Choosing Wisely: The American College of Rheumatology's Top 5 for Pediatric Rheumatology
Bibliographic record
Abstract
OBJECTIVE: To create a pediatric rheumatology Top 5 list as part of the American Board of Internal Medicine Foundation's Choosing Wisely campaign. METHODS: Delphi surveys of a core group of representative pediatric rheumatology providers from across North America generated candidate Top 5 items. Items with high content agreement and perceived to be of prevalent use and of high impact were included in a survey of all American College of Rheumatology (ACR) members who identified themselves as providing care to pediatric patients. Items with the highest ratings were subjected to literature review and further evaluation. RESULTS: A total of 121 candidate items were proposed in the initial Delphi survey and were reduced to 28 items in subsequent surveys. These 28 items were sent to 1,198 rheumatology providers who care for pediatric patients, and 397 (33%) responded. Based upon survey data and literature review, the Top 5 items were identified. These items focused on testing for antinuclear antibodies, autoantibody panels, Lyme disease, methotrexate toxicity monitoring, and use of routine radiographs. CONCLUSION: The ACR pediatric rheumatology Top 5 is one of the first pediatric subspecialty-specific Choosing Wisely Top 5 lists and provides an opportunity for patients and providers to discuss appropriate use of health care in pediatric rheumatology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".