Evidence map›Paper›PMID 38622723›Full record

ArticleAnnals of clinical microbiology and antimicrobials2024

Antimicrobial resistance prediction by clinical metagenomics in pediatric severe pneumonia patients.

Mingyu Gan, Yanyan Zhang, Gangfeng Yan, Yixue Wang, Guoping Lu, Bingbing Wu, Weiming Chen, Wenhao Zhou

Open access · goldAbstract read
In one paragraph

Article in Annals of clinical microbiology and antimicrobials, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

18 citing papers in PubMed, 21 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Mingyu Gan *Center for Molecular Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, People's Republic of China.
Yanyan Zhang *Department of Neonatology, Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China.
Gangfeng YanDepartment of Critical Care Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, People's Republic of China.
Yixue WangDepartment of Critical Care Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, People's Republic of China.
Guoping LuDepartment of Critical Care Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, People's Republic of China.
Bingbing WuCenter for Molecular Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, People's Republic of China.
Weiming ChenDepartment of Critical Care Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, People's Republic of China. Weiming_chen@fudan.edu.cn.
Wenhao ZhouCenter for Molecular Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, People's Republic of China. zhouwenhao@fudan.edu.cn.
Children's Hospital of Fudan University · CNGuangzhou Medical University · CNSecond Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University · CN

Funding

National Key Research and Development Program of China 2021YFC2701800 and 2021YFC2701805National Key Research and Development Program of China 2022YFC2703603the China Primary Health Care Foundation MTP2022A014the Science and Technology Commission of Shanghai Municipality 22Y11902700the Shanghai Municipal Health System key supports discipline projects 2023ZDFC0103
6 · The paper itself

Abstract

backgroundAntimicrobial resistance (AMR) is a major threat to children's health, particularly in respiratory infections. Accurate identification of pathogens and AMR is crucial for targeted antibiotic treatment. Metagenomic next-generation sequencing (mNGS) shows promise in directly detecting microorganisms and resistance genes in clinical samples. However, the accuracy of AMR prediction through mNGS testing needs further investigation for practical clinical decision-making.

methodsWe aimed to evaluate the performance of mNGS in predicting AMR for severe pneumonia in pediatric patients. We conducted a retrospective analysis at a tertiary hospital from May 2022 to May 2023. Simultaneous mNGS and culture were performed on bronchoalveolar lavage fluid samples obtained from pediatric patients with severe pneumonia. By comparing the results of mNGS detection of microorganisms and antibiotic resistance genes with those of culture, sensitivity, specificity, positive predictive value, and negative predictive value were calculated.

resultsmNGS detected bacterial in 71.7% cases (86/120), significantly higher than culture (58/120, 48.3%). Compared to culture, mNGS demonstrated a sensitivity of 96.6% and a specificity of 51.6% in detecting pathogenic microorganisms. Phenotypic susceptibility testing (PST) of 19 antibiotics revealed significant variations in antibiotics resistance rates among different bacteria. Sensitivity prediction of mNGS for carbapenem resistance was higher than penicillins and cephalosporin (67.74% vs. 28.57%, 46.15%), while specificity showed no significant difference (85.71%, 75.00%, 75.00%). mNGS also showed a high sensitivity of 94.74% in predicting carbapenem resistance in Acinetobacter baumannii.

conclusionsmNGS exhibits variable predictive performance among different pathogens and antibiotics, indicating its potential as a supplementary tool to conventional PST. However, mNGS currently cannot replace conventional PST.

Indexed as

Anti-Bacterial AgentsPneumoniaBronchoalveolar Lavage FluidCarbapenemsChildDrug Resistance, BacterialHigh-Throughput Nucleotide SequencingHumansRetrospective StudiesSensitivity and SpecificityAnti-Bacterial AgentsCarbapenemsAntimicrobial resistanceMetagenomic next-generation sequencingPediatricSevere pneumonia

Identifiers

PMID38622723
PMCPMC11020437
OpenAlexW4394822162

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.