Treatment in the pediatric emergency department is evidence based: a retrospective analysis
Bibliographic record
Abstract
BACKGROUND: Our goal was to quantify the evidence that is available to the physicians of a pediatric emergency department (PED) in making treatment decisions. Further, we wished to ascertain what percentage of evidence for treatment provided in the PED comes from pediatric studies. METHODS: We conducted a retrospective chart review of randomly selected patients seen in the PED between January 1 and December 31, 2002. The principal investigator identified a primary diagnosis and primary intervention for each chart. A thorough literature search was then undertaken with respect to the primary intervention. If a randomized control trial (RCT) or a systematic review was found, the intervention was classified as level I evidence. If no RCT was found, the intervention was assessed by an expert committee who determined its appropriateness based on face validity (RCTs were unanimously judged to be both unnecessary and, if a placebo would have been involved, unethical). These interventions were classified as level II evidence. Interventions that did not fall into either above category were classified as level III evidence. RESULTS: Two hundred and sixty-two patient charts were reviewed. Of these, 35.9% did not receive a primary intervention. Of the 168 interventions assessed, 80.4% were evidence-based (level I), 7.1% had face validity (level II) and 12.5% had no supporting evidence (level III). Of the evidence-based interventions, 83.7% were supported by studies with mostly pediatric patients. CONCLUSION: Our study demonstrates that a substantial proportion of PED treatment decisions are evidence-based, with most based on studies in pediatric patients. Also, a large number of patients seen in the PED receive no intervention.
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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 | 0.020 | 0.107 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".