Evidence map›Paper›PMID 40325379›Full record

ArticleBMC infectious diseases2025

Point-prevalence surveys of hospital-acquired infections in 42 Chinese hospitals in Weifang, China: from 2015 to 2020.

Yu Dong, Hongqing Liu

Abstract read
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

2 authors.

Yu DongSchool of Public Health, Shandong Second Medical University, Weifang, China.
Hongqing LiuSchool of Public Health, Shandong Second Medical University, Weifang, China. liuhq576@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHospital-acquired infections (HAIs) are a major health challenge, especially for developing countries. Therefore, this study investigated the prevalence of HAIs in 42 Chinese hospitals in Weifang, China.

methodsThe definition of HAIs was identified using the Ministry of Health of the People's Republic of China. One-day cross-sectional surveys were annually performed from 2015 to 2020. The trained staff collected information on the prevalence of HAIs, isolated pathogens, and antibiotic use.

resultsAmong the surveyed inpatients, 1.66% developed HAIs, with a significant decline in HAI prevalence from 2015 (1.84%) to 2020 (1.55%) (Z = -4.206, P < 0.001). The ICU exhibited the highest prevalence of HAIs at 19.04%. Lower respiratory tract infections accounted for 46.32% of total cases. Moreover, a total of 1,297 bacterial isolates were identified, with Pseudomonas aeruginosa (218 isolates, 16.8%), Klebsiella pneumoniae (199 isolates, 15.3%), and Escherichia coli (133 isolates, 10.3%) being the most prevalent. The most frequently detected resistant pathogen was Carbapenem-Resistant Enterobacteriaceae(218 isolates,37.20%).Antimicrobial usage reached 35.19%, accompanied by a notable increase in pathogen testing submissions over the study period (Z = 4.287, P < 0.001).

conclusionsThe overall prevalence of HAIs across 42 hospitals shows a declining trend. The prevention and control of healthcare-associated pathogens and multidrug-resistant organisms remain key priorities. Ensuring the rational use of antimicrobial agents is also a critical focus for future efforts.

Indexed as

Cross InfectionAdultAgedAnti-Bacterial AgentsBacteriaChinaCross-Sectional StudiesFemaleHospitalsHumansMaleMiddle AgedPrevalenceRespiratory Tract InfectionsYoung AdultAnti-Bacterial AgentsAntimicrobial useChinaHospital-acquired infectionsPoint prevalence survey

Identifiers

PMID40325379
PMCPMC12054055

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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.