Current status of research on models for predicting acute kidney injury following cardiac surgery
10.7507/1007-4848.201612020
- VernacularTitle:心脏术后急性肾损伤预测模型的研究现状
- Author:
WU Dongchen
1
;
WANG Qi
1
;
ZHANG Yangyang
2
Author Information
1. Clinical Medical College of Nanjing Medical University, Nanjing, 210029, P.R.China
2. Department of Cardiovascular Surgery, Dongfang Hospital Affiliated to Shanghai Tongji University, Shanghai, 200120, P.R.China
- Publication Type:Journal Article
- Keywords:
Cardiac surgery;
acute kidney injury;
risk prediction models
- From:
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
2018;25(3):237-248
- CountryChina
- Language:Chinese
-
Abstract:
Acute kidney injury (AKI) is a complication with high morbidity and mortality after cardiac surgery. In order to predict the incidence of AKI after cardiac surgery, many risk prediction models have been established worldwide. We made a detailed introduction to the composing features, clinical application and predictive capability of 14 commonly used models. Among the 14 risk prediction models, age, congestive heart failure, hypertension, left ventricular ejection fraction, diabetes, cardiac valve surgery, coronary artery bypass grafting (CABG) combined with cardiac valve surgery, emergency surgery, preoperative creatinine, preoperative estimated glomerular filtration rate (eGFR), preoperative New York Heart Association (NYHA) score>Ⅱ, previous cardiac surgery, cadiopulmonary bypass (CPB) time and low cardiac output syndrome (LCOS) are included in many risks prediction models (>3 times). In comparison to Mehta and SRI models, Cleveland risk prediction model shows the best discrimination for the prediction of renal replacement therapy (RRT)-AKI and AKI in the European. However, in Chinese population, the predictive ability of the above three risk prediction models for RRT-AKI and AKI is poor.
