Evidence map›Paper›PMID 40182288›Full record

ArticleFrontiers in microbiology2025

Enhancing bloodstream infection diagnostics: a novel filtration and targeted next-generation sequencing approach for precise pathogen identification.

Ting-Syuan Lin, ZiHao Zhu, XiaoHong Lin, Hsi-Yuan Huang, Li-Ping Li, Jing Li, Jie Ni, PeiZhi Li, LanChun Chen, WeiXin Tang and 10 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

20 authors.

Ting-Syuan Lin *School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
ZiHao Zhu *School of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
XiaoHong LinDepartment of Critical Care Medicine, The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
Hsi-Yuan HuangSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
Li-Ping LiSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
Jing LiSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
Jie NiSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
PeiZhi LiShanya life-tech Co. Ltd., Guangzhou, Guangdong, China.
LanChun ChenDepartment of Critical Care Medicine, The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
WeiXin TangDepartment of Critical Care Medicine, The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
HuiXin LiuDepartment of Critical Care Medicine, The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
XiaoLong SeDepartment of Critical Care Medicine, The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
MingFei XieDepartment of Critical Care Medicine, The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
Canling LongCentral Laboratory, The Second Affiliated Hospital, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, China.
Chih-Min ChiuHealth SwifTech Co. Ltd., Shenzhen, Guangdong, China.
Szu-Han FangHealth SwifTech Co. Ltd., Shenzhen, Guangdong, China.
JiaMing ZhaoHealth SwifTech Co. Ltd., Shenzhen, Guangdong, China.
Yang-Chi-Dung LinSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.
XueTao YuDepartment of Critical Care Medicine, The Second Affiliated Hospital, School of Medicine, The Chinese University of Hong Kong, Shenzhen & Longgang District People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
Hsien-Da HuangSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bloodstream infections (BSIs) pose a significant diagnostic challenge, largely due to the limitations of traditional methods such as blood cultures. These methods often yield low positive rates, have lengthy processing times that delay treatment, and are limited in detecting only a narrow range of pathogens. Such delays and inaccuracies can critically impede timely clinical interventions, potentially compromising patient outcomes. Next-generation sequencing (NGS) is a powerful tool for rapid, precise pathogen identification. While metagenomic NGS (mNGS) offers broad pathogen coverage, it is often costly and complex. Targeted NGS (tNGS), however, focuses on key regions of clinically relevant pathogens, reducing costs and simplifying workflows while maintaining high sensitivity, making it more practical for routine diagnostics. In this study, we introduce a novel approach combining a human cell-specific filtration membrane with a multiplex tNGS panel to overcome these challenges. The filtration membrane, designed with surface charge properties to be electrostatically attractive to leukocytes for the selective capture of specific cells, demonstrated high efficiency in removing host cells and nucleic acids, achieving over a 98% reduction in host DNA and thereby minimizing background interference in pathogen detection. Additionally, we developed an effective multiplex tNGS panel targeting over 330 clinically relevant pathogens and verified its consistency with mNGS and blood culture results, demonstrating a significant improvement in detection sensitivity. By integrating these two methods, we achieved a synergistic enhancement in diagnostic capability, boosting pathogen reads by 6- to 8-fold, which enabled reliable identification even in cases of low-abundance pathogens. This approach provides faster, more accurate, and more sensitive detection of BSIs, enabling earlier identification of infections. This facilitates timely and targeted treatment, ultimately improving patient outcomes in critical care settings. Given the unique properties of the filtration membrane and the strengths of the tNGS panel, this approach shows promising applications in prenatal and genetic health support, as well as in advancing early cancer screening strategies.

Indexed as

bloodstream infectionsfiltration membranepathogentargeted next-generation sequencingwhole blood

Identifiers

PMID40182288
PMCPMC11965694

What OpenQuestion holds

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LicenceCC BY
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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.