Evidence map›Paper›PMID 41547842›Full record

Observational studyAntimicrobial resistance and infection control2026

Point-prevalence of healthcare-associated infections and antimicrobial use in a tertiary hospital in Shanghai, China: 2012-2023.

Ya Yang, Ruihong Shen, Feng Lu, Bingchao Cai, Mei Huang, Jiayan Ding, Yayun Yuan, Xiaobo Gui, Sijin Yan, Luyao Li and 5 more

Abstract readObservational Study
In one paragraph

Observational study in Antimicrobial resistance and infection control, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Ya Yang *Department of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Ruihong Shen *Department of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Feng Lu *Department of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Bingchao CaiDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Mei HuangDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Jiayan DingDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Yayun YuanDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xiaobo GuiDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Sijin YanDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Luyao LiDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Shiwen HuangDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Xiaofang FuDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Haiqun BanDepartment of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. banhaiqun@renji.com.
Xingrong GongDepartment of Medical Administration, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. gongxingrong@renji.com.
Zheng WangDepartment of Gastrointestinal Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. wangzheng@renji.com.

Funding

National Natural Science Foundation of China 72504176Shanghai Pujiang Program 22PJD041Shanghai Shenkang Hospital Development Center SHDC22022213
6 · The paper itself

Abstract

backgroundHealthcare-associated infections (HAIs) are a global public health issue and a major threat to patient safety. This study aimed to estimate the prevalence of HAIs and antimicrobial use in a tertiary hospital in Shanghai, China.

methodsPoint-prevalence surveys were conducted annually from 2012 to 2023. All inpatients present on the survey day were included. Data were analyzed to identify trends and patterns in the prevalence of HAIs and antimicrobial use.

resultsThe overall prevalence of HAIs was 3.97%, with significant variations observed across departments, age groups and patient populations, whether undergoing surgery or not. There was a significant upward trend in surgical wards from 3.97% in 2012 to 4.82% in 2023 (β = 0.135, P = 0.003). The prevalence of catheter-associated urinary tract infection showed a significant decreasing trend (β = - 0.032, P < 0.001). There was an increasing trend in the proportion of patients receiving single-agent antimicrobial use for prophylactic and therapeutic purposes. The most frequently isolated pathogens were Acinetobacter baumannii, Klebsiella pneumoniae, and Escherichia coli, which exhibited high rates of resistance to carbapenems.

conclusionDespite some progress, challenges regarding HAIs and antimicrobial resistance persist in a tertiary care setting. The findings highlight the necessity for targeted infection control measures and robust antimicrobial stewardship programs to mitigate the burden of HAIs and optimize antimicrobial use.

Indexed as

Anti-Infective AgentsCross InfectionTertiary Care CentersAdultAgedAged, 80 and overAntibiotic ProphylaxisChinaFemaleHumansLength of StayMaleMiddle AgedPrevalenceAnti-Infective AgentsAntimicrobial useChinaHealthcare-associated infectionPoint-prevalence survey

Identifiers

PMID41547842
PMCPMC12896229

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.