Umeå University's logo

umu.sePublications
Operational message
There are currently operational disruptions. Troubleshooting is in progress.
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Strategies to reduce antibiotic use in women with uncomplicated urinary tract infection in primary care: protocol of a systematic review and meta-analysis including individual patient data
Show others and affiliations
2020 (English)In: BMJ Open, E-ISSN 2044-6055, Vol. 10, no 10, article id e035883Article, review/survey (Refereed) Published
Abstract [en]

Introduction: Uncomplicated urinary tract infection (UTI) in women is a common reason to present in general practice and is usually treated with antibiotics to reduce symptom severity and duration. Results of recent clinical trials indicate that non-antibiotic treatment approaches can also be effective. However, it remains unclear which patients would benefit from antibiotic treatment and which can effectively and safely be treated without antibiotics. This systematic review and meta-analysis aims to estimate the effect of treatment strategies to reduce antibiotic use in comparison with immediate antibiotic treatment and to identify prognostic factors and moderators of treatment effects. A further aim is to identify subgroups of patients benefiting from a specific therapy.

Methods and analysis: A systematic literature search will be performed to identify randomised controlled trials which investigated the effect of treatment strategies to reduce antibiotic use in female adults with uncomplicated UTI compared with immediate antibiotic treatment. Therefore, the primary outcome of the meta-analysis is incomplete recovery. Anonymised individual patient data (IPD) will be collected. Aggregate data will be used for pairwise comparisons of treatment strategies using meta-analysis models with random effects accounting for potential between-study heterogeneity. Potential effect moderators will be explored in meta-regressions. For IPD, generalised linear mixed models will be used, which may be adjusted for baseline characteristics. Interactions of baseline variables with treatment effects will be explored. These models will be used to assess direct comparisons of treatment, but might be extended to networks.

Ethics and dissemination: The local institutional review and ethics board judged the project a secondary analysis of existing anonymous data which meet the criteria for waiver of ethics review. Dissemination of the results will be via published scientific papers and presentations. Key messages will be promoted for example, via social media or press releases.

Place, publisher, year, edition, pages
BMJ Publishing Group Ltd, 2020. Vol. 10, no 10, article id e035883
Keywords [en]
urinary tract infections, general medicine (see internal medicine), adult urology
National Category
Infectious Medicine General Practice
Identifiers
URN: urn:nbn:se:umu:diva-176557DOI: 10.1136/bmjopen-2019-035883ISI: 000578439600015PubMedID: 33004385Scopus ID: 2-s2.0-85092511257OAI: oai:DiVA.org:umu-176557DiVA, id: diva2:1500113
Available from: 2020-11-11 Created: 2020-11-11 Last updated: 2023-08-28Bibliographically approved

Open Access in DiVA

fulltext(436 kB)303 downloads
File information
File name FULLTEXT01.pdfFile size 436 kBChecksum SHA-512
4ca6dd6c75dace79bb832846cf866db41e0100171ca84598e0582521cf771a699c5810be3a0c7d2e0b9ad984f290024558b7208d94761c64a9d41fc1dded5f36
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMedScopus

Authority records

Ferry, SvenMonsen, Tor

Search in DiVA

By author/editor
Rover, ChristianMoore, MichaelFerry, SvenMonsen, Tor
By organisation
Clinical Bacteriology
In the same journal
BMJ Open
Infectious MedicineGeneral Practice

Search outside of DiVA

GoogleGoogle Scholar
Total: 303 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 365 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf