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.

IF 2.6 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
PLoS ONE Pub Date : 2024-12-31 eCollection Date: 2024-01-01 DOI:10.1371/journal.pone.0311515
Ali Fahmi, Victoria Palin, Xiaomin Zhong, Ya-Ting Yang, Simon Watts, Darren M Ashcroft, Ben Goldacre, Brian MacKenna, Louis Fisher, Jon Massey, Amir Mehrkar, Seb Bacon, Kieran Hand, Tjeerd Pieter van Staa
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引用次数: 0

Abstract

Background: 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.

Methods: 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.

Results: 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), 0.35-0.36) and UTI (aHR 0.45; 95% CI, 0.44-0.46), compared to URTI (aHR 1.04; 95% CI, 1.03-1.06).

Conclusions: 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.

评估COVID-19大流行对与常见感染相关的住院率的影响:应对初级保健中抗菌素耐药性的风险预测模型
背景:抗菌素耐药性(AMR)是一个多方面的全球挑战,部分原因是不适当的抗生素处方。本研究的目的是评估COVID-19大流行对常见感染治疗的影响,建立风险预测模型,并检查抗生素对感染相关住院的影响。方法:经英国国家医疗服务体系(NHS England)批准,通过opensafety平台获取凤凰合作伙伴(the Phoenix Partnership, TPP)的电子健康记录。我们纳入了2019年1月1日至2022年8月31日期间被初级保健诊断为常见感染的成年患者,包括下呼吸道感染(LRTI)、上呼吸道感染(URTI)和下尿路感染(UTI)。我们排除了感染诊断前90天至感染诊断后30天有COVID-19记录的患者。采用Cox比例风险回归对常见感染诊断后30天内感染相关住院患者建立风险预测模型。结果:2019年1月1日至2022年8月31日,共发现12745,165例感染诊断。其中80395例(2.05%)在随访期间入院。在2019冠状病毒病期间,因感染住院的人数有所下降,例如,LRTI从2019年12月的3950人降至2020年4月的520人。与未开抗生素的患者相比,LRTI患者入院风险降低最大(调整风险比(aHR)为0.35;95%置信区间(CI), 0.35-0.36)和UTI (aHR 0.45;95% CI, 0.44-0.46),与URTI相比(aHR 1.04;95% ci, 1.03-1.06)。结论:发现感染和患者组之间住院风险存在显著差异。抗生素在预防下呼吸道感染和尿路感染的感染相关并发症方面似乎更有效,但在预防尿路感染方面则没有效果。虽然这项研究有一些局限性,但结果表明,关注基于风险的抗生素处方可能有助于解决初级保健中的抗生素耐药性问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS ONE
PLoS ONE 生物-生物学
CiteScore
6.20
自引率
5.40%
发文量
14242
审稿时长
3.7 months
期刊介绍: PLOS ONE is an international, peer-reviewed, open-access, online publication. PLOS ONE welcomes reports on primary research from any scientific discipline. It provides: * Open-access—freely accessible online, authors retain copyright * Fast publication times * Peer review by expert, practicing researchers * Post-publication tools to indicate quality and impact * Community-based dialogue on articles * Worldwide media coverage
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