Evidence map›Paper›PMID 37883697›Full record

SynthesisThe Journal of antimicrobial chemotherapy2023

Prevalence of antibiotic prescribing in COVID-19 patients in China and other low- and middle-income countries during the pandemic (December 2019-March 2021): a systematic review and meta-analysis.

Wenjuan Cong, Hung-Yuan Cheng, Beth Stuart, Binjuan Liu, Yunyi Tang, Yi Wang, Nour AIhusein, Hexing Wang, Amit Manchundiya, Helen Lambert

Open access · hybridAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in The Journal of antimicrobial chemotherapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 12% of its field
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

9 citing papers in PubMed, 10 citations in OpenAlex.

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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

10 authors at 3 institutions in 2 countries.

Wenjuan CongDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, 39 Whatley Road, Bristol BS8 2PS, UK.ORCID 0000-0002-5034-8182
Hung-Yuan ChengDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, 39 Whatley Road, Bristol BS8 2PS, UK.ORCID 0000-0002-6162-4146
Beth StuartCentre for Evaluation and Methods, Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London E1 2AB, UK.
Binjuan LiuDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, 39 Whatley Road, Bristol BS8 2PS, UK.
Yunyi TangDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, 39 Whatley Road, Bristol BS8 2PS, UK.
Yi WangKey Laboratory of Public Health Safety of Ministry of Education, School of Public Health, Fudan University, 130 Dongan Road, Shanghai 200243, China.
Nour AIhuseinDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, 39 Whatley Road, Bristol BS8 2PS, UK.
Hexing WangKey Laboratory of Public Health Safety of Ministry of Education, School of Public Health, Fudan University, 130 Dongan Road, Shanghai 200243, China.
Amit ManchundiyaDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, 39 Whatley Road, Bristol BS8 2PS, UK.
Helen LambertDepartment of Population Health Sciences, Bristol Medical School, University of Bristol, 39 Whatley Road, Bristol BS8 2PS, UK.
University of Bristol · GBFudan University · CNQueen Mary University of London · GB

Funding

British Society of Antimicrobial Chemotherapy BSAC-COVID-72Medical Research Council MR/S013717/1NIHR Advanced Fellowship NIHR301440
6 · The paper itself

Abstract

objectivesLow- and middle-income countries (LMICs) are particularly vulnerable to the threat of antimicrobial resistance (AMR). Use of antibiotics to treat COVID-19 patients during the pandemic may have contributed to increasing the AMR burden, but systematic evidence is lacking.

methodsWe searched Web of Science, EMBASE, PubMed, China National Knowledge Infrastructure (CNKI) and VIP databases from 1 December 2019 to 31 March 2021. Interventional and observation studies across all settings that reported antibiotic use in at least 10 COVID-19 patients were included. We restricted publications to English and Chinese languages. Screening and data extraction were undertaken by at least two independent reviewers. Results were synthesized using random-effects meta-analyses. Subgroup analyses and meta-regression were used to explore heterogeneities. This review was registered with PROSPERO (CRD42021288291).

resultsWe included 284 studies involving 210 611 participants in 19 countries. The antibiotic prescribing rates (APRs) in COVID-19 inpatients were 71.7% (95% CI 66.7%-76.5%) in China and 86.5% (77.1%-93.9%) in other LMICs, respectively. APR was lower in mild/moderate cases in China [66.9% (57.9%-75.4%) compared with 91.8% (71.4%-100%) in other LMICs]. High APRs were found among pregnant women and the elderly in China. Disparities in APRs of other patient groups were identified. In studies reporting bacterial infections, the prevalence was 17.3% (10.0%-25.9%) in China and 24.9% (0.1%-68.8%) in other LMICs. Several antibiotics on the WHO 'Watch' and 'Reserve' lists were prescribed frequently in LMICs.

conclusionsInappropriate antibiotic use and high prevalence of antibiotic prescribing were found in COVID-19 inpatients in many LMICs.

Indexed as

COVID-19Developing CountriesAgedAnti-Bacterial AgentsFemaleHumansPandemicsPregnancyPrevalenceAnti-Bacterial Agents

Identifiers

PMID37883697
PMCPMC10689912
OpenAlexW4387965373

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.