Evidence map›Paper›PMID 41142442›Full record

ReviewPractical laboratory medicine2025

Advancements in laboratory diagnostics for HIV/MTB coinfection: Integrating conventional methods with emerging technologies.

Yu Li, Hongjuan Wei, Limei Sun, Dongsong Tang, Tiantian Wang, Yanhua Yu

Abstract readReview
In one paragraph

Review in Practical laboratory medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Yu LiDepartment of Clinical Laboratory, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Hongjuan WeiDepartment of Clinical Laboratory, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Limei SunDepartment of Clinical Laboratory, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Dongsong TangDepartment of Clinical Laboratory, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Tiantian WangState Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.
Yanhua YuDepartment of Clinical Laboratory, Beijing Youan Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Individuals infected with the Human Immunodeficiency Virus (HIV) face an elevated risk of Mycobacterium tuberculosis (MTB) infection. Clinical diagnosis of HIV/MTB coinfection presents substantial challenges, with co-infected patients exhibiting high mortality rates and representing a critical public health burden. The diagnostic process is complicated by atypical clinical presentations, frequent extrapulmonary tuberculosis involvement, difficulties in obtaining adequate sputum specimens, and low mycobacterial loads in samples-factors that severely limit the utility of conventional diagnostic methods such as sputum smear microscopy. Furthermore, HIV-associated immunosuppression diminishes the reliability of immunological diagnostic approaches. Recent advancements in molecular diagnostics have revolutionized tuberculosis detection in this vulnerable population. This review critically evaluates current laboratory methods for MTB detection in HIV/MTB co-infected individuals, analyzing their diagnostic performance, inherent limitations, and clinical applicability across diverse healthcare settings.

Indexed as

BiomarkersCoinfection diagnosticsHuman immunodeficiency virusMolecular assaysMycobacterium tuberculosisPoint-of-care testing

Identifiers

PMID41142442
PMCPMC12550725

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.