Risk factors for resistance and MDR in community urine isolates: population-level analysis using the NHS Scotland Infection Intelligence Platform

William Malcolm (Lead / Corresponding author), Eilidh Fletcher, Kimberley Kavanagh, Ashutosh Deshpande, Camilla Wiuff, Charis Marwick, Marion Bennie

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    Abstract

    Background: Urinary tract infections (UTI) are common. Antibiotic treatment is usually empirical, with the risk of under-treatment of resistant infections.

    Objectives: To characterise risk factors for antibiotic resistant community urine isolates using routine record linked health data.

    Methods: Within the National Health Service Scotland Infection Intelligence Platform, national surveillance patient-level data on community urine isolates (January 2012-June 30 2015) were linked to hospital activity and community prescribing data. Associations between age, gender, comorbidity, care home residence, previous hospitalisations, antibiotic exposure, and resistant (any antibiotic) or MDR (≥1 antibiotic from ≥3 categories) urinary isolates were quantified using multivariable logistic regression.

    Results: Of 40,984 isolates, 28% were susceptible, 45% resistant, and 27% MDR. Exposure to ≥ 4 different antibiotics in the prior six months increased MDR risk, OR 6.81 (95%CI 5.73-36 8.11). MDR was associated with ≥29 DDD cumulative exposure, in the prior six months, for any antibiotic (OR 6.54, 95%CI 5.88-7.27), nitrofurantoin (OR 8.56, 95%CI 6.56-11.18) and trimethoprim (OR 14.61, 95%CI10.53-20.27). Associations persisted for 10-12 months for nitrofurantoin (OR 2.31, 95%CI 1.93-2.76) and trimethoprim (OR 1.81, 95%CI 1.57-2.09). Increasing age, comorbidity, previous hospitalisation and care home residence were independently associated with MDR. For resistant isolates the factors were the same but with weaker associations.

    Conclusion: We have demonstrated, using national capability at scale, the risk of MDR in community urine isolates for the first time and quantified the cumulative and sustained impact of antibiotic exposure. These data will inform the development of decision support tools for UTI treatment.
    Original languageEnglish
    Pages (from-to)223-230
    Number of pages8
    JournalJournal of Antimicrobial Chemotherapy
    Volume73
    Issue number1
    Early online date10 Oct 2017
    DOIs
    Publication statusPublished - 10 Oct 2017

    Keywords

    • Antibiotics
    • Antibiotic resistance
    • Bacterial
    • Decision support systems
    • Urinary tract infection
    • Comorbidity
    • Intelligence

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