Evidence map›Paper›PMID 42524283›Full record

ArticleFrontiers in public health2026

Association between MDROs colonization and subsequent infections in ICU patients: a retrospective cohort study.

Shanbi Cheng, Dejun Tong, Qianqian Zhao, Bing Xiao, Yudong Zhang, Yibo Gong

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Antimicrobial Resistance Profile ofAntibiotics (Basel, Switzerland) · 2026
    Article
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.

Shanbi ChengDepartment of Hospital Infection Control, The Second Xiangya Hospital Central South University, Changsha, Hunan, China.
Dejun TongDepartment of Hospital Infection Control, The Second Xiangya Hospital Central South University, Changsha, Hunan, China.
Qianqian ZhaoDepartment of Emergency, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Bing XiaoDepartment of Emergency, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Yudong ZhangGuilin Hospital of the Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Yibo GongDepartment of Cardiac Surgery, The Second Xiangya Hospital Central South University, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the association between multidrug-resistant organisms (MDROs) colonization and subsequent infection in intensive care unit (ICU) patients. Methods: A retrospective analysis was conducted on 388 ICU patients admitted to the Second Xiangya Hospital between January 2023 and December 2025. Patients were divided into infection ( Results: Among the 388 ICU patients, 99 (25.52, 95%CI: 21.44-30.08%) were colonized by MDROs. A total of 108 MDROs isolates were detected, including 29 strains of ESBL-producing Conclusion: Diabetes, MDROs colonization, high APACHE II scores, and low albumin levels are factors associated with MDROs infection in ICU patients. The nomogram constructed based on these factors may facilitate the early identification of patients at high risk for MDROs infection and provide a basis for individualized treatment strategies.

Indexed as

Cross InfectionDrug Resistance, Multiple, BacterialIntensive Care UnitsAgedChinaFemaleHumansKlebsiella pneumoniaeMaleMethicillin-Resistant Staphylococcus aureusMiddle AgedNomogramsRetrospective StudiesRisk FactorscolonizationICUinfectionmultidrug-resistant organismsrisk factors

Identifiers

PMID42524283
PMCPMC13410322

What OpenQuestion holds

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Registered trials

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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.