Evidence map›Paper›PMID 41445950›Full record

ArticleFrontiers in microbiology2025

Drug resistance profile of

Yannan Xu, Sixuan Liu, Jiaxiong Zheng, Jianxiong Lin, Liwei Gi, Qiaocheng Chang

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

6 authors.

Yannan Xu *School of Public Health, Shantou University, Shantou, China.
Sixuan Liu *School of Basic Medicine and Public Health, Jinan University, Guangzhou, China.
Jiaxiong ZhengSchool of Public Health, Shantou University, Shantou, China.
Jianxiong LinShantou Tuberculosis Prevention and Control Institute, Shantou, China.
Liwei GiShantou Tuberculosis Prevention and Control Institute, Shantou, China.
Qiaocheng ChangSchool of Public Health, Shantou University, Shantou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The situation of drug-resistant tuberculosis in China remains serious and complex. The majority of the study data are still derived from the 2,207 national survey of drug-resistant tuberculosis. In this study, we aimed to comprehensively characterize the prevalence of Materials and methods: This study analyzed Results: 55,388 MTB strains collected from 2002 to 2024 were analyzed, among which 15,078 were drug-resistant, including 7,848 multidrug-resistant strains. The resistance rates for INH, RFP, SM, EMB, PZA, and QS were 27.67, 25.33, 11.55, 6.19, 8.63, and 20.63%, respectively. Regional distribution patterns revealed that the eastern and western regions had the highest number of strains, but relatively low resistance rates. There was a low inflection point in 2019 for the resistance rates of all drugs except INH, whose resistance rate continued to increase after 2017. A total of 754 non-synonymous mutations were identified, with the highest mutation rates observed in INH (32.91%), RIF (28.98%), and QS (14.47%). The dominant mutation sites were Conclusion: Our analysis demonstrates that drug-resistant tuberculosis remains a serious challenge in China. Newly identified resistance-conferring mutations should be prioritized and integrated with the specific epidemiological characteristics of DR-TB in China to support the development and implementation of rapid diagnostic technologies.

Indexed as

drug resistancegene mutationmolecular epidemiologymutation profileMycobacterium tuberculosis

Identifiers

PMID41445950
PMCPMC12722995

What OpenQuestion holds

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Registered trials

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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.