Evidence map›Paper›PMID 36396946›Full record

ArticleThe Journal of international medical research2022

Rapid diagnosis of a complex oral mucosal infection using metagenomic next-generation sequencing: a case report.

Yuhan Song, Fujie Song, Shangfeng Liu, Shuang Chen, Zhifeng Song

Open access · goldAbstract readCase Reports
PubMed Full text at PMC Publisher
In one paragraph

Article in The Journal of international medical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 42% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. 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

5 authors at 2 institutions in 2 countries.

Yuhan SongDepartment of Oral Mucosa, Shanghai Stomatological Hospital, Fudan University, Shanghai, P. R. China.
Fujie SongDepartment of First Dental Clinic, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine; College of Stomatology, Shanghai Jiao Tong University; National Center for Stomatology; National Clinical Research Center for Oral Diseases; Shanghai Key Laboratory of Stomatology, Shanghai, P. R. China.
Shangfeng LiuShanghai Key Laboratory of Craniomaxillofacial Development and Diseases, Shanghai Stomatological Hospital, Fudan University, Shanghai, P. R. China.ORCID 0000-0002-2413-3946
Shuang ChenShanghai Key Laboratory of Craniomaxillofacial Development and Diseases, Shanghai Stomatological Hospital, Fudan University, Shanghai, P. R. China.
Zhifeng SongDepartment of Oral Mucosa, Shanghai Stomatological Hospital, Fudan University, Shanghai, P. R. China.
Fudan University · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The most commonly used methods for pathogen detection and identification in oral mucosal infectious diseases are DNA or RNA quantitative polymerase chain reaction detection, bacterial or fungal cultures, and immunohistochemical analysis. These traditional methods are time-consuming and can only detect one specific targeted pathogen at a time. An efficient and sensitive method with higher species richness is urgently needed. Metagenomic next-generation sequencing (mNGS) is a new method of pathogen detection with high efficiency and sensitivity. In this case report, mNGS was used to identify the pathogens in oral mucosal tissues of a patient with complex oral mucosal infections and oral leukoplakia.

Indexed as

Communicable DiseasesMetagenomicsHigh-Throughput Nucleotide SequencingHumansMucous MembraneSensitivity and Specificitycase reportComplex oral mucosal infectiondiagnosismetagenomic next-generation sequencingprecanceroustreatment

Identifiers

PMID36396946
PMCPMC9679348
OpenAlexW4309263546

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.