimate morbidity and mortality caused by these diseases globally. METHODS: Systematic literature review and review of World Health Organisation (WHO) vital registration data (VRD). RESULTS: Incidence and prevalence of rheumatic fever and RHD show very significant global variation. The greatest burden was found in sub-Saharan Africa, the lowest in North America. The highest mortality rates from these two diseases were reported in the indigenous populations of Australia (23.8 per 100,000). Among countries with VRD, the highest mortality was found in Mauritius (4.32 per 100,000). A few studies reported mortality from PSGN and these reported low mortality rates (mean 0.028 per 100,000 in developing countries). CONCLUSION: Lack of data from key parts of the world limits our ability to make precise statements of disease burden. Further research and surveillance is required to generate more primary data to inform future estimates.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".