Evidence map›Paper›PMID 36196026›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2022

Performance of Xpert MTB/RIF for Diagnosis of Tuberculosis in HIV-Infected People in China: A Retrospective, Single-Center Study.

Guiju Gao, Chunyu Zhu, Yingchu Liu, Siyuan Yang, Jiang Xiao, Hongxin Zhao, Di Yang, Hongyuan Liang, Fang Wang, Liang Wu and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 49% of its field
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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Cost-effectiveness of community tuberculosis screening in South Africa.American journal of respiratory and critical care medicine · 2026
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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

12 authors at 2 institutions in 1 country.

Guiju GaoClinical and Research Center of Infectious Diseases, Beijing Ditan Hospital Capital Medical University, Beijing, China (mainland).
Chunyu ZhuBeijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).
Yingchu LiuSchool Of General Practice And Continung Education, Capital Medical University, Beijing, China (mainland).
Siyuan YangLaboratory of Infectious Diseases Center, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).ORCID 0000-0002-2636-9610
Jiang XiaoClinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).
Hongxin ZhaoClinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).
Di YangClinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).
Hongyuan LiangClinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).
Fang WangClinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).
Liang WuClinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).
Fujie ZhangClinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).
Liang NiClinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China (mainland).
Beijing Ditan Hospital · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND There are few studies of GeneXpert MTB/RIF (hereafter referred to as Xpert) detection technology in HIV-infected people in China. Therefore, this study aimed to evaluate the value of Xpert in HIV/TB co-infected patients and to provide reference and guidance for the diagnosis of TB in HIV-infected populations. MATERIAL AND METHODS This study reviewed medical records of human immunodeficiency virus (HIV) patients hospitalized at the Infection Center of Beijing Ditan Hospital affiliated to Capital Medical University from January 2018 to May 2020, and patients diagnosed with pulmonary and extrapulmonary tuberculosis were screened as study subjects. Sensitivity and specificity of Xpert were analyzed using ROC curves. RESULTS Of the 413 HIV patients, 177 patients met the entry criteria, of which the diagnosis was active pulmonary tuberculosis (PTB): 145 and extrapulmonary tuberculosis (EPTB): 32. The sensitivity of Xpert for PTB and EPTB was 82.0% and 100%, higher than that of acid-fast bacilli (AFB) (61.0% and 58.3%), and slightly lower than that of T-SPOT.TB (91.0% and 100%); the specificity was 83.7% and 93.5%, higher than that of AFB (72.6%, 87.1%) and T-SPOT.TB (16.6%, 21.2%). The sensitivity of Xpert was 100% in bronchoalveolar lavage fluid (BALF) and 80.0% in sputum; in patients with CD4⁺ <200 cells/mm³, the sensitivity of Xpert was 90.0% and specificity was 84.8%, higher than that of AFB (60.0%, 75.5%) and T-SPOT.TB (90.0%, 21.5%). CONCLUSIONS Xpert has a high accuracy in HIV/TB co-infected patients, and Xpert still shows a high sensitivity and specificity even in HIV patients with CD4⁺ <200 cells/mm³. Xpert is recommended for the diagnosis of tuberculosis in HIV-infected patients.

Indexed as

HIV InfectionsMycobacterium tuberculosisTuberculosisTuberculosis, PulmonaryHumansRetrospective StudiesRifampinSensitivity and SpecificitySputumRifampin

Identifiers

PMID36196026
PMCPMC9549759
OpenAlexW4296785991

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.