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. 2017 May 26;12(5):e0178178.
doi: 10.1371/journal.pone.0178178. eCollection 2017.

Pseudomonas aeruginosa urinary tract infections in hospitalized patients: Mortality and prognostic factors

Affiliations

Pseudomonas aeruginosa urinary tract infections in hospitalized patients: Mortality and prognostic factors

Jose Luis Lamas Ferreiro et al. PLoS One. .

Abstract

Background: The aim of this study was to analyze the mortality and predictors of 30-day mortality among hospitalized patients with Pseudomonas aeruginosa urinary tract infection (PAUTI) and the impact of antibiotic treatment on survival.

Methods: Patients admitted to our hospital with PAUTI or those diagnosed of PAUTI during hospitalization for other disease between September 2012 and September 2014 were included. Repeated episodes from the same patient were excluded. Database with demographic, clinical and laboratory ítems was created. Empirical and definitive antibiotic therapy, antimicrobial resistance and all-cause mortality at 30 and 90 days were included.

Results: 62 patients were included, with a mean age of 75 years. 51% were male. Mortality was 17.7% at 30 days and 33.9% at 90 days. Factors associated with reduced survival at 30 days were chronic liver disease with portal hypertension (P<0,01), diabetes mellitus (P = 0,04) chronic renal failure (P = 0,02), severe sepsis or septic shock (P<0,01), Charlson index > 3 (P = 0.02) and inadequated definitive antibiotic treatment (P<0,01). Independent risk factors for mortality in multivariate analysis were advanced chronic liver disease (HR 77,4; P<0,01), diabetes mellitus (HR 3,6; P = 0,04), chronic renal failure (HR 4,1; P = 0,03) and inadequated definitive antimicrobial treatment (HR 6,8; P = 0,01).

Conclusions: PAUTI are associated with high mortality in hospitalized patients, which increases significantly in those with severe comorbidity such as chronic renal failure, advanced liver disease or diabetes mellitus. Inadequated antibiotic treatment is associated with poor outcome, which remarks the importance of adjusting empirical antibiotic treatment based on the microbiological susceptibility results.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Kaplan-Meier 30-day survival curve according to advanced liver disease.
P<0.01 (log-rank test).
Fig 2
Fig 2. Kaplan-Meier 30-day survival curve according to diabetes mellitus.
P = 0.04 (log-rank test).
Fig 3
Fig 3. Kaplan-Meier 30-day survival curve according to chronic renal failure.
P = 0.02 (log-rank test).
Fig 4
Fig 4. Kaplan-Meier 30-day survival curve according to severe sepsis or shock.
P<0.01 (log-rank test).
Fig 5
Fig 5. Kaplan-Meier 30-day survival curve according to Charlson index>3.
P = 0.02 (log-rank test).
Fig 6
Fig 6. Kaplan-Meier 30-day survival curve according to inadequate antibiotic treatment.
P<0.01 (log-rank test).

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