Amoxicillin is associated with a lower risk of further antibiotic prescriptions for lower respiratory tract infections in primary care – A database analysis spanning over 30 years

ABSTRACT

Antibiotic prescriptions for lower respiratory tract infections occur commonly in primary care but there is uncertainty about the most effective initial treatment strategy. Both increasing antimicrobial resistance and awareness of preventable harm from medicines make resolving this uncertainty a priority. Pragmatic, real-life epidemiological investigations are needed to inform future interventional studies.

In this cross-sectional database study we analysed antibiotic prescriptions for non-pneumonic, lower respiratory tract infections (LRTI) in primary care as captured in the Optimum Care Database from 1984 to 2017. The primary outcome was a second antibiotic prescription for a LRTI code within 14 days of index prescription, the secondary outcome further antibiotic prescription for any indication. Only individuals without chronic respiratory diseases were included. We conducted univariable analysis to identify factors associated with repeat prescriptions and generate hypotheses for forthcoming projects.

We analysed 367,188 index prescriptions for LRTI. Amoxicillin was the commonest used index drug (65.1%). In 6% a second antibiotic course coded for a further LRTI was prescribed (11.2% without this coding restriction). Further antibiotic prescriptions for LRTI were significantly associated with older age, previous smoking, seven day index courses and not using amoxicillin initially. The largest effect size was seen when amoxicillin was not used as index drug (odds ratio (OR) 1.15, p < 0.001). This would support current prescribing practice for amoxicillin as index drug in those without respiratory disease. Prospective studies are needed to explore the observed differences.

KEYWORDS:

• Antibiotics
• lower respiratory tract infections
• primary care
• amoxicillin
• treatment failure
• database

Acknowledgements

Derek Skinner, data analyst, and Victoria Carter, Optimum Patient Care, Cambridge, UK; Alison Chisholm, previously at Optimum Patient Care, Cambridge, UK. In collaboration with the Respiratory Effectiveness Group.

Declaration of interest

We are grateful to the Eleanor Peel Trust for providing funding for bespoke data extraction and database creation from the OPC. Marie Stolbrink is funded by a National Institute for Health Research Academic Clinical Fellowship. Laura J Bonnett is funded by a NIHR Post-Doctoral Fellowship (PDF-2015-08-044). The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research, or the Department of Health.

Supplementary material

Supplemental data for this article can be accessed here.

Additional information

Funding

This work was supported by the Dowager Countess Eleanor Peel Trust; National Institute for Health Research [PDF-2015-08-044]; National Institute for Health Research [Academic Clinical Fellowship].

Notes on contributors

Marie Stolbrink

Dr Marie Stolbrink is a NIHR Academic Clinical Fellow in respiratory medicine at the University of Liverpool and a respiratory physician. She has an interest in non-communicable lung disease and global health.

Laura J. Bonnett

Laura Bonnett is an Medical Statistician in the Department of Biostatistics at the University of Liverpool, Liverpool, UK.  She is a Chartered Statistician and a member of the Royal Statistical Society’s Education and Statistical Literacy Committee.  Laura specialises in the development and validation of clinical prediction models in a diverse range of medical conditions from asthma to psychosis, and epilepsy to tuberculosis.

John D. Blakey

John Blakey is a consultant in Respiratory Medicine with a special interest in airways disease, undertaking weekly severe asthma and community airways disease clinics. He is co-founder and Clinical Group chair of the North West Severe Asthma Service and Respiratory SRG Lead for NIHR North West Coast CRN. His PhD research concentrated on population genetics before subsequently undertaking research with more immediate clinical relevance including award-winning projects in information technology. His current focus is on the development and validation of tools to assess the future risk of asthma attacks both in the UK and in lower income countries.