Evidence map›Paper›PMID 39086796›Full record

ArticleFrontiers in public health2024

Multiple impacts of the COVID-19 pandemic and antimicrobial stewardship on antimicrobial resistance in nosocomial infections: an interrupted time series analysis.

Weibin Li, Xinyi Yang, Chaojie Liu, Xu Liu, Lin Shi, Yingchao Zeng, Haohai Xia, Jia Li, Manzhi Zhao, Shifang Yang and 3 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Clinical microbiology reviews · 2025
    Review
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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

13 authors.

Weibin Li *School of Public Health, Sun Yat-sen University, Guangzhou, China.
Xinyi Yang *School of Public Health, Sun Yat-sen University, Guangzhou, China.
Chaojie LiuSchool of Psychology and Public Health, La Trobe University, Melbourne, VIC, Australia.
Xu LiuDepartment of Infectious Disease, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China.
Lin ShiSchool of Public Health, Sun Yat-sen University, Guangzhou, China.
Yingchao ZengSchool of Public Health, Sun Yat-sen University, Guangzhou, China.
Haohai XiaSchool of Public Health, Sun Yat-sen University, Guangzhou, China.
Jia LiDepartment of Pharmacy, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Manzhi ZhaoDepartment of Pulmonary and Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Shifang YangDepartment of Pulmonary and Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Xiaojie LiDepartment of Laboratory Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Bo HuDepartment of Laboratory Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Lianping YangSchool of Public Health, Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The emergency response to the COVID-19 pandemic may disrupt hospital management activities of antimicrobial resistance (AMR). This study aimed to determine the changing AMR trend over the period in China when stringent COVID-19 response measures were implemented. Methods: This retrospective study was conducted in a designated hospital for COVID-19 patients in Guangzhou, China from April 2018 to September 2021. The prevalence of 13 antimicrobial-resistant bacteria was compared before and after the COVID-19 responses through Chi-square tests. Interrupted time series (ITS) models on the weekly prevalence of AMR were established to determine the changing trend. Controlled ITS models were performed to compare the differences between subgroups. Results: A total of 10,134 isolates over 1,265 days were collected. And antimicrobial-resistant strains presented in 38.6% of the testing isolates. The weekly AMR prevalence decreased by 0.29 percentage point (95% CI [0.05-0.80]) after antimicrobial stewardship (AMS) policy, despite an increase in the prevalence of penicillin-resistant Conclusion: The response to COVID-19 did not lead to an increase in overall AMR; however, it appears that management strategy on the prudent use of antimicrobials likely contributed to a sizable long-term drop. The frequency of several multidrug-resistant bacteria continues to increase after the COVID-19 epidemic. It is crucial to continue to monitor AMR when COVID-19 cases have surged in China after the relaxation of restriction measures.

Indexed as

Antimicrobial StewardshipCOVID-19Cross InfectionInterrupted Time Series AnalysisAnti-Bacterial AgentsChinaDrug Resistance, BacterialFemaleHumansMaleMiddle AgedPandemicsPrevalenceRetrospective StudiesSARS-CoV-2Anti-Bacterial Agentsantimicrobial resistanceantimicrobial stewardshipChinaCOVID-19interrupted time series

Identifiers

PMID39086796
PMCPMC11288819

What OpenQuestion holds

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LicenceCC BY
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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.