Evidence map›Paper›PMID 37363797›Full record

ArticleThe Lancet regional health. Europe2023

Impact of COVID-19 on broad-spectrum antibiotic prescribing for common infections in primary care in England: a time-series analyses using OpenSAFELY and effects of predictors including deprivation.

Xiaomin Zhong, Alexander Pate, Ya-Ting Yang, Ali Fahmi, Darren M Ashcroft, Ben Goldacre, Brian MacKenna, Amir Mehrkar, Sebastian Cj Bacon, Jon Massey and 6 more

Open access · goldAbstract read
In one paragraph

Article in The Lancet regional health. Europe, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.8field-weighted citation impact, top 5% 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

10 citing papers in PubMed, 21 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

16 authors at 3 institutions in 1 country.

Xiaomin ZhongCentre for Health Informatics, School of Health Sciences, Faculty of Biology, Medicine, and Health, the University of Manchester, M13 9PL, UK.
Alexander PateCentre for Health Informatics, School of Health Sciences, Faculty of Biology, Medicine, and Health, the University of Manchester, M13 9PL, UK.
Ya-Ting YangCentre for Health Informatics, School of Health Sciences, Faculty of Biology, Medicine, and Health, the University of Manchester, M13 9PL, UK.
Ali FahmiCentre for Health Informatics, School of Health Sciences, Faculty of Biology, Medicine, and Health, the University of Manchester, M13 9PL, UK.
Darren M AshcroftCentre for Pharmacoepidemiology and Drug Safety, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
Ben GoldacreBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
Brian MacKennaBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
Amir MehrkarBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
Sebastian Cj BaconBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
Jon MasseyBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
Louis FisherBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
Peter InglesbyBennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX2 6GG, UK.
OpenSAFELY collaborative
Kieran HandPharmacy Department, Portsmouth Hospitals University NHS Trust, Portsmouth, UK.
Tjeerd van StaaCentre for Health Informatics, School of Health Sciences, Faculty of Biology, Medicine, and Health, the University of Manchester, M13 9PL, UK.
Victoria PalinCentre for Health Informatics, School of Health Sciences, Faculty of Biology, Medicine, and Health, the University of Manchester, M13 9PL, UK.
Manchester Academic Health Science Centre · GBUniversity of Oxford · GBPublic Health England · GB

Funding

Medical Research Council MR/V015737/1Medical Research Council MR/W016729/1Wellcome Trust
6 · The paper itself

Abstract

Background: The COVID-19 pandemic impacted the healthcare systems, adding extra pressure to reduce antimicrobial resistance. Therefore, we aimed to evaluate changes in antibiotic prescription patterns after COVID-19 started. Methods: With the approval of NHS England, we used the OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system in primary care and selected patients prescribed antibiotics from 2019 to 2021. To evaluate the impact of COVID-19 on broad-spectrum antibiotic prescribing, we evaluated prescribing rates and its predictors and used interrupted time series analysis by fitting binomial logistic regression models. Findings: Over 32 million antibiotic prescriptions were extracted over the study period; 8.7% were broad-spectrum. The study showed increases in broad-spectrum antibiotic prescribing (odds ratio [OR] 1.37; 95% confidence interval [CI] 1.36-1.38) as an immediate impact of the pandemic, followed by a gradual recovery with a 1.1-1.2% decrease in odds of broad-spectrum prescription per month. The same pattern was found within subgroups defined by age, sex, region, ethnicity, and socioeconomic deprivation quintiles. More deprived patients were more likely to receive broad-spectrum antibiotics, which differences remained stable over time. The most significant increase in broad-spectrum prescribing was observed for lower respiratory tract infection (OR 2.33; 95% CI 2.1-2.50) and otitis media (OR 1.96; 95% CI 1.80-2.13). Interpretation: An immediate reduction in antibiotic prescribing and an increase in the proportion of broad-spectrum antibiotic prescribing in primary care was observed. The trends recovered to pre-pandemic levels, but the consequence of the COVID-19 pandemic on AMR needs further investigation. Funding: This work was supported by Health Data Research UK and by National Institute for Health Research.

Indexed as

Antimicrobial resistanceBroad-spectrum antibioticsCOVID-19 pandemicPrimary care

Identifiers

PMID37363797
PMCPMC10186397
OpenAlexW4376956826

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.