ArticleIndian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine2023
Comparison of Six Scoring Systems for Predicting In-hospital Mortality among Patients with SARS-COV2 Presenting to the Emergency Department.
Article in Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
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- Early prognosis prediction in mechanically ventilated patients using machine learning for tertiary care hospital settings.Journal of clinical monitoring and computing · 2026Article
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- A nomogram for predicting ICU mortality of sepsis associated encephalopathy: a retrospective cohort study based on MIMIC-IV and eICU-CRD.BMC medical informatics and decision making · 2025Article
- Evaluating the predictive performance of PIRO score against six clinical prediction scores for COVID-19 outcomes in the emergency department.Scientific reports · 2025Article
- Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study.Journal of medical Internet research · 2025Article
- Interpretable machine learning for predicting sepsis risk in emergency triage patients.Scientific reports · 2025Article
- Development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit.Scientific reports · 2025Article
- A nomogram to distinguish noncardiac chest pain based on cardiopulmonary exercise testing in cardiology clinic.BMC medical informatics and decision making · 2024Article
- Development and validation of nomogram for predicting the risk of transferring to the ICU for children with influenza.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2024Article
- Predictive model of risk factors for 28-day mortality in patients with sepsis or sepsis-associated delirium based on the MIMIC-IV database.Scientific reports · 2024Article
- An elastic net regression model for predicting the risk of ICU admission and death for hospitalized patients with COVID-19.Scientific reports · 2024Article
- A comparative study of explainable ensemble learning and logistic regression for predicting in-hospital mortality in the emergency department.Scientific reports · 2024Article
- Calibration of Prediction Models of In-hospital Mortality in SARS-CoV-2 Patients Depends also on Data Quality.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2024Article
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8 authors.
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Abstract
Background: The study aimed to compare the prognostic accuracy of six different severity-of-illness scoring systems for predicting in-hospital mortality among patients with confirmed SARS-COV2 who presented to the emergency department (ED). The scoring systems assessed were worthing physiological score (WPS), early warning score (EWS), rapid acute physiology score (RAPS), rapid emergency medicine score (REMS), national early warning score (NEWS), and quick sequential organ failure assessment (qSOFA). Materials and methods: A cohort study was conducted using data obtained from electronic medical records of 6,429 confirmed SARS-COV2 patients presenting to the ED. Logistic regression models were fitted on the original severity-of-illness scores to assess the models' performance using the Area Under the Curve for ROC (AUC-ROC) and Precision-Recall curves (AUC-PR), Brier Score (BS), and calibration plots were used to assess the models' performance. Bootstrap samples with multiple imputations were used for internal validation. Results: The mean age of the patients was 64 years (IQR:50-76) and 57.5% were male. The WPS, REMS, and NEWS models had AUROC of 0.714, 0.705, and 0.701, respectively. The poorest performance was observed in the RAPS model, with an AUROC of 0.601. The BS for the NEWS, qSOFA, EWS, WPS, RAPS, and REMS was 0.18, 0.09, 0.03, 0.14, 0.15, and 0.11 respectively. Excellent calibration was obtained for the NEWS, while the other models had proper calibration. Conclusion: The WPS, REMS, and NEWS have a fair discriminatory performance and may assist in risk stratification for SARS-COV2 patients presenting to the ED. Generally, underlying diseases and most vital signs are positively associated with mortality and were different between the survivors and non-survivors. How to cite this article: Rahmatinejad Z, Hoseini B, Reihani H, Hanna AA, Pourmand A, Tabatabaei SM,
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