A National Prospective Surveillance Study of Acute Rheumatic Fever in Australian Children
Bibliographic record
Abstract
BACKGROUND: Acute rheumatic fever (ARF) is an important cause of heart disease in Indigenous people of northern and central Australia. However, little is known about ARF in children across all Australian population groups. This national prospective study was conducted to determine patterns of disease, and populations and regions at highest risk. METHODS: The Australian Paediatric Surveillance Unit surveillance model was used to collect data on children with ARF across Australia. Children up to 15 years of age were included if they had an ARF episode diagnosed between October 1, 2007 and December 31, 2010 that met the case definition. RESULTS: ARF was identified in 151 children: 131 Indigenous Australians, 10 non-Indigenous Australians, 8 Pacific Islanders and 1 African (1 unknown). Common presenting features were joint symptoms, fever and carditis. Sydenham chorea was reported in 19% of children. Aseptic monoarthritis was a major manifestation in 19% of high-risk children. Seven non-Indigenous Australian children presented with classic, highly specific features compared with 23% of high-risk children, suggesting that subtle presentations of ARF are being missed in non-Indigenous children. Recent sore throat was reported in 33% of cases, including 25% of remote Indigenous children. There were delays in presentation to care and referral to higher-level care across urban/rural and remote areas. CONCLUSIONS: ARF may be more common than previously thought among low-risk children. These data should prompt an awareness of ARF diagnosis and management across all regions, including strategies for primary prevention. There should be renewed emphasis on treatment of sore throat in high-risk groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".