{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T21:05:10Z","timestamp":1776373510726,"version":"3.51.2"},"reference-count":37,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T00:00:00Z","timestamp":1735603200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100023699","name":"Health Data Research UK","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100023699","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000272","name":"National Institute for Health and Care Research","doi-asserted-by":"publisher","award":["NIHR130581"],"award-info":[{"award-number":["NIHR130581"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013235","name":"NIHR Greater Manchester Patient Safety Translational Research Centre","doi-asserted-by":"publisher","award":["PSTRC-2016-003"],"award-info":[{"award-number":["PSTRC-2016-003"]}],"id":[{"id":"10.13039\/501100013235","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000272","name":"National Institute for Health and Care Research","doi-asserted-by":"publisher","award":["NIHR303781"],"award-info":[{"award-number":["NIHR303781"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Background<\/jats:title>\n<jats:p>Antimicrobial resistance (AMR) is a multifaceted global challenge, partly driven by inappropriate antibiotic prescribing. The objectives of this study were to evaluate the impact of the COVID-19 pandemic on treatment of common infections, develop risk prediction models and examine the effects of antibiotics on infection-related hospital admissions.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>With the approval of NHS England, we accessed electronic health records from The Phoenix Partnership (TPP) through OpenSAFELY platform. We included adult patients with primary care diagnosis of common infections, including lower respiratory tract infection (LRTI), upper respiratory tract infections (URTI), and lower urinary tract infection (UTI), from 1 January 2019 to 31 August 2022. We excluded patients with a COVID-19 record in the 90 days before to 30 days after the infection diagnosis. Risk prediction models using Cox proportional-hazard regression were developed for infection-related hospital admission in the 30 days after the common infection diagnosis.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>We found 12,745,165 infection diagnoses from 1 January 2019 to 31 August 2022. Of them, 80,395 (2.05%) cases were admitted to the hospital during follow-up. Counts of hospital admission for infections dropped during COVID-19, for example LRTI from 3,950 in December 2019 to 520 in April 2020. Comparing those prescribed an antibiotic to those without, reduction in risk of hospital admission were largest with LRTI (adjusted hazard ratio (aHR) of 0.35; 95% confidence interval (CI), 0.35\u20130.36) and UTI (aHR 0.45; 95% CI, 0.44\u20130.46), compared to URTI (aHR 1.04; 95% CI, 1.03\u20131.06).<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusions<\/jats:title>\n<jats:p>A substantial variation in hospital admission risks between infections and patient groups was found. Antibiotics appeared more effective in preventing infection-related complications with LRTI and UTI, but not URTI. While this study has several limitations, the results indicate that a focus on risk-based antibiotic prescribing could help tackle AMR in primary care.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0311515","type":"journal-article","created":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T18:50:42Z","timestamp":1735671042000},"page":"e0311515","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["Evaluation of the impact of COVID-19 pandemic on hospital admission related to common infections: Risk prediction models to tackle antimicrobial resistance in primary care"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1661-4475","authenticated-orcid":true,"given":"Ali","family":"Fahmi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Victoria","family":"Palin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3448-6702","authenticated-orcid":true,"given":"Xiaomin","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ya-Ting","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Watts","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2958-915X","authenticated-orcid":true,"given":"Darren M.","family":"Ashcroft","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ben","family":"Goldacre","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brian","family":"MacKenna","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Louis","family":"Fisher","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2497-4040","authenticated-orcid":true,"given":"Jon","family":"Massey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amir","family":"Mehrkar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seb","family":"Bacon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"the OpenSAFELY Collaborative","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3834-2415","authenticated-orcid":true,"given":"Kieran","family":"Hand","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tjeerd Pieter","family":"van Staa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2024,12,31]]},"reference":[{"key":"pone.0311515.ref001","first-page":"1","article-title":"Combatting antimicrobial resistance globally.","author":"R Sugden","year":"2016","journal-title":"Nat Microbiol."},{"key":"pone.0311515.ref002","first-page":"1","article-title":"ESPAUR Oversight Group Writing Committee. English surveillance programme for antimicrobial utilisation and resistance (ESPAUR): Report 2020 to 2021.","author":"D Ashiru-Oredope","year":"2021","journal-title":"Public Heal Engl Publ"},{"key":"pone.0311515.ref003","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12916-020-01581-2","article-title":"Development and validation of a multivariable prediction model for infection-related complications in patients with common infections in UK primary care and the extent of risk-based prescribing of antibiotics","volume":"18","author":"C Mistry","year":"2020","journal-title":"BMC Med"},{"key":"pone.0311515.ref004","doi-asserted-by":"crossref","first-page":"762","DOI":"10.1016\/j.cmi.2021.02.007","article-title":"Investigating the impact of COVID-19 on primary care antibiotic prescribing in North West London across two epidemic waves","volume":"27","author":"N Zhu","year":"2021","journal-title":"Clin Microbiol Infect"},{"key":"pone.0311515.ref005","first-page":"10","article-title":"The impact of the covid\u201019 pandemic on antibiotic prescribing trends in outpatient care: A nationwide, quasi\u2010experimental approach.","author":"TM Silva","year":"2021","journal-title":"Antibiotics."},{"key":"pone.0311515.ref006","first-page":"11","article-title":"Infection-related complications after common infection in association with new antibiotic prescribing in primary care: Retrospective cohort study using linked electronic health records","author":"B van Bodegraven","year":"2021","journal-title":"BMJ Open"},{"key":"pone.0311515.ref007","first-page":"13","article-title":"Knowledge support for optimising antibiotic prescribing for common infections in general practices: evaluation of the effectiveness of periodic feedback, decision support during consultations and peer comparisons in a cluster randomised trial (BRIT2)\u2013st.","author":"TP van Staa","year":"2023","journal-title":"BMJ Open"},{"key":"pone.0311515.ref008","unstructured":"NHS. 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