ArticleRenal failure2026
An explainable machine learning model for predicting in-hospital infection in patients with systemic lupus erythematosus.
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Article in Renal failure, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
13 authors.
Jiabao LiuSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Yong WangSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Zheyi DongSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Zhe FengSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Xiaomin LiuSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Yue NiuSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Jie WuSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Li ZhangSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Pu ChenSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Guangyan CaiSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Sai PanSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Ping LiSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Xiangmei ChenSenior Department of Nephrology, Chinese PLA General Hospital; State Key Laboratory of Kidney Diseases; National Clinical Research Center for Kidney Diseases; Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases; Key Disciplines of National Administration of Traditional Chinese Medicine; and Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine, Beijing, China.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Infection is a leading cause of mortality in patients with systemic lupus erythematosus (SLE), yet effective tools for early identification of high-risk patients are lacking. This study aimed to develop an explainable machine learning (ML) model to predict in-hospital infection risk among SLE patients. We analyzed adult patients (≥18 years) with SLE (
Indexed as
Cross InfectionLupus Erythematosus, SystemicMachine LearningAdultBoosting Machine Learning AlgorithmsFemaleHospitalizationHumansMaleMiddle AgedPredictive Learning ModelsRisk AssessmentRisk Factorsinfectionmachine learningprediction modelSHAP (SHapley additive exPlanations)Systemic lupus erythematosus
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.