Evidence map›Paper›PMID 34234473›Full record

ArticleInfection and drug resistance2021

Dependence of Xpert MTB/RIF Accuracy for Detecting Rifampin Resistance in Bronchoalveolar Lavage Fluid on Bacterial Load: A Retrospective Study in Beijing, China.

Lin Qin, Fengmin Huo, Weicong Ren, Yuanyuan Shang, Cong Yao, Xuxia Zhang, Rongmei Liu, Liping Ma, Mengqiu Gao, Yu Pang

Open access · goldAbstract read
In one paragraph

Article in Infection and drug resistance, 2021. 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
0.8field-weighted citation impact, top 25% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

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  7. Real-time recombinase-aided amplification assay for rapid amplification of the IS1081 gene of Mycobacterium tuberculosis.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2023
    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

10 authors at 1 institution in 1 country.

Lin Qin *Department of Endoscopic Diagnosis & Treatment, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.
Fengmin Huo *Department of Bacteriology and Immunology, Beijing Key Laboratory on Drug-Resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.
Weicong Ren *Department of Bacteriology and Immunology, Beijing Key Laboratory on Drug-Resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.
Yuanyuan ShangDepartment of Bacteriology and Immunology, Beijing Key Laboratory on Drug-Resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.
Cong YaoDepartment of Bacteriology and Immunology, Beijing Key Laboratory on Drug-Resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.
Xuxia ZhangDepartment of Bacteriology and Immunology, Beijing Key Laboratory on Drug-Resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.
Rongmei LiuDepartment of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.
Liping MaDepartment of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.
Mengqiu GaoDepartment of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.
Yu PangDepartment of Bacteriology and Immunology, Beijing Key Laboratory on Drug-Resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, People's Republic of China.ORCID 0000-0001-6803-9807
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionWe assessed the effect of

methodsA retrospective study was conducted at Beijing Chest Hospital. Patients with symptoms suggestive of pulmonary TB who provided BALF specimens for routine MTB detection between June 2019 and July 2020 were enrolled in the study. Chi-square test and Student's

resultsIn total, 1125 patients with positive Xpert results who were enrolled in final analysis, 263 provided BALF specimens that tested positive for RIF-resistant MTB via Xpert MTB/RIF. The RIF-resistance rate of specimens with very low MTB bacterial load was 30.9%, a resistance rate significantly greater than rates obtained for groups with high (25.0%), medium (17.3%) and low (19.2%) MTB loads (

conclusionXpert MTB/RIF assay performed alarmingly poorly when used to detect RIF-resistant MTB in BALF specimens with very low bacterial loads. A high rate of Xpert probe E hybridization failure was the main driver of false-positive RIF-resistant results.

Indexed as

bronchoalveolar lavage fluidChinarifampicinXpert MTB/RIF

Identifiers

PMID34234473
PMCPMC8254186
OpenAlexW3176107256

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.