Evidence map›Paper›PMID 41983105›Full record

ArticleInfection and drug resistance2026

Factors Influencing Adherence to All-Oral Short-Course Treatment for DR-TB and Establishment of a Predictive Model.

Jie Huang, Qing-Dong Zhu, Zhi-Feng Li, Kan Xie, Jian-Ning Deng, Qiu-Ying Ma, Han-Zhen Su, Ting-Ting Lu, Xing-Fa Lu, Yan-Ling Hu and 1 more

Abstract read
In one paragraph

Article in Infection and drug resistance, 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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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Jie Huang *Faculty of Data Science, City University of Macau, Macau, 999878, People's Republic of China.
Qing-Dong Zhu *HIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530000, People's Republic of China.
Zhi-Feng LiHIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530000, People's Republic of China.
Kan XieHIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530000, People's Republic of China.
Jian-Ning DengHIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530000, People's Republic of China.
Qiu-Ying MaHIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530000, People's Republic of China.
Han-Zhen SuHIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530000, People's Republic of China.
Ting-Ting LuHIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530000, People's Republic of China.
Xing-Fa LuHIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530000, People's Republic of China.
Yan-Ling HuFaculty of Data Science, City University of Macau, Macau, 999878, People's Republic of China.
Zhou-Hua XieHIV/AIDS Clinical Treatment Center of Guangxi (Nanning) and The Fourth People's Hospital of Nanning, Nanning, 530000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore factors influencing adherence to all-oral short-course treatment for drug-resistant tuberculosis (DR-TB) and establish a predictive model. Methods: The study is retrospective and single-center. 241 TB patients treated at our hospital from January 2022 to December 2024 were retrospectively selected. Using a random number table method in a 7:3 ratio, patients were divided into a modeling group (n=169) and a validation group (n=72). The modeling group patients were categorized into groups of good adherence (n=89) and poor adherence (n=80). Univariate and binary Logistics regression analyses were used to identify influencing factors. A predictive model was constructed using SPSS, and R language was utilized to assess the model's application value through receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results: Binary logistic regression analysis showed that family monthly income, level of education, history of previous confirmed TB, and family-supervised drug administration were influencing factors for adherence to short-course treatment for DR-TB ( Conclusion: Family monthly income, level of education, history of previous confirmed TB, and family-supervised drug administration are factors influencing adherence to short-course treatment for DR-TB. The model established based on these factors holds significant value in predictive applications.

Indexed as

adherenceall, oral short, course treatmentDR-TBdrug-resistant tuberculosisTB

Identifiers

PMID41983105
PMCPMC13075505

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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.