ASSESS-IE: a Novel Risk Score for Patients with Infective Endocarditis.

Autor: Wei, Xuebiao, Ran, Peng, Nong, Yuxin, Ye, Tao, Jian, Xuhua, Yao, Younan, Xu, Yiwei, Li, Yang, Wang, Zhonghua, Yang, Junqing, Wang, Shouhong, Yu, Danqing, Chen, Jiyan
Zdroj: Journal of Cardiovascular Translational Research; Jun2024, Vol. 17 Issue 3, p695-704, 10p
Abstrakt: Mortality in patients with infective endocarditis (IE) remains high. The existing risk scores are relatively complex with limited clinical application. This study was conducted to establish a new risk model to predict in-hospital and 6-month mortality in IE patients. A total of 1549 adult patients with definite IE admitted to Guangdong Provincial People's Hospital (n=1354) or Xiamen Cardiovascular Hospital (n=195) were included. The derivation cohort consisted of 1141 patients. The score was developed using the multivariate stepwise logistic regression analysis for in-hospital death. Bootstrap analysis was used for validation. Discrimination and calibration were evaluated by the receiver operating characteristic curve and the Hosmer–Lemeshow goodness-of-fit test. Six risk factors were used as score parameters (1 point for each): aortic valve affected, previous valve replacement surgery, severe heart failure, elevated serum direct bilirubin, moderate–severe anemia and acute stage. The predictive value and calibration of the ASSESS-IE score for in-hospital death were excellent in the derivation (area under the curve [AUC]=0.781, p<0.001; Hosmer–Lemeshow p=0.948) and validation (AUC=0.779, p<0.001; Hosmer–Lemeshow p=0.520) cohorts. The score remained excellent in bootstrap validation (AUC=0.783). The discriminatory ability of the ASSESS-IE score for in-hospital (AUC: 0.781 vs. 0.799, p=0.398) and 6-month mortality (AUC: 0.778 vs. 0.814, p=0.040) were similar with that of Park's score which comprised 14 variables. The ASSESS-IE risk score is a new and robust risk-stratified tool for patients with IE, which might further facilitate clinical decision-making. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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