Risk Factors for Return Visits to the Pediatric Emergency Department: Systematic Search and Review
Bibliographic record
Abstract
Objectives Return visits (RVs) to the emergency department (ED) has always been a major concern. RVs to the emergency department are a big burden on the healthcare system as its cost is higher than the cost of the initial visit. This review was performed to identify factors associated with risk of RVs to the pediatric ED. Methods and Analysis One researcher searched Medline, Embase, Cochrane Library and Web of Science. Studies were identified by using MeSH and keywords and included RVs to the pediatric ED up to 1 year a primary outcome. All studies were screened by two independent reviewers for eligibility and in case of disagreement, a meeting was held to discuss the problematic studies and a consensus was achieved. Results The search identified 539 reports from which 28 articles were included. Data was then extracted from the included studies according to a preset format. The exposures were grouped in 3 different groups: very probable, possible, and less likely. As a result, young age, language barrier and high acuity were identified as very probable risk factors. Having a public insurance or with low income, patients with comorbidities and patients who had multiple previous ED visits were found to be possible risk factors for return visits. Conclusion Young age, high acuity and language barrier among others are risk factors for return visits to the pediatric ED. Physicians should be aware of these factors and have a low threshold for admission or a good discharge plan for patients with one or more factors.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".