Development and Validation of a Nomogram for Predicting Drug-Induced Acute Kidney Injury in Hospitalized Patients: A Case-Control Study Based on Propensity-Score Matching

作者全名："Yu, Chengxuan; Guo, Daihong; Yao, Chong; Zhu, Yu; Liu, Siyuan; Kong, Xianghao"

作者地址："[Yu, Chengxuan; Guo, Daihong; Yao, Chong; Zhu, Yu; Liu, Siyuan; Kong, Xianghao] Chinese Peoples Liberat Army Gen Hosp, Med Secur Ctr, Pharm Dept, Beijing, Peoples R China; [Yu, Chengxuan; Zhu, Yu; Liu, Siyuan] Chinese Peoples Liberat Army Gen Hosp, Grad Sch, Beijing, Peoples R China; [Kong, Xianghao] Chongqing Med Univ, Coll Pharm, Chongqing, Peoples R China"

通信作者："Guo, DH (corresponding author), Chinese Peoples Liberat Army Gen Hosp, Med Secur Ctr, Pharm Dept, Beijing, Peoples R China."

来源：FRONTIERS IN PHARMACOLOGY

ESI学科分类：PHARMACOLOGY & TOXICOLOGY

WOS号：WOS:000667187400001

JCR分区：Q1

影响因子：5.6

年份：2021

卷号：12

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：adverse drug reaction; drug-induced acute kidney injury; active surveillance; informatization; nomogram; predictive model

摘要："Background: Drug-induced acute kidney injury (D-AKI) is associated with increased mortality and longer hospital stays. This study aims to establish a nomogram to predict the occurrence of D-AKI in hospitalized patients in a multi-drug environment. Methods: A single center retrospective study among adult hospitalized patients was conducted from July 2019 to September 2019 based on the Adverse Drug Events Active Surveillance and Assessment System-2 developed by our hospital. According to the propensity score matching algorithm, four controls per case were matched to eliminate the confounding bias caused by individual baseline variables. The predictors for D-AKI were obtained by logistic regression equation and used to establish the nomogram. Results: Among 51,772 hospitalized patients, 332 were diagnosed with D-AKI. After matching, 288 pairs and 1,440 patients were included in the study, including 1,005 cases in the development group and 435 cases in the validation group. Six variables were independent predictors for D-AKI: alcohol abuse, the concurrent use of nonsteroidal anti-inflammatory drugs or diuretics, chronic kidney disease, lower baseline red blood cell count and neutrophil count >= 7 x 10(9)/L. The area under the curve (AUC) of the prediction model in the development group and validation group were 0.787 (95%CI, 0.752-0.823) and 0.788 (95%CI, 0.736-0.840), respectively. The GiViTI calibration belts showed that the model had a good prediction accuracy for the occurrence of D-AKI (p > 0.05). Conclusion: This nomogram can help identify patients at high risk of D-AKI, which was useful in preventing the progression of D-AKI and treating it in the early stages."

基金机构：Key Project of Military Medical Innovation Project [17CXZ010]; Project of Monitoring and Evaluation of the Use of Key Clinical Drugs [Y2021FH-YWPJ01]

基金资助正文：This study was supported by the Key Project of Military Medical Innovation Project in 2017 (No. 17CXZ010) and "the Project of Monitoring and Evaluation of the Use of Key Clinical Drugs" commissioned by the Chinese Association of Research Hospitals (No. Y2021FH-YWPJ01).