Condition-specific surveillance in health care-associated urinary tract infections as a strategy to improve empirical antibiotic treatment: an epidemiological modelling study

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dc.authoridCai, Tommaso/0000-0002-7234-3526
dc.authoridtandogdu, zafer/0000-0002-5309-3656
dc.authoridKoves, Bela/0000-0001-6886-0750
dc.authorwosidCai, Tommaso/AAC-5939-2021
dc.authorwosidNaber, Kurt/AAR-9997-2020
dc.contributor.authorTandogdu, Zafer
dc.contributor.authorKoves, Bela
dc.contributor.authorCai, Tommaso
dc.contributor.authorCek, Mete
dc.contributor.authorTenke, Peter
dc.contributor.authorNaber, Kurt
dc.contributor.authorWagenlehner, Florian
dc.date.accessioned2024-06-12T10:51:55Z
dc.date.available2024-06-12T10:51:55Z
dc.date.issued2020
dc.departmentTrakya Üniversitesien_US
dc.description.abstractBackground Health care-associated urinary tract infection (HAUTI) consists of unique conditions (cystitis, pyelonephritis and urosepsis). These conditions could have different pathogen diversity and antibiotic resistance impacting on the empirical antibiotic choices. The aim of this study is to compare the estimated chances of coverage of empirical antibiotics between conditions (cystitis, pyelonephritis and urosepsis) in urology departments from Europe. Methods A mathematical modelling based on antibiotic susceptibility data from a point prevalence study was carried. Data were obtained for HAUTI patients from multiple urology departments in Europe from 2006 to 2017. The primary outcome of the study is the Bayesian weighted incidence syndromic antibiogram (WISCA) and Bayesian factor. Bayesian WISCA is the estimated chance of an antibiotic to cover the causative pathogens when used for first-line empirical treatment. Bayesian factor is used to compare if HAUTI conditions did or did not impact on empirical antibiotic choices. Results Bayesian WISCA of antibiotics in European urology departments from 2006 to 2017 ranged between 0.07 (cystitis, 2006, Amoxicillin) to 0.89 (pyelonephritis, 2009, Imipenem). Bayesian WISCA estimates were lowest in urosepsis. Clinical infective conditions had an impact on the Bayesian WISCA estimates (Bayesian factor > 3 in 81% of studied antibiotics). The main limitation of the study is the lack of local data. Conclusions Our estimates illustrate that antibiotic choices can be different between HAUTI conditions. Findings can improve empirical antibiotic selection towards a personalized approach but should be validated in local surveillance studies.en_US
dc.identifier.doi10.1007/s00345-019-02963-9
dc.identifier.endpage34en_US
dc.identifier.issn0724-4983
dc.identifier.issn1433-8726
dc.identifier.issue1en_US
dc.identifier.pmid31555835en_US
dc.identifier.scopus2-s2.0-85074041102en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage27en_US
dc.identifier.urihttps://doi.org/10.1007/s00345-019-02963-9
dc.identifier.urihttps://hdl.handle.net/20.500.14551/18529
dc.identifier.volume38en_US
dc.identifier.wosWOS:000511866800005en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofWorld Journal Of Urologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAntibiotic Stewardshipen_US
dc.subjectHealth Care-Associated UTIen_US
dc.subjectCondition-Specific Surveillanceen_US
dc.subjectBlood-Stream Infectionsen_US
dc.subjectAntimicrobial Resistanceen_US
dc.subjectOutcomesen_US
dc.subjectMulticenteren_US
dc.subjectPrevalenceen_US
dc.titleCondition-specific surveillance in health care-associated urinary tract infections as a strategy to improve empirical antibiotic treatment: an epidemiological modelling studyen_US
dc.typeArticleen_US

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