ArticleBioMed research international2023
Comparing In-Hospital Mortality Prediction by Senior Emergency Resident's Judgment and Prognostic Models in the Emergency Department.
Article in BioMed research international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Hybrid model based on fuzzy logic and classification trees for the prediction of mortality of critical trauma patients: Pre-hospital variables from the RETRAUCI registry.BMC medical research methodology · 2026Article
- Application of XGBoost and logistic regression in predicting 90 days mortality for elderly severe acute renal failure patients.Scientific reports · 2026Article
- Machine learning improves prediction of pulmonary thromboembolism and reduces unnecessary computed tomography scans in the emergency department.Scientific reports · 2026Article
- Respiratory National Early Warning Score for 28-day mortality prediction in suspected sepsis patients in the emergency department.BMC emergency medicine · 2025Article
- Performance of five trauma scoring systems in predicting in-hospital outcomes in geriatric trauma: a retrospective cohort study.BMC geriatrics · 2025Article
- Forecasting COVID-19 inpatient mortality using fundamental parameters in resource-constrained settings: a countrywide multi-center cohort study.BMC infectious diseases · 2025Article
- Nomogram predicts in-hospital mortality in patients with emergency gastrointestinal bleeding: A multicenter retrospective study.Scientific reports · 2025Article
- 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
- Machine learning models for predicting in-hospital mortality from acute pancreatitis in intensive care unit.BMC medical informatics and decision making · 2025Article
- A methodological systematic review of validation and performance of sepsis real-time prediction models.NPJ digital medicine · 2025Article
- Relationship between atherogenic index of plasma and length of stay in critically ill patients with atherosclerotic cardiovascular disease: a retrospective cohort study and predictive modeling based on machine learning.Cardiovascular diabetology · 2025Article
- Construction and evaluation of a triage assessment model for patients with acute non-traumatic chest pain: mixed retrospective and prospective observational study.BMC emergency medicine · 2025Observational
- Development and validation of a nomogram to predict survival in septic patients with heart failure in the intensive care unit.Scientific reports · 2025Article
- Interpretable machine learning for predicting sepsis risk in emergency triage patients.Scientific reports · 2025Article
- 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
- Author Response.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2024Article
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7 authors.
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Abstract
Background: A comparison of emergency residents' judgments and two derivatives of the Sequential Organ Failure Assessment (SOFA), namely, the mSOFA and the qSOFA, was conducted to determine the accuracy of predicting in-hospital mortality among critically ill patients in the emergency department (ED). Methods: A prospective cohort research was performed on patients over 18 years of age presented to the ED. We used logistic regression to develop a model for predicting in-hospital mortality by using qSOFA, mSOFA, and residents' judgment scores. We compared the accuracy of prognostic models and residents' judgment in terms of the overall accuracy of the predicted probabilities (Brier score), discrimination (area under the ROC curve), and calibration (calibration graph). Analyses were carried out using R software version R-4.2.0. Results: In the study, 2,205 patients with median age of 64 (IQR: 50-77) years were included. There were no significant differences between the qSOFA (AUC 0.70; 95% CI: 0.67-0.73) and physician's judgment (AUC 0.68; 0.65-0.71). Despite this, the discrimination of mSOFA (AUC 0.74; 0.71-0.77) was significantly higher than that of the qSOFA and residents' judgments. Additionally, the AUC-PR of mSOFA, qSOFA, and emergency resident's judgments was 0.45 (0.43-0.47), 0.38 (0.36-0.40), and 0.35 (0.33-0.37), respectively. The mSOFA appears stronger in terms of overall performance: 0.13 vs. 0.14 and 0.15. All three models showed good calibration. Conclusion: The performance of emergency residents' judgment and the qSOFA was the same in predicting in-hospital mortality. However, the mSOFA predicted better-calibrated mortality risk. Large-scale studies should be conducted to determine the utility of these models.
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