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Record W7115006886 · doi:10.1093/pch/pxaf116.034

34 Predictors of bounce back for children redirected by triage nurse from the paediatric emergency department

2025· article· en· W7115006886 on OpenAlexaffabout

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
Fundersnot available
KeywordsTriageEmergency departmentLogistic regressionIntraclass correlationCohortPrimary care

Abstract

fetched live from OpenAlex

Abstract Background To address the overcrowding, our paediatric emergency department (ED) implemented a procedure to redirect non-emergency patients. Using a standardized guideline, triage nurses can redirect children to external paediatric clinic, alternative professional, family doctor or home. Objectives This study aimed to identify the proportion of children who returned to the ED after redirection and to identify predictors of these return visits. Design/Methods We conducted a retrospective cohort study involving all children 18 years and under who were redirected from the ED of a tertiary care paediatric hospital in Montreal. Of them, a random sample of 150 return visits and 300 controls were selected to be included in a nested case-control study. The primary outcome was a return visit to the same ED within seven days. Potential predictors of return visits included demographic information, disease characteristics, triage scores and disposition. A 10% random sample was evaluated in duplicate. The primary analysis was the proportion of return visits among all redirected children. Subsequently, a multivariate logistic regression analysis was performed to identified independent variables associated with the return visits. It was estimated that evaluation of at least 100 cases of return visit would allow an evaluation of 10 independent variables. Results Between September 2023 and August 2024, 80 221 children were evaluated in the ED of whom 6 556 (8.2%) patients were redirected: 372 (5.7%) redirected children returned to the ED in the seven days. The inter-rater reliability evaluation demonstrated Kappa scores or intraclass correlation coefficient higher than 0.6 for all variables. Of the 150 return visits, 127 (85%; 95%CI: 78-90%) were related to the initial chief complaint: 64 (43%; 95%CI: 35-51%) for persistence of symptoms and 49 (33%; 95%CI: 26-41%) for clinical deterioration. Seven (5%; 95%CI: 2-9%) returning patients were hospitalized. Factors associated with a higher risk of return visit included abdominal complaint, fever at triage and patients redirected home. Patients with dental problems and redirected to specialized clinics were at lower risk of return. Conclusion This study identified that 6% of children redirected from the CHU Sainte-Justine triage returned to the same ED within seven days of initial presentation, most commonly for persistence or deterioration of symptoms. The knowledge of predictors of these return visits can improve reorientation guidelines and help the Quebec health care system to develop more focused interventions for reorientation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.009
GPT teacher head0.283
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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