Evidence map›Paper›PMID 33614906›Full record

ReviewSmall methods2021

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings.

Na Li, Qingqing Cai, Qing Miao, Zeshi Song, Yuan Fang, Bijie Hu

Registry-linked trialAbstract readReview
In one paragraph

Review in Small methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06566898 (Monitoring of Antimicrobial Resistance Based on Metagenomics Analyses in Pneumonia Patients), which is not on this map. Cited by 183 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
183citing papers in PubMed, 3 pooled it
–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.

NCT06566898 recruitingnot on this mapstarted 2024, after this paper: background citation

Monitoring of Antimicrobial Resistance Based on Metagenomics Analyses in Pneumonia Patients: a Genomic Epidemiology Study

TypeobservationalSponsorShanghai General Hospital, ChinaRan2024 to 2026Enrolled800ConditionsPneumonia, Next-generation Sequencing, Microbiome, Antimicrobial Resistance
3 · Its place in the literature

Who cites it

183 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  14. Characteristics of CD4Journal of intensive medicine · 2026
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123 more citing papers are in PubMed but not listed here.

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.

Na LiDepartment of Infectious Diseases Zhongshan Hospital Fudan University Shanghai 200032 China.
Qingqing CaiGenoxor Medical Science and Technology Inc. Zhejiang 317317 China.
Qing MiaoDepartment of Infectious Diseases Zhongshan Hospital Fudan University Shanghai 200032 China.
Zeshi SongGenoxor Medical Science and Technology Inc. Zhejiang 317317 China.
Yuan FangGenoxor Medical Science and Technology Inc. Zhejiang 317317 China.
Bijie HuDepartment of Infectious Diseases Zhongshan Hospital Fudan University Shanghai 200032 China.ORCID https://orcid.org/0000-0002-2821-4292

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.

Indexed as

clinical applicationinfectious diseasemetagenomicsnext‐generation sequencing

Identifiers

PMID33614906
PMCPMC7883231

What OpenQuestion holds

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Registered trials

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.