Simplified acute physiology score III is excellent for predicting in-hospital mortality in coronary care unit patients with acute myocardial infarction: A retrospective study
作者全名:"Zheng, Xiaoyu; Hu, Tianyang; Liu, Tingrong; Wang, Wei"
作者地址:"[Zheng, Xiaoyu] Chongqing Med & Pharmaceut Coll, Sch Clin Med, Chongqing, Peoples R China; [Hu, Tianyang] Chongqing Med Univ, Affiliated Hosp 2, Precis Med Ctr, Chongqing, Peoples R China; [Liu, Tingrong] Peoples Hosp Yubei Dist Chongqing City, Dept Geriatr, Chongqing, Peoples R China; [Wang, Wei] Peoples Hosp Yubei Dist Chongqing City, Dept Orthoped, Chongqing, Peoples R China"
通信作者:"Wang, W (通讯作者),Peoples Hosp Yubei Dist Chongqing City, Dept Orthoped, Chongqing, Peoples R China."
来源:FRONTIERS IN CARDIOVASCULAR MEDICINE
ESI学科分类:
WOS号:WOS:000901516200001
JCR分区:Q2
影响因子:3.6
年份:2022
卷号:9
期号:
开始页:
结束页:
文献类型:Article
关键词:SAPS III; SAPS II; OASIS; LODS; acute myocardial infarction; in-hospital mortality; coronary care unit
摘要:"BackgroundCoronary 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. MethodsThe 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. ResultsA 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, P < 0.001) and after PSM (HR 2.077, P = 0.005). The DCA curve of SAPS III had the greatest benefit score across the largest threshold range compared to the other three scoring systems. ConclusionThe 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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