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INFECTION

Understanding clinical variables to improve empirical antibiotic therapy for UTI

A recent study showed a correlation between clinical patient features and antibiotic resistance in patients with urinary tract infection (UTI). As resistance to antibiotics cannot be reversed, managing its emergence is of the utmost importance. Improving surveillance data will enable selection of appropriate antibiotics and help reduce the development of resistance.

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References

  1. Yelin, I. et al. Personal clinical history predicts antibiotic resistance of urinary tract infections. Nat. Med. 25, 1143–1152 (2019).

    Article  CAS  Google Scholar 

  2. Sundqvist, M. et al. Little evidence for reversibility of trimethoprim resistance after a drastic reduction in trimethoprim use. J. Antimicrob. Chemother. 65, 350–360 (2010).

    Article  CAS  Google Scholar 

  3. Eliakim-Raz, N. et al. Risk factors for treatment failure and mortality among hospitalized patients with complicated urinary tract infection: a multicenter retrospective cohort study (RESCUING Study Group). Clin. Infect. Dis. 68, 29–36 (2019).

    PubMed  Google Scholar 

  4. Tandog˘du, Z. et al. Antimicrobial resistance in urosepsis: outcomes from the multinational, multicenter global prevalence of infections in urology (GPIU) study 2003–2013. World J. Urol. 34, 1193–1200 (2016).

    Article  Google Scholar 

  5. Paul, M. et al. Improving empirical antibiotic treatment using TREAT, a computerized decision support system: cluster randomized trial. J. Antimicrob. Chemother. 58, 1238–1245 (2006).

    Article  CAS  Google Scholar 

  6. Tandogdu, Z. et al. Appropriate empiric antibiotic choices in health care associated urinary tract infections in urology departments in Europe from 2006 to 2015: a Bayesian analytical approach applied in a surveillance study. PLOS ONE 14, e0214710 (2019).

    Article  CAS  Google Scholar 

  7. Haldrup, S. et al. Microbiological point of care testing before antibiotic prescribing in primary care: considerable variations between practices. BMC Fam. Pract. 18, 9 (2017).

    Article  Google Scholar 

  8. Fritzenwanker, M. et al. Modern diagnostic methods for urinary tract infections. Expert Rev. Anti. Infect. Ther. 14, 1047–1063 (2016).

    Article  CAS  Google Scholar 

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Correspondence to Florian M. Wagenlehner or Kurt G. Naber.

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Competing interests

F.M.W. declares personal fees and other from Bionorica, during the conduct of the study; personal fees and other from Achaogen, personal fees from AstraZeneca, personal fees and other from Bionorica, other from Enteris BioPharma, other from Helperby Therapeutics, personal fees from Janssen, personal fees from LeoPharma, personal fees from MerLion, personal fees from Merck Sharp and Dohme (MSD), personal fees and other from OM Pharma/Vifor Pharma, personal fees from Pfizer, personal fees from RosenPharma, personal fees and other from Shionogi, personal fees from VenatoRx, personal fees from GlaxoSmithKline (GSK) and other from Deutsches Zentrum für Infektionsforschung (DZIF) (Giessen-Marburg-Langen site), outside the submitted work. K.G.N declares personal fees from Adamed, personal fees from Allecra, personal fees from Apogepha, personal fees from Aristo, personal fees from Bionorica, personal fees from Biomerieux, personal fees from Enteris, personal fees from GlaxoSmithKline, personal fees from Gruenenthal Mexico, personal fees from Helperby, personal fees from Marpinion, personal fees from MerLion, personal fees from Medice, non-financial support from Mission Pharmacal, personal fees from MSD, personal fees from OM Pharma/Vifor, personal fees from Paratek, personal fees from Roche, personal fees from Saxonia and personal fees from Zambon, outside the submitted work.

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Wagenlehner, F.M., Naber, K.G. Understanding clinical variables to improve empirical antibiotic therapy for UTI. Nat Rev Urol 16, 695–696 (2019). https://doi.org/10.1038/s41585-019-0240-0

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