Evidence map›Paper›PMID 40761921›Full record

ArticleInternational journal of general medicine2025

Construction and Validation of a Nomogram-Based Predictive Model for Acute Kidney Injury Caused by Drug Resistance to Tuberculosis.

Mo Deng, Na Han, Mishan Jia, Zhiqing Zheng, Yanqing Tian, Hui Wang, Li Feng

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Article in International journal of general medicine, 2025. 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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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mo Deng *Department of Tuberculosis, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, People's Republic of China.
Na HanDepartment of Tuberculosis, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, People's Republic of China.
Mishan JiaDepartment of Tuberculosis, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, People's Republic of China.
Zhiqing ZhengDepartment of Tuberculosis, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, People's Republic of China.
Yanqing TianDepartment of Tuberculosis, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, People's Republic of China.
Hui Wang *Department of Tuberculosis, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, People's Republic of China.
Li FengDepartment of Tuberculosis, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Acute kidney injury (AKI) is a common and serious adverse effect during tuberculosis (TB) treatment in clinical settings, particularly in patients with drug-resistant TB. AKI may lead to treatment interruption and poor prognosis. Early identification of patients at high risk for AKI is crucial to improve clinical outcomes. Methods: We retrospectively enrolled 571 TB patients, divided into training and validation cohorts. LASSO and multivariate logistic regression were used to identify risk factors, and the nomogram was evaluated using AUC, calibration, and decision curve analysis (DCA). Results: This study included 571 patients with TB. In this study, five variables (age, hypertension, diabetes, Scr, and ALB) were included to construct a nomogram for predicting AKI caused by drug resistance to TB. The AUC of the training set and validation set were 0.809 (95% CI: 0.7480-0.871, Conclusion: The nomogram model of AKI caused by drug resistance to TB established in this study has good predictive value and helps identify high-risk populations.

Indexed as

acute renal injuryanti tuberculosis drugsnomogramrisk factors

Identifiers

PMID40761921
PMCPMC12320139

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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.