Risk assessment models for contrast-induced acute kidney injury after enhanced CT scanning
10.3760/cma.j.cn114015-20210909-00976
- VernacularTitle:增强CT扫描后对比剂急性肾损伤的风险评估模型
- Author:
Yichun XU
1
;
Chen LIU
;
Jianghua SHEN
;
Lan ZHANG
;
Yanqi CHU
Author Information
1. 首都医科大学宣武医院药学部，北京 100053
- Publication Type:Journal Article
- Keywords:
Contrast media;
Tomography scanners, X-ray computed;
Acute kidney injury;
Risk assessment
- From:
Adverse Drug Reactions Journal
2022;24(3):139-143
- CountryChina
- Language:Chinese
-
Abstract:
Contrast-induced acute kidney injury (CI-AKI) is a serious complication after contrast-enhanced CT scanning. Since the incidence of CI-AKI after contrast-enhanced CT scanning is very low, it is particularly important to screen the high-risk population of CI-AKI for targeted prevention using the risk assessment model. In this paper, 6 risk prediction models for CI-AKI after contrast-enhanced CT scanning are retrieved by searching the literature at home and abroad, including Herts′ prediction equation, Kim′s nomogram prediction model, Huang′s scoring prediction model, Moos′s risk factor prediction model, Jeon′s risk scoring prediction model, and Baek′s risk scoring model for CI-AKI prognosis in patients with chronic kidney disease. The predictive factors involved in the 6 models include estimated glomerular filtration rate, serum creatinine, and serum albumin before contrast-enhanced CT scanning, patient′s age, history of diabetes mellitus, hypertension, and chronic kidney disease, development of acute hypotension or congestive heart failure, and repeated use of contrast. Baek′s risk scoring model is used to predict the development and outcome of CI-AKI in patients with chronic kidney disease after contrast-enhanced CT scanning, while the other 5 models are prediction models for the risk of CI-AKI after contrast-enhanced CT scanning. However, the performance indicators of these 6 models are incomplete and lack of external verification by other researchers.
