Predictive values of different critical scoring systems for survival rate after discharge in critically ill patients supported by extracorporeal membrane oxygenation
10.3760/cma.j.issn.2095-4352.2018.05.012
- VernacularTitle:不同危重症评分系统对体外膜肺氧合支持下危重症患者出院存活率的预测价值
- Author:
Jinsong ZHANG
1
;
Wei LI
;
Xufeng CHEN
;
Yong MEI
;
Jinru LYU
;
Deliang HU
;
Gang ZHANG
;
Yongxia GAO
;
Xihua HUANG
Author Information
1. 南京医科大学第一附属医院(江苏省人民医院)急诊医学科
- Keywords:
Critical scoring system;
Extracorporeal membrane oxygenation;
Survival rate
- From:
Chinese Critical Care Medicine
2018;30(5):456-460
- CountryChina
- Language:Chinese
-
Abstract:
Objective To determine the predictive values of different critical scoring systems for survival rate after discharge in critically ill patients supported by extracorporeal membrane oxygenation (ECMO). Methods The clinical data of 34 critically ill patients supported by ECMO admitted to Department of Emergency of the First Affiliated Hospital of Nanjing Medical University (Jiangsu Provincial People's Hospital) from July 2015 to September 2017 were retrospectively analyzed. The general information and the worst values of vital signs and related pathophysiological indicators within 12 hours before ECMO treatment of patients were collected, and sequential organ failure assessment (SOFA), multiple organs dysfunction score (MODS), simplified acute physiology score Ⅱ (SAPSⅡ), and acute physiology and chronic health evaluation Ⅳ(APACHEⅣ) scores were calculated. The patients were divided into survival group and non-survival group according to 28-day survival after hospital discharge. General clinical characteristics and aforementioned scores were compared between the two groups. Scoring systems for predicting prognosis were assessed by using the receiver operating characteristic (ROC) curve. The Kaplan-Meier method was used to depict the surviving curve. Results Thirty-four patients were finally enrolled, 13 of whom were dead at the follow-up period of 28 days after hospital discharge, and 21 survived. Duration of ECMO support in non-survival group was significantly shorter than that in survival group (hours: 101.4±7.8 vs. 134.4±12.6), SOFA, SAPSⅡ, and APACHEⅣ scores were significantly higher than those of survival group (SOFA score: 10.6±3.6 vs. 8.8±3.3, SAPSⅡscore: 38.7±14.3 vs. 31.8±12.5, APACHEⅣ score: 46.5±15.5 vs. 38.1±11.3, all P < 0.05). There was no significant difference in gender, age, body mass index (BMI), vital signs or related pathophysiological indicators within 12 hours before ECMO treatment, or MODS score between the two groups. ROC curve analysis showed that the area under ROC curve (AUC) of SAPSⅡ score for predicting 28-day survival rate was the highest, which was significantly higher than that of SOFA, MODS, and APACHEⅣ score (0.880 vs. 0.694, 0.654, 0.682, all P < 0.05). When the best cut-off value of SAPSⅡ score was 43, the sensitivity was 81.2%, and the specificity was 77.9%. Kaplan-Meier survival analysis showed that 28-day survival rate after hospital discharge in patients with SAPSⅡ score < 43 (n = 18) was significantly higher than that in patients with SAPSⅡ score ≥43 (n = 16; χ2= 2.444, P = 0.018). Conclusions Four critical scoring systems of SOFA, MODS, SAPSⅡand APACHEⅣ have been proved to have good prognostic ability to predict 28-day survival after hospital discharge in critically ill patients supported by ECMO. Among them, SAPSⅡ score system has more accurate prediction value.
