Evidence map›Paper›PMID 39754613›Full record

SynthesisEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology2025

Diagnostic accuracy of Xpert MTB/RIF Ultra for detecting pulmonary tuberculosis and rifampicin resistance: a systematic review and meta-analysis.

Man-Qing Wang, Ya-Fang Zheng, Yu-Qi Hu, Jin-Xia Huang, Zi-Xin Yuan, Zu-Yan Wu, Lu-Fang Huang, Chu-Ting Tang, Feng-Yi Zhang, Yan Chen and 3 more

Abstract readSystematic ReviewMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 2025. 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. Clinical performance of the Abbott RealTime Mycobacterium tuberculosis (MTB) PCR on bronchoscopic specimens for diagnosing pulmonary tuberculosis.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
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

13 authors.

Man-Qing WangDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Ya-Fang ZhengDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Yu-Qi HuDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Jin-Xia HuangDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Zi-Xin YuanDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Zu-Yan WuDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Lu-Fang HuangDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Chu-Ting TangDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Feng-Yi ZhangDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Yan ChenDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Jin-Ke HeDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.
Xu-Guang GuoDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China. gysygxg@gmail.com.
Bao-Mei YanDepartment of Ultrasound Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China. 308114436@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPublic health issues related to tuberculosis still exist. Because Xpert MTB/RIF Ultra is more effective than conventional TB diagnostic techniques are, it is now regarded as an emerging technology. The diagnostic accuracy of Xpert MTB/RIF Ultra for tuberculosis was assessed in this systematic study.

methodsWe searched the PubMed, Cochrane, EMBASE, and Web of Science databases for pertinent literature published before January 18, 2024. The quality of the collected literature was assessed via Review Manager 5.3 software, which applies the quality assessment of diagnostic accuracy studies criteria. Using Metadisc 1.40 software, the sensitivity, specificity, and summary receiver operating characteristic curves were plotted and examined. Stata 12.0 was the program we utilized to assess publication bias in this investigation. The Prospero prospective register of systematic reviews included this study (reference number CRD42024569674).

resultsAnalysis of 187 fourfold tables from 72 studies revealed that Xpert MTB/RIF Ultra demonstrated an overall pooled sensitivity of 76% and specificity of 95% for detecting pulmonary tuberculosis. The positive likelihood ratio (PLR) was 14.91, and the negative likelihood ratio (NLR) was 0.23, with an area under the curve (AUC) of 0.9351 and a diagnostic odds ratio (DOR) of 73.39. For detecting rifampin resistance, the combined sensitivity and specificity were 94% and 97%, respectively. The pooled PLR was 24.94, the NLR was 0.07, and the DOR was 429.05. The area under the summary receiver operating characteristic (SROC) curve was 0.9868.

conclusionIn conclusion, developing effective laboratory diagnostic tools for identifying Mycobacterium tuberculosis is essential for epidemiological research. This study demonstrated that Xpert MTB/RIF Ultra effectively diagnosed Mycobacterium tuberculosis infection, including pulmonary tuberculosis, as well as rifampin resistance, highlighting its potential as a valuable tool for both diagnosis and resistance detection.

Indexed as

Antibiotics, AntitubercularDrug Resistance, BacterialMolecular Diagnostic TechniquesMycobacterium tuberculosisRifampinTuberculosis, PulmonaryHumansROC CurveSensitivity and SpecificityAntibiotics, AntitubercularRifampinMeta-analysisMycobacterium tuberculosis complex (MTBC)Pulmonary tuberculosisRifampin resistanceXpert MTB/RIF Ultra

Identifiers

What OpenQuestion holds

Textmetadata
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.