A Randomized Trial of a Single Dose of Oral Dexamethasone for Mild Croup
Bibliographic record
Abstract
BACKGROUND: The benefits of dexamethasone treatment for moderate-to-severe croup are well established. However, most children with croup have mild symptoms, and it is unknown whether they would derive the same degree of benefit from dexamethasone treatment as children with more severe disease. METHODS: We conducted a double-blind trial at four pediatric emergency departments in which 720 children with mild croup were randomly assigned to receive one oral dose of either dexamethasone (0.6 mg per kilogram of body weight) or placebo. The children had mild croup, as defined by a score of < or =2 on the croup scoring system of Westley et al. The primary outcome was a return to a medical care provider for croup within seven days after treatment. The secondary outcome was the presence of ongoing symptoms of croup on days 1, 2, and 3 after treatment. Other outcomes included economic costs, hours of sleep lost by the child, and stress on the part of the parent in relation to the child's illness. RESULTS: Baseline clinical characteristics were similar in the two groups. Return to medical care was significantly lower in the dexamethasone group (7.3 percent vs. 15.3 percent, P<0.001). In the dexamethasone group, there was quicker resolution of croup symptoms (P=0.003), less lost sleep (P<0.001), and less stress on the part of the parent (P<0.001). CONCLUSIONS: For children with mild croup, dexamethasone is an effective treatment that results in consistent and small but important clinical and economic benefits. Although the long-term effects of this treatment are not known, our data support the use of dexamethasone in most, if not all, children with croup.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".