Management of Wheezy Preschoolers in the Emergency Department: A Discrete Choice Experiment.
Bibliographic record
Abstract
OBJECTIVES: This study aimed to elicit pediatric emergency physician's treatment choices for preschool-aged children with wheeze, determine the characteristics of the presenting child that influence treatment choices, and determine whether there is clinical equipoise by eliciting physician willingness to enroll these children in a placebo-controlled trial of corticosteroids. METHODS: Discrete choice experiments varying the characteristics of the presenting child were designed to elicit Canadian emergency physician's treatment choices, both in the emergency department (ED) and at discharge, for young children presenting with wheeze and their willingness to enroll in a randomized controlled trial (RCT). RESULTS: Most physicians chose to treat children with albuterol both in the ED and at discharge for all clinical scenarios. The proportion of physicians who chose to treat children with oral corticosteroids both in the ED and at discharge varied widely (from 12% to 81%) across all scenarios. Physician preference whether preschool children with wheeze should be treated with corticosteroids varied depending on the child's age, history of atopy, and previous and continuous wheeze. Between 73% and 86% of physicians were willing to enroll these children in an RCT indicating clinical equipoise. CONCLUSIONS: Physician treatment choices varied widely indicating clinical equipoise as to the effectiveness of corticosteroids in this population of patients. Management choices with respect to albuterol and corticosteroids were not consistent with published national and international guidelines. In line with this finding, physician's considerable willingness to enroll these children in an RCT may suggest that they are seeking guidance on how to manage these patients.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".