ArticleFrontiers in cardiovascular medicine2022
Simplified acute physiology score III is excellent for predicting in-hospital mortality in coronary care unit patients with acute myocardial infarction: A retrospective study.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Article
- Cardiac autonomic function score: a novel risk stratification tool in the cardiac intensive care unit based on periodic repolarization dynamics and deceleration capacity of heart rate (LMU-eICU study).European heart journal. Digital health · 2025Article
- The prognostic value of pulmonary hypertension in intensive care unit patients from Beth Israel Deaconess Medical Center (BIDMC).Journal of cardiothoracic surgery · 2025Article
- A Nomogram for Predicting Survival in Patients with Respiratory Failure Following Trauma: A Retrospective Study Using the MIMIC-IV Database.Drug, healthcare and patient safety · 2025Article
- Urinary Output as a Predictor of Mortality in Cardiogenic Shock: An Explorative Retrospective Analysis.Journal of clinical medicine · 2024Article
- Comparison of different intensive care scoring systems and Glasgow Aneurysm score for aortic aneurysm in predicting 28-day mortality: a retrospective cohort study from MIMIC-IV database.BMC cardiovascular disorders · 2024Article
- Association of serum potassium levels with mortality in critically ill patients with sepsis during hospitalization.PloS one · 2024Article
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Abstract
Background: Coronary care unit (CCU) patients with acute myocardial infarction (AMI) lack effective predictors of in-hospital mortality. This study aimed to investigate the performance of four scoring systems in predicting in-hospital mortality in CCU patients with AMI. Methods: The baseline data, the logistic organ dysfunction system (LODS), the Oxford acute severity of illness score (OASIS), the simplified acute physiology score II (SAPS II), and the simplified acute physiology score III (SAPS III) scores of the patients were extracted from the fourth edition of the Medical Information Mart for Critical Care (MIMIC-IV) database. Independent risk factors for in-hospital mortality were identified by regression analysis. We performed receiver operating characteristic (ROC) curves and compared the area under the curve (AUC) to clarify the predictive value of the four scoring systems. Meanwhile, Kaplan-Meier curves and decision curve analysis (DCA) were performed to determine the optimal scoring system for predicting in-hospital mortality. Results: A total of 1,098 patients were included. The SAPS III was an independent risk factor for predicting in-hospital mortality in CCU patients with AMI before and after the propensity score matching (PSM) analysis. The discrimination of in-hospital mortality by SAPS III was superior to that of LODS, OASIS, and SAPS II. The AUC of the SAPS III scoring system was the highest among the four scoring systems, at 0.901 (before PSM) and 0.736 (after PSM). Survival analysis showed that significantly more in-hospital mortality occurred in the high-score SAPS III group compared to the low-score SAPS III group before PSM (HR 7.636, Conclusion: The SAPS III was an independent risk factor for predicting in-hospital mortality in CCU patients with AMI. The predictive value for in-hospital mortality with SAPS III is superior to that of LODS, OASIS, and SAPS II. The results of the DCA analysis suggest that SAPS III may provide a better clinical benefit for patients. We demonstrated that SAPS III is an excellent scoring system for predicting in-hospital mortality for CCU patients with AMI.
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