Evidence map›Paper›PMID 32504464›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2020

Combination of Xpert MTB/RIF and MTBDRplus for Diagnosing Tuberculosis in a Chinese District.

Chunfang Lv, Jianhong Wu, Catherine Pierre-Audigier, Liuzhu Lu, Amel Kévin Alame-Emane, Howard Takiff, Yangfeng Xu, Jian Wang, Brigitte Gicquel, Shengyuan Liu

Open access · hybridAbstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.1field-weighted citation impact, top 45% 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, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 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

10 authors at 2 institutions in 2 countries.

Chunfang LvDepartment of Clinical Laboratory, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, Guangdong, China (mainland).
Jianhong WuDepartment of Clinical Laboratory, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, Guangdong, China (mainland).
Catherine Pierre-AudigierBacteriology Laboratory, Centre Hospitalo-Universitaire Bichat-Claude Bernard, APHP, Paris, France.
Liuzhu LuDepartment of Clinical Laboratory, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, Guangdong, China (mainland).
Amel Kévin Alame-EmaneDepartment of Tuberculosis Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, Guangdong, China (mainland).
Howard TakiffDepartment of Tuberculosis Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, Guangdong, China (mainland).
Yangfeng XuDepartment of Clinical Laboratory, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, Guangdong, China (mainland).
Jian WangDepartment of Tuberculosis Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, Guangdong, China (mainland).
Brigitte GicquelDepartment of Tuberculosis Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, Guangdong, China (mainland).
Shengyuan LiuDepartment of Tuberculosis Prevention and Control, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen, Guangdong, China (mainland).
Shenzhen Nanshan Center for Chronic Disease Control · CNUniversité Claude Bernard Lyon 1 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND The incidence of tuberculosis (TB) remains high in many countries, including some middle- and high-income countries without financial constraints for diagnosis and treatment. The implementation of an improved algorithm for diagnosis using 2 rapid molecular tests should help reduce the TB burden. MATERIAL AND METHODS Between April 2018 and March 2019, sputum samples from 711 patients suspected of TB in Nanshan, Shenzhen, China, were included in this prospective study. All sputum samples were examined by smear microscopy, Mycobacterium Growth Indicator Tube (MGIT) 960 culture, and Xpert MTB/RIF. The sputum remnants of Xpert MTB/RIF were used for MTBDRplus to confirm the Xpert results both for the presence of TB bacilli and for resistance to rifampicin (RIF), and also to diagnose multidrug-resistant tuberculosis (MDR-TB). RESULTS In total, 200 (28.1%) of the 711 sputa were positive for TB by Xpert MTB/RIF, and the sputum remnants were used for MTBDRplus. The simultaneous use of Xpert MTB/RIF and MTBDRplus directly on sputum samples permitted accurate bacteriologic confirmation of TB in 64% (119/187) of cases and detection of 70% (7/10) of strains that were MDR. CONCLUSIONS The implementation of 2 rapid nucleic acid-based tests on sputum samples could facilitate the prompt and appropriate treatment of most TB cases.

Indexed as

Asian PeopleChinaFemaleHumansIncidenceMaleMicroscopyMycobacterium tuberculosisProspective StudiesReagent Kits, DiagnosticSensitivity and SpecificitySpecimen HandlingSputumTuberculosisTuberculosis, Multidrug-ResistantTuberculosis, PulmonaryReagent Kits, Diagnostic

Identifiers

PMID32504464
PMCPMC7297034
OpenAlexW3033776233

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.