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  • 1 January 2017 to 1 January 2018
  • Project No: 335
  • Funding round: FR 12
  • Infection

One in ten women visit their GP each year with symptoms of a urine infection. The most common way to confirm a urine infection and decide on the best antibiotics is to grow the bacteria in a laboratory. Over 6 million urine samples from UK GPs are tested like this every year. However, up to a third will be contaminated by bacteria from the patient’s skin or faeces, meaning infection cannot be proven or ruled out. A contaminated sample can lead to patients suffering from symptoms for longer because of delays in working out the best antibiotic to use, or receiving unnecessary antibiotics (because infection could not be ruled out), increasing their chances of getting infections resistant to antibiotics in the future.

We think that some samples reported as ’contaminated’ might really be infections. We already have funding to begin a study which will collect 1191 urine samples from women contacting their GP with symptoms of urine infection. This proposal is for a complementary project that will increase the information we can get from these samples by seeing whether we can work out which ‘contaminated’ samples are ‘likely infection’ or ‘likely contamination’.

This project will let us collect more information about the patients providing the urine samples. Special techniques which read each bacteria’s genetic code will let us work out what different kinds of bacteria are in ‘contaminated’ samples, to see if these are mostly from skin or faeces, or bacteria known to cause urine infections. We will test whether patient symptoms and outcomes are different in samples we think were infections compared to those we think were contaminated. This project will be a major step forward in understanding what a ‘contaminated’ sample really means.  This may also help GPs make better antibiotic prescribing decisions for this very common infection.

Gail Hayward (Oxford) with co-applicants Chris Butler (Oxford), Michael Moore (Southampton), Alastair Hay (Bristol), Tom Fanshawe (Oxford).

Amount awarded: £107,204

Evidence synthesis working group

The collaboration will be conducting 18 high impact systematic reviews, under four workstreams.

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