Evidence map›Paper›PMID 40952128›Full record

ArticlemSystems2025

Machine learning-based evaluation of risk factors for carbapenem-resistant

Xiao Liu, Muxiu Jiang, Jinzhi Zhang, Heng Li, Yina Liu, Jiaqi Zhang, Xia Chen, Jun Bu, Shichang Xie, Menghan Zhang and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in mSystems, 2025. 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. 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

13 authors.

Xiao Liu *Key Laboratory of Alkene-carbon Fibres-based Technology & Application for Detection of Major Infectious Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Cancer Institute, Suzhou Medical College, Soochow University, Suzhou, China.ORCID 0009-0004-7336-0194
Muxiu Jiang *Department of Infectious Disease, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0002-4076-8394
Jinzhi Zhang *Emergency and Critical Care Center, Intensive Care Unit, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China.
Heng Li *Key Laboratory of Alkene-carbon Fibres-based Technology & Application for Detection of Major Infectious Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Cancer Institute, Suzhou Medical College, Soochow University, Suzhou, China.
Yina LiuKey Laboratory of Alkene-carbon Fibres-based Technology & Application for Detection of Major Infectious Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Cancer Institute, Suzhou Medical College, Soochow University, Suzhou, China.
Jiaqi ZhangKey Laboratory of Alkene-carbon Fibres-based Technology & Application for Detection of Major Infectious Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Cancer Institute, Suzhou Medical College, Soochow University, Suzhou, China.
Xia ChenDepartment of Infectious Disease, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Jun BuDepartment of Neonatology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Shichang XieKey Laboratory of Alkene-carbon Fibres-based Technology & Application for Detection of Major Infectious Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Cancer Institute, Suzhou Medical College, Soochow University, Suzhou, China.
Menghan ZhangSuzhou Center for Disease Control and Prevention, Suzhou, China.
Ning DongSchool of Public Health, Zhejiang University School of Medicine, Hangzhou, China.ORCID 0000-0001-6515-4201
Qing CaoDepartment of Infectious Disease, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0002-7637-2068
Zhemin ZhouKey Laboratory of Alkene-carbon Fibres-based Technology & Application for Detection of Major Infectious Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Cancer Institute, Suzhou Medical College, Soochow University, Suzhou, China.ORCID 0000-0001-9783-0366

Funding

National Natural Science Foundation of China 32170003, 32370099National Natural Science Foundation of China 82202465Natural Science Foundation of Jiangsu Province BK20211311Shanghai Pudong New Area Health Commission PW2023D-03
6 · The paper itself

Abstract

Healthcare-associated infections (HAIs), particularly in neonatal intensive care units (NICUs), pose significant challenges due to neonates' vulnerability and the rapid infection spread. However, risk factors facilitating pathogen persistence and dissemination have not been comprehensively investigated. This study aims to track HAI transmission pathways in NICUs and identify key risk factors contributing to the persistence and spread of carbapenem-resistant

Indexed as

Carbapenem-Resistant EnterobacteriaceaeCarbapenemsCross InfectionIntensive Care Units, NeonatalKlebsiella InfectionsKlebsiella pneumoniaeMachine LearningAnti-Bacterial AgentsChinaDisease OutbreaksFemaleHumansInfant, NewbornMalePlasmidsRisk FactorsAnti-Bacterial AgentsCarbapenemsbla NDM-1multi-drug resistance plasmidneonatesphylogeny

Identifiers

PMID40952128
PMCPMC12542634

What OpenQuestion holds

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LicenceCC BY
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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.