Acute rheumatic fever and poststreptococcal reactive arthritis: diagnostic and treatment practices of pediatric subspecialists in Canada.
Bibliographic record
Abstract
OBJECTIVE: We conducted a survey of pediatric specialists in rheumatology, cardiology, and infectious diseases to ascertain present Canadian clinical practice with respect to diagnosis and treatment of acute rheumatic fever (ARF) and poststreptococcal reactive arthritis (PSReA), and to determine what variables influence the decision for or against prophylaxis in these cases. METHODS: A questionnaire comprising 6 clinical case scenarios of acute arthritis occurring after recent streptococcal pharyngitis was sent to members of the Canadian Pediatric Rheumatology Association, and to heads of divisions of pediatric cardiology and pediatric infectious diseases at the 16 university affiliated centers across Canada. RESULTS: There is considerable variability with respect to diagnosis in cases of ReA following group A streptococcal (GAS) infection both within and across specialties. There is extensive variability regarding the decision to provide prophylaxis in cases designated as ARF or PSReA. Findings indicated that physicians are most comfortable prescribing antibiotic prophylaxis in the presence of clear cardiac risk and are less inclined to such intervention for patients diagnosed with PSReA. When prophylaxis was recommended for cases of PSReA, the majority of respondents prescribed longer term courses of antibiotics. CONCLUSION: The lack of observed consistency in diagnosis and treatment in cases of reactive arthritis post-GAS infection likely reflects the lack of universally accepted criteria for diagnosis of PSReA and insufficient longterm data regarding carditis risk within this population. There is a need for clear definitions and treatment guidelines to allow greater consistency in clinical practice across pediatric specialties.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".