Time‐series Analysis of Ondansetron Use in Pediatric Gastroenteritis
Bibliographic record
Abstract
OBJECTIVE: Emergency department use of ondansetron in children with gastroenteritis is increasing; however, its effect on clinical outcomes is unknown. We aimed to determine whether increasing ondansetron usage is associated with improved outcomes in children with gastroenteritis. METHODS: A retrospective cohort study was conducted at The Hospital for Sick Children, Toronto, Canada. Eligible children included those younger than 18 years old with gastroenteritis who presented to an emergency department between 2003 and 2008. There were 22,125 potentially eligible visits; 20% were selected at random for chart review. The primary outcome measure, the intravenous rehydration rate, was evaluated using an interrupted time-series analysis with segmented logistic regression. Secondary outcomes included emergency department revisits, hospitalization, and length of stay. RESULTS: A total of 3508 patient visits were included in the final analysis. During the study period, there was a significant reduction in intravenous rehydration usage (27%-13%; P < 0.001) and an increase in ondansetron administration (1%-18%; P < 0.001). Time-series analysis demonstrated a level break (P = 0.03) following the introduction of ondansetron. The mean length of stay for children declined from 8.6 ± 3.4 to 5.9 ± 2.8 hours, P = 0.03. During the week following the index visit, there was a reduction in return visits (18%-13%; P = 0.008) and need for intravenous rehydration (7%-4%; P = 0.02). CONCLUSIONS: Ondansetron use has increased significantly and is associated with reductions in the use of intravenous rehydration, emergency department revisits, and length of stay. The selective use of ondansetron is associated with improved clinical outcomes.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".