ArticleEuropean journal of medical research2023
Predictors of 72-h unscheduled return visits with admission in patients presenting to the emergency department with abdominal pain.
Article in European journal of medical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Deep Learning for Emergency Department Sustainability: Interpretable Prediction of Revisit.Healthcare (Basel, Switzerland) · 2026Article
- Article
- Performance comparison of artificial intelligence models in predicting 72-h emergency department unscheduled return visits.Frontiers in public health · 2025Article
- Prediction Models Using Decision Tree and Logistic Regression Method for Predicting Hospital Revisits in Peritoneal Dialysis Patients.Diagnostics (Basel, Switzerland) · 2024Article
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4 authors.
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Abstract
backgroundUnscheduled return visits (URVs) to the emergency department (ED) constitute a crucial indicator of patient care quality.
objectiveWe aimed to analyze the clinical characteristics of patients who visited the ED with abdominal pain and to identify the risk of URVs with admission (URVAs) from URVs without admission (URVNAs).
methodsThis retrospective study included adult patients who visited the ED of Taipei Medical University Hospital because of abdominal pain and revisited in 72 h over a 5-year period (January 1, 2014, to December 31, 2018). Multivariable logistic regression analysis was employed to identify risk factors for URVAs and receiver operating characteristic (ROC) curve analysis was performed to determine the efficacy of variables predicting URVAs and the optimal cut-off points for the variables. In addition, a classification and regression tree (CART)-based scoring system was used for predicting risk of URVA.
resultsOf 702 eligible patients with URVs related to abdominal pain, 249 had URVAs (35.5%). In multivariable analysis, risk factors for URVAs during the index visit included execution of laboratory tests (yes vs no: adjusted odds ratio [AOR], 4.32; 95% CI 2.99-6.23), older age (≥ 40 vs < 40 years: AOR, 2.10; 95% CI 1.10-1.34), Level 1-2 triage scores (Levels 1-2 vs Levels 3-5: AOR, 2.30; 95% CI 1.26-4.19), and use of ≥ 2 analgesics (≥ 2 vs < 2: AOR, 2.90; 95% CI 1.58-5.30). ROC curve analysis results revealed the combination of these 4 above variables resulted in acceptable performance (area under curve: 0.716). The above 4 variables were used in the CART model to evaluate URVA propensity.
conclusionsElder patients with abdominal pain who needed laboratory workup, had Level 1-2 triage scores, and received ≥ 2 doses of analgesics during their index visits to the ED had higher risk of URVAs.
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