Evidence map›Paper›PMID 39086797›Full record

ArticleFrontiers in public health2024

Analysis of epidemiological characteristics of extrapulmonary tuberculosis from South-Central China.

Yanyan Yu, Yu Xiang, Haican Liu, Shuliu Yang, Machao Li, Binbin Liu, Da Xu, Yaning Wu, Wenbin Li, Tanwei Fang and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Observational
  3. Review
  4. Article
  5. 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

16 authors.

Yanyan Yu *Clinical Laboratory, Hunan Provincial Tuberculosis Prevention and Control Institute & Hunan Chest Hospital, Changsha, Hunan, China.
Yu Xiang *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Haican Liu *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Shuliu Yang *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Machao LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Binbin LiuClinical Laboratory, Hunan Provincial Tuberculosis Prevention and Control Institute & Hunan Chest Hospital, Changsha, Hunan, China.
Da XuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yaning WuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Wenbin LiClinical Laboratory, Hunan Provincial Tuberculosis Prevention and Control Institute & Hunan Chest Hospital, Changsha, Hunan, China.
Tanwei FangClinical Laboratory, Hunan Provincial Tuberculosis Prevention and Control Institute & Hunan Chest Hospital, Changsha, Hunan, China.
Jixiang LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Donglei XuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Kanglin WanNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yunhong TanClinical Laboratory, Hunan Provincial Tuberculosis Prevention and Control Institute & Hunan Chest Hospital, Changsha, Hunan, China.
Xiuqin YuanSchool of Public Health, University of South China, Hengyang, China.
Guilian LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Tuberculosis Reference Laboratory, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aimed to investigate the epidemiological and drug resistance (DR) characteristics of extrapulmonary tuberculosis (EPTB) in South-Central China. Methods: EPTB inpatients who were culture-positive for Results: A total of 1,324 cases were included. The majority of EPTB patients were in the age range of 20-29 years, were predominantly men (male-to-female ratio: 2.03), and were farmers (65.63%). Most EPTB cases were found in 2013 and 2017 from 2013 to 2021. The most prevalent subtypes of EPTB were lymphatic TB (29.83%, 395/1,324), multiple EPTB (20.85%, 276/1,324), and musculoskeletal TB (14.65%, 194/1,324). Musculoskeletal TB and genitourinary TB predominantly presented as exclusive EPTB forms, while lymphatic TB and pharyngeal/laryngeal TB often co-occurred with pulmonary TB (PTB). Drug susceptibility testing results showed that total DR rates (resistance to any of RFP, isoniazid [INH], streptomycin [STR], and/or ethambutol [EMB]) and RR/MDR rates in EPTB were 25.23% and 12.39%, respectively. Musculoskeletal TB exhibited the highest rates of total DR (31.40%), INH resistance (28.90%), STR resistance (20.10%), EMB resistance (6.20%), MDR (13.90%), and poly-DR (6.70%). The multivariable logistic regression model showed that patients aged from 20 to 59 years (compared to those aged 10 years), workers (compared to retirees), and EPTB patients from the south and west of Hunan (compared to those from the east of Hunan) were at an increased risk of developing RR/MDR EPTB (all Conclusion: Our study provided a detailed account of the epidemiological and DR characteristics of EPTB in Hunan province, China. The significant DR rates, particularly in musculoskeletal TB cases, highlight the need for timely diagnosis, effective drug susceptibility testing, and the development of more effective treatment regimens for EPTB, especially targeting musculoskeletal TB treatments.

Indexed as

Antitubercular AgentsMycobacterium tuberculosisTuberculosis, ExtrapulmonaryAdolescentAdultChildChinaFemaleHumansMaleMicrobial Sensitivity TestsMiddle AgedRetrospective StudiesRifampinRisk FactorsTuberculosis, Multidrug-ResistantAntitubercular AgentsRifampindrug resistanceepidemiologyextrapulmonary tuberculosisprevalencerisk factors

Identifiers

PMID39086797
PMCPMC11288871

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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.