Evidence map›Paper›PMID 40766036›Full record

ArticleFrontiers in public health2025

Prediction of risk factors associated with the development of multidrug-resistant tuberculosis in patients with tuberculosis.

Haiyan Chen, Zhaowei Tong, Jianfeng Zhong, Yong Tong, Qingqiu Zeng, Bin Shen, Qun Song, Fuchu Qian, Xin Xiao

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Haiyan ChenDepartment of Infection, Huzhou Central Hospital, Huzhou, Zhejiang, China.
Zhaowei TongDepartment of Infection, Huzhou Central Hospital, Huzhou, Zhejiang, China.
Jianfeng ZhongDepartment of Infection, Huzhou Central Hospital, Huzhou, Zhejiang, China.
Yong TongDepartment of Infection, Huzhou Central Hospital, Huzhou, Zhejiang, China.
Qingqiu ZengDepartment of Infection, Huzhou Central Hospital, Huzhou, Zhejiang, China.
Bin ShenDepartment of Infection, Huzhou Central Hospital, Huzhou, Zhejiang, China.
Qun SongDepartment of Infection, Huzhou Central Hospital, Huzhou, Zhejiang, China.
Fuchu QianDepartment of Clinical Medicine, Huzhou University, Huzhou, Zhejiang, China.
Xin XiaoHuzhou Key Laboratory of Precision Medicine Research and Translation for Infectious Diseases, Huzhou Central Hospital, Huzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to develop and validate a reliable nomogram based on clinical factors to predict development of multidrug-resistant tuberculosis (MDR-TB) associated with individuals with tuberculosis (TB), so as to reduce the harm and economic burden caused by disease progression. Methods: The study included 4,251 individuals with TB who received treatment at Huzhou Central Hospital between January 2016 and December 2023, excluding 87 individuals because of infection with non-TB mycobacterium or incomplete information (including missing laboratory or clinical data). A total of 4,164 individuals (2,261 sputum smear-positive and 1,903 sputum smear-negative patients) were ultimately included in the analysis. This analysis incorporated clinical baseline presentations, demographic information, imaging findings, laboratory results, and clinical diagnoses to develop a predictive model for MDR-TB. Results: This study demonstrated that sex, age, a history of anti-TB therapy, body mass index (BMI) ≤ 18.5, smoking history, occupation, previously diagnosed TB, pulmonary cavitation, comorbidities, poverty, and C-reactive protein (CRP) ≥ 37.3 mg/L were major risk factors for MDR-TB in patients with TB. The area under the receiver operating characteristic (ROC) curve was 0.902 for the training group and 0.909 for the validation group. Calibration curve analysis revealed that the predicted and actual incidence rates of MDR-TB in the two groups were in good agreement, whereas decision curve analysis (DCA) indicated that the predictive model resulted in better clinical benefit. Conclusion: The nomogram model established in this study included 11 clinical characteristics and demographic features of patients with TB, which may be valuable for predicting MDR-TB.

Indexed as

NomogramsTuberculosis, Multidrug-ResistantAdultAgedAntitubercular AgentsChinaFemaleHumansMaleMiddle AgedRisk FactorsAntitubercular Agentsmultidrug-resistant tuberculosispredictionpredictive modelrisk factorstuberculosis

Identifiers

PMID40766036
PMCPMC12321860

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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.