Title: Improving Outcomes for Older People with Urinary Tract Infection in Primary Care
Funder: Health and Care Research Wales (Welsh Government)

Abstract: Background Urinary tract infection (UTI) in older people is an important and common condition identified as a major infection related challenge by the Chief Medical Officer of England. The evidence base for several key aspects of management is inadequate, and improved care based on new research evidence is an urgent priority. By analysing routinely collected and linked primary care, secondary care and laboratory data, we will generate robust evidence for the burden of disease, variation in management, most effective antibiotic regimens and predictors of hospitalisation, to fill important gaps identified through systematic literature review. Aims and Objectives To improve the management of older people with UTI in primary care by investigating variation in antibiotic prescribing and its effect on outcomes. Specifically, we aim to: • Estimate the incidence of community-acquired UTI. • Estimate the benefits and harms of prophylactic antibiotics for preventing UTI. • Describe current management. • Estimate the risk of antibiotic treatment failure for different antibiotic regimens. • Derive and validate predictors of hospitalisation from serious or complicated UTI. Plan of investigation We have carried out a systematic literature review of PubMed, MEDLINE and EMBASE to identify important gaps in the current evidence base and inform the objectives of this Fellowship proposal. We propose a series of retrospective observational, hypothesis driven studies using two primary care databases. We will use the Clinical Practice Research Datalink (CPRD) and the Secure Anonymised Information Linkage (SAIL) databank to develop datasets specific to each research objective. The primary outcome for investigation of different antibiotic regimens (choice and duration of therapy) will be antibiotic treatment failure. Secondary outcomes will be re-consultation, recurrent infection, adverse drug reaction, hospitalisation and subsequent urinary antibiotic resistance. Hospitalisation is an important adverse consequence of community acquired UTI in older adults, and has significant health, function and resource implications. We will therefore use the CPRD to identify variables that are predictive of hospitalisation within 28 days of a community acquired UTI. These may include age, sex, measures of social deprivation, co-morbid conditions, previous antibiotic use, antibiotic choice for current episode, history of antibiotic resistant UTI, renal function, and recent hospitalisation. These variables will be used to develop a prognostic model. The validity of this model will then be explored in the SAIL databank to assess its performance. Benefit to patients and the NHS There are clear benefits to patients and the NHS from the findings of the proposed research. Firstly, accurate population based estimates of the incidence and burden of UTI in this important and growing sub-section of the population will enable better planning and provision of care. Secondly, if prophylactic antibiotics have no net benefit, then this represents an opportunity to reduce unnecessary antibiotic use. Thirdly, if variation in antibiotic prescribing for UTI in older people does not improve clinical outcomes, then this suggests a need for improved care through greater standardisation. Data about most effective antibiotic treatment regimen will inform clinical guidelines that aim to standardise care. Fourthly, development of a prognostic score that predicts risk of hospitalisation in older people presenting to primary care with urinary tract symptoms will, once tested, allow clinicians to take a more prudent approach to antibiotic prescribing and encourage prescription of the most appropriate antibiotic first time round, reducing the risk of treatment failure and subsequent hospitalisation.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: RENAL AND UROGENITAL;INFECTION