The Treatment of Pediatric Gastroenteritis: A Comparative Analysis of Pediatric Emergency Physicians’ Practice Patterns
Bibliographic record
Abstract
OBJECTIVES: Acute gastroenteritis is a very common emergency department (ED) diagnosis accounting for greater than 1.5 million outpatient visits and 200,000 hospitalizations annually among children in the United States. Although guidelines exist to assist clinicians, they do not clearly address topics for which evidence is new or limited, including the use of antiemetic agents, probiotics, and intravenous (IV) fluid rehydration regimens. This study sought to describe the ED treatments administered to children with acute gastroenteritis and to compare management between Canadian and U.S. physicians practicing pediatric emergency medicine (PEM). METHODS: Members of PEM research networks located in Canada and the United States were invited to participate in a cross-sectional, Internet-based survey. Participants were included if they are attending physicians and provide care to patients <18 years of age in an ED. RESULTS: In total, 235 of 339 (73%) eligible individuals responded. A total of 103 of 136 Canadian physicians (76%) report initiating oral rehydration therapy (ORT) in children with moderate dehydration, compared with 44 of 94 (47%) of their U.S. colleagues (p<0.001). The latter more often administer antiemetic agents to children with vomiting (67% vs. 45%; p=0.001). American physicians administer larger IV fluid bolus volumes (p<0.001) and over shorter time periods (p=0.001) and repeat the fluid boluses more frequently (p<0.001). Probiotics are routinely recommended by only 35 of 230 respondents (15%). CONCLUSIONS: The treatment of pediatric gastroenteritis varies by geographic location and differs significantly between Canadian and American PEM physicians. Oral rehydration continues to be underused, particularly in the United States. Probiotic use remains uncommon, while ondansetron administration has become routine. Children frequently receive IV rehydration, with the rate and volume administered being greater in the United States.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".