Evidence map›Paper›PMID 40206488›Full record

ArticleFrontiers in medicine2025

Diagnostic value of metagenomic next-generation sequencing in detecting

Jiawen He, Ying Chen, Zhuxiu Jiang, Feng Li, Mingli Zhu, Zhibo Xu, Meihua Wang, Meng Tang, Yuanting Wu, Yang Li

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jiawen HeHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Ying ChenHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Zhuxiu JiangHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Feng LiHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Mingli ZhuHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Zhibo XuHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Meihua WangHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Meng TangHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Yuanting WuHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.
Yang LiHangzhou Xixi Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Accurate diagnosis of Methods: BALF samples from 34 HIV-positive PJP patients and 50 non-PJP controls were analyzed. Diagnostic performance metrics (sensitivity, specificity, NPV, AUC) and co-pathogen profiles were evaluated for mNGS versus conventional methods. Results: mNGS and PCR both achieved 100% sensitivity. mNGS showed higher specificity (91.3% vs. 88%) and AUC (0.898 vs. 0.940 for PCR). Co-infections were detected in 67.6% of PJP cases by mNGS, including cytomegalovirus (41.2%), Epstein-Barr virus (29.4%), and non-tuberculous mycobacteria (14.7%). GMS and BG assays exhibited lower sensitivity (64.7% and 76.5%, respectively). Discussion: mNGS offers superior specificity, accuracy, and co-infection detection compared to traditional methods. Its high NPV (100%) supports clinical utility in ruling out PJP. While resource-intensive, mNGS is a promising first-line diagnostic tool for HIV-associated PJP, particularly in polymicrobial infection settings.

Indexed as

bronchoalveolar lavage fluidco-infectiondiagnostic performanceHIVmetagenomic next-generation sequencingPneumocystis jirovecii pneumonia

Identifiers

PMID40206488
PMCPMC11978654

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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.