Evidence map›Paper›PMID 38328429›Full record

ArticleFrontiers in microbiology2024

Whole-genome shotgun sequencing unravels the influence of environmental microbial co-infections on the treatment efficacy for severe pediatric infectious diseases.

Chengxin Li, Jing Song, Qihong Chen, Dandan Ge, Qiyuan Li, Yungang Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 2024. 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
–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

2 citing papers in PubMed.

  1. Article
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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.

Chengxin LiDepartment of Pediatrics, Pediatric Key Laboratory of Xiamen, The First Affiliated Hospital of Xiamen University, Institute of Pediatrics, School of Medicine, Xiamen University, Xiamen, China.
Jing SongDepartment of Pediatrics, Pediatric Key Laboratory of Xiamen, The First Affiliated Hospital of Xiamen University, Institute of Pediatrics, School of Medicine, Xiamen University, Xiamen, China.
Qihong ChenDepartment of Pediatrics, Pediatric Key Laboratory of Xiamen, The First Affiliated Hospital of Xiamen University, Institute of Pediatrics, School of Medicine, Xiamen University, Xiamen, China.
Dandan GeDepartment of Pediatrics, Pediatric Key Laboratory of Xiamen, The First Affiliated Hospital of Xiamen University, Institute of Pediatrics, School of Medicine, Xiamen University, Xiamen, China.
Qiyuan LiDepartment of Pediatrics, Pediatric Key Laboratory of Xiamen, The First Affiliated Hospital of Xiamen University, Institute of Pediatrics, School of Medicine, Xiamen University, Xiamen, China.
Yungang YangDepartment of Pediatrics, Pediatric Key Laboratory of Xiamen, The First Affiliated Hospital of Xiamen University, Institute of Pediatrics, School of Medicine, Xiamen University, Xiamen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The microbiome plays a pivotal role in mediating immune deviation during the development of early-life viral infections. Recurrent infections in children are considered a risk factor for disease development. This study delves into the metagenomics of the microbiome in children suffering from severe infections, seeking to identify potential sources of these infections. Aims: The aim of this study was to identify the specific microorganisms and factors that significantly influence the treatment duration in patients suffering from severe infections. We sought to understand how these microbial communities and other variables may affect the treatment duration and the use of antibiotics of these patients with severe infections. Method: Whole-genome shotgun sequencing was conducted on samples collected from children aged 0-14 years with severe infections, admitted to the Pediatrics Department of Xiamen First Hospital. The Kraken2 algorithm was used for taxonomic identification from sequence reads, and linear mixed models were employed to identify significant microorganisms influencing treatment duration. Results: Using a linear mixed model after removed the outliers, we identified that the abundance of Conclusion: These findings suggest that

Indexed as

co-infectionmicrobiomepediatricsevere infectionshotgun sequencing

Identifiers

PMID38328429
PMCPMC10847551

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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.