Evidence map›Paper›PMID 39723191›Full record

ArticleFrontiers in cellular and infection microbiology2024

Diagnosis value of targeted and metagenomic sequencing in respiratory tract infection.

Yukun Kuang, Weiping Tan, Chaohui Hu, Zehan Dai, Lihong Bai, Jiyu Wang, Huai Liao, Haihong Chen, Rongling He, Pengyuan Zhu and 4 more

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Frontiers in medicine · 2026
    Article
  10. Article
  11. Review
  12. Article
  13. Precise pathogen detection and clinical characterization of bronchiectasis.Frontiers in cellular and infection microbiology · 2025
    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

14 authors.

Yukun Kuang *Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Weiping Tan *Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Chaohui Hu *Guangzhou Kingcreate Biotechnology Co., Ltd., Guangzhou, China.
Zehan Dai *Guangzhou Kingcreate Biotechnology Co., Ltd., Guangzhou, China.
Lihong Bai *Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Jiyu WangDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Huai LiaoDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Haihong ChenDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Rongling HeDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Pengyuan ZhuGuangzhou Kingcreate Biotechnology Co., Ltd., Guangzhou, China.
Jun LiuGuangzhou Kingcreate Biotechnology Co., Ltd., Guangzhou, China.
Canmao XieDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Zunfu KeMolecular Diagnosis and Gene Testing Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Ke-Jing TangDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Targeted next-generation sequencing (tNGS) has become a trending tool in the field of infection diagnosis, but concerns are also raising about its performance compared with metagenomic next-generation sequencing (mNGS). This study aims to explore the clinical feasibility of a tNGS panel for respiratory tract infection diagnosis and compare it with mNGS in the same cohort of inpatients. Methods: 180 bronchoalveolar lavage fluid samples were collected and sent to two centers for mNGS and tNGS blinded tests, respectively. The concordance between pathogen reports of both methods and the clinical significance among samples with/without known etiology was further evaluated. Results: Overall, both methods displayed high agreement on pathogen reports, as the average percent agreement reached 95.29%. But tNGS presented a slightly higher detection rate per species than mNGS (P Conclusion: Collectively, tNGS presented a similar overall performance in pathogen identification compared to mNGS, but outperformed in some pathogens. This study also demonstrated that deployment of tNGS significantly improves etiology identification in routine practice and provides hints for clinical decisions. The low agreement between clinical diagnosis and NGS reports towards opportunistic pathogens implies that adjudication is essential for report interpretation. Finally, We proposed tNGS as a diagnosis option in clinical practice due to its cost-efficiency.

Indexed as

Bronchoalveolar Lavage FluidHigh-Throughput Nucleotide SequencingMetagenomicsRespiratory Tract InfectionsSensitivity and SpecificityAdultAgedAged, 80 and overBacteriaFemaleHumansMaleMiddle AgedYoung Adultbroad-spectrum pathogen identificationdiagnosis valuemetagenomic next-generation sequencing (mNGS)respiratory tract infectiontargeted next-generation sequencing (tNGS)

Identifiers

PMID39723191
PMCPMC11669359

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Registered trials

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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.