Evidence map›Paper›PMID 41322220›Full record

ArticleFrontiers in medicine2025

Construction and validation of a risk assessment scale for multidrug-resistant bacteria infections in critically ill patients.

Jia Zhao, Li Yuan, Yujing Wang, Bing Liu, Xiaoyan Wang, Xuexian Ma, Ping Li

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. 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. 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

7 authors.

Jia ZhaoSchool of Nursing, Xinjiang Medical University, Xinjiang, China.
Li YuanThe Second Affiliated Hospital of Xinjiang Medical University, Xinjiang, China.
Yujing WangSchool of Nursing, Xinjiang Medical University, Xinjiang, China.
Bing LiuThe Second Affiliated Hospital of Xinjiang Medical University, Xinjiang, China.
Xiaoyan WangThe Second Affiliated Hospital of Xinjiang Medical University, Xinjiang, China.
Xuexian MaThe Second Affiliated Hospital of Xinjiang Medical University, Xinjiang, China.
Ping LiThe Second Affiliated Hospital of Xinjiang Medical University, Xinjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To develop a risk assessment scale for infections caused by multidrug-resistant organisms (MDROs) in patients with critical illness and to evaluate its reliability and validity. Methods: An initial risk assessment scale for MDRO infections in patients with critical illness was developed by using a systematic literature review, the Delphi method, and the analytic hierarchy process. Data from 750 critically ill patients admitted to the intensive care unit (ICU) of a Grade A tertiary hospital in China between January 2019 and June 2025 were analyzed. The scale's reliability and validity were assessed through exploratory factor analysis ( Results: The risk assessment scale for MDRO infection in patients with critical illness comprised five dimensions and 20 items. The Cronbach's alpha for the total scale was 0.873. The scale-level content validity index was 0.925, with the content validity indices for individual scale items ranging 0.875-1.000. Exploratory factor analysis enabled the extraction of five common factors, which accounted for 67.861% of the cumulative variance. Confirmatory factor analysis yielded Conclusion: The risk assessment scale for MDRO infection in patients with critical illness demonstrated good reliability and validity, enabling the scientific and reliable assessment of patient infection risk.

Indexed as

Delphi methodmulti-drug resistant bacteriareliabilityscalevalidity

Identifiers

PMID41322220
PMCPMC12660218

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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.