Evidence map›Paper›PMID 40688272›Full record

ArticleJournal of thoracic disease2025

Diagnostic performance of Xpert MTB/RIF in lymph node tuberculosis in a general hospital.

Wenting Jin, Xiaoyu Yin, Meixia Wang, Tingting Fang, Jiayi Ni, Chunmei Zhou, Wanqin Yang, Jue Pan, Bijie Hu

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2025. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Wenting Jin *Department of Infectious Diseases, Zhongshan Hospital, Fudan University, Shanghai, China.
Xiaoyu Yin *Department of Infectious Diseases, Zhongshan Hospital, Fudan University, Shanghai, China.
Meixia WangDepartment of Hospital Infection Management, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
Tingting FangDepartment of Infectious Diseases, Zhongshan Hospital, Fudan University, Shanghai, China.
Jiayi NiDepartment of Infectious Diseases, Shanghai Fengxian District Central Hospital, Shanghai, China.
Chunmei ZhouDepartment of Laboratory Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Wanqin YangDepartment of Infectious Diseases, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
Jue PanDepartment of Infectious Diseases, Zhongshan Hospital, Fudan University, Shanghai, China.
Bijie HuDepartment of Infectious Diseases, Zhongshan Hospital, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In general hospitals, tuberculosis (TB) is an important infectious cause of lymphadenopathy, but its etiological diagnosis rate is very low. This study aimed to determine the performance of Xpert MTB/RIF(Xpert) in differentiate tuberculous lymphadenopathy from other causes. Methods: A retrospective pairing study was carried out from August 2015 to July 2024. A total of 229 participants were involved. Microbiological reference standard (MRS) and composite reference standard (CRS) were used as two standards. All patients underwent biopsy measurement and specimens were examined using histopathology, acid-fast bacilli (AFB), liquid culture with/without Xpert. The baseline information, diagnostic methods and time were compared between two groups. The diagnostic values including sensitivity, specificity, accuracy (ACC), Kappa value and area under the curve (AUC) were compared. Results: This study included a total of 229 participants, of whom 150 were in the no Xpert group and 79 in the Xpert group. The median age was 44 [31-58] years, with female proportion of 60.0%. The most common sites of lymphadenopathy are the neck (66%), mediastinum (17%), and abdomen (7%). In patients with lymph node tuberculosis (LNTB), MRS was achieved in 35.4% of cases, while 60.0% fulfilled CRS criteria. No significant differences were observed in MRS percentage or pathology positivity rates between the two groups. The median time from biopsy to diagnosis was significantly shorter in the Xpert group compared to the no Xpert group {2 days [interquartile range (IQR), 1-9 days] Conclusions: Xpert can accelerate the microbiological diagnosis time and reduce the misdiagnose of lymph node granulomatous lesions. The application of Xpert combined with culture or pathology may be the best pattern for the diagnosis of LNTB in general hospital.

Indexed as

lymphadenopathylymph node tuberculosis (LNTB)rapid diagnosistuberculosis (TB)Xpert MTB/RIF

Identifiers

PMID40688272
PMCPMC12268821

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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.