Evidence map›Paper›PMID 40723928›Full record

ArticleAntibiotics (Basel, Switzerland)2025

Sentinel-Site-Based Surveillance of

Yiting Wang, Chunfa Liu, Bing Zhao, Xichao Ou, Hui Xia, Yuanyuan Song, Yang Zheng, Yang Zhou, Ruida Xing, Yanlin Zhao and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Antibiotics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Yiting WangInstitute for Immunization and Prevention, Beijing Center for Disease Control and Prevention, Beijing Academy for Preventive Medicine, Beijing Institute of Tuberculosis Control Research and Prevention, Beijing 100013, China.
Chunfa LiuDepartment of Animal Science and Technology, Beijing University of Agriculture, Beijing 100096, China.
Bing ZhaoNational Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing 102200, China.
Xichao OuNational Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing 102200, China.ORCID 0000-0002-3126-4450
Hui XiaNational Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing 102200, China.
Yuanyuan SongNational Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing 102200, China.
Yang ZhengNational Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing 102200, China.
Yang ZhouNational Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing 102200, China.
Ruida XingNational Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing 102200, China.ORCID 0000-0001-9696-0214
Yanlin ZhaoNational Tuberculosis Reference Laboratory, Chinese Center for Disease Control and Prevention, Beijing 102200, China.ORCID 0000-0002-7890-4312
Huiwen ZhengLaboratory of Respiratory Diseases, Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Center for Children's Health, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, Beijing 100045, China.

Funding

Beijing Natural Science Foundation 7224328Beijing University of Agriculture's internal scientific research special project KYZX-2024001Beijing University of Agriculture youth teacher scientific research and innovation capability enhancement program QJKC-2023018China CDC-Tuberculosis Control and Prevention Project 2528Funding for Reform and Development of Beijing Municipal Health Commission EYGF-HX-05National Key Research and Development Program 2022YFC2305204National Key Research and Development Program 2023YFC2307301
6 · The paper itself

Abstract

objectivesTo investigate epidemiological/drug-resistance characteristics and identify potential factors related to drug-resistant and clustered tuberculosis in Sichuan.

methodsA total of 295

resultsOf 268 MTB isolates with both WGS and drug-susceptibility testing (DST) results, 159 (59.3%, 159/268) strains belonged to the Beijing lineage (L2). Isoniazid had the highest resistance rate (15.3%, 41/268), followed by rifampicin (9.3%, 25/268). The sensitivity of WGS to predict drug resistance varied from 75% to 97.6%, and the specificity was above 96.0% for all.

conclusionsOur findings prove that WGS is a promising tool for predicting drug resistance to isoniazid, rifampicin, ethambutol, moxifloxacin and levofloxacin in Sichuan. The higher resistance rate to isoniazid emphasizes the urgent need for susceptibility testing surveillance and application management. Improving the diagnosis, treatment and management of patients ≤ 24 years old may reduce the transmission of MTB in Sichuan.

Indexed as

drug resistancerisktransmissiontuberculosiswhole-genome sequencing

Identifiers

PMID40723928
PMCPMC12291903

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.