ArticleThe western journal of emergency medicine2022
Development and Validation of a Novel Triage Tool for Predicting Cardiac Arrest in the Emergency Department.
Article in The western journal of emergency medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of Machine Learning for Patients With Cardiac Arrest: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Evaluation of Nurse-Led Triage in the Emergency Department: A Retrospective Observational Study.Journal of clinical nursing · 2026Observational
- The Growing Burden of Fall-Related Injuries among Older Adults: A Seven-Year Study from a Tertiary Medical Center in Taiwan.Annals of geriatric medicine and research · 2026Article
- Grouping of Emergency Department-based Cardiac Arrest Patients According to Clinical Features to Assess Patient Outcomes.The western journal of emergency medicine · 2025Article
- Deep Learning-Based Electrocardiogram Model (EIANet) to Predict Emergency Department Cardiac Arrest: Development and External Validation Study.Journal of medical Internet research · 2025Article
- Deep learning-based Emergency Department In-hospital Cardiac Arrest Score (Deep EDICAS) for early prediction of cardiac arrest and cardiopulmonary resuscitation in the emergency department.BioData mining · 2024Article
- Characteristics, Outcome and Prognostic Factors of Patients with Emergency Department Cardiac Arrest: A 14-Year Retrospective Study.Journal of clinical medicine · 2024Article
- Development of early prediction model of in-hospital cardiac arrest based on laboratory parameters.Biomedical engineering online · 2023Article
- Development of a machine-learning algorithm to predict in-hospital cardiac arrest for emergency department patients using a nationwide database.Scientific reports · 2022Observational
- External validation of a triage tool for predicting cardiac arrest in the emergency department.Scientific reports · 2022Article
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly recognition and prevention of in-hospital cardiac arrest (IHCA) have played an increasingly important role in the chain of survival. However, clinical tools for predicting IHCA are scarce, particularly in the emergency department (ED). We sought to estimate the incidence of ED-based IHCA and to develop and validate a novel triage tool, the Emergency Department In-hospital Cardiac Arrest Score (EDICAS), for predicting ED-based IHCA.
methodsIn this retrospective cohort study we used electronic clinical warehouse data from a tertiary medical center with approximately 100,000 ED visits per year. We extracted data from 733,398 ED visits over a seven-year period. We selected one ED visit per person and excluded out-of-hospital cardiac arrest or children. Patient demographics and computerized triage information were included as potential predictors.
resultsA total of 325,502 adult ED patients were included. Of these patients, 623 (0.2%) developed ED-based IHCA. The EDICAS, which includes age and arrival mode and categorizes vital signs with simple cut-offs, showed excellent discrimination (area under the receiver operating characteristic [AUROC] curve, 0.87) and maintained its discriminatory ability (AUROC, 0.86) in cross-validation. Previously developed early warning scores showed lower AUROC (0.77 for the Modified Early Warning Score and 0.83 for the National Early Warning Score) when applied to our ED population.
conclusionIn-hospital cardiac arrest in the ED is relatively uncommon. We developed and internally validated a novel tool for predicting imminent IHCA in the ED. Future studies are warranted to determine whether this tool could gain lead time to identify high-risk patients and potentially reduce ED-based IHCA.
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