Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/121283
DC Field | Value | Language |
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dc.contributor.author | Gomila, A. | en_US |
dc.contributor.author | Carratala, J. | en_US |
dc.contributor.author | Eliakim-Raz, N. | en_US |
dc.contributor.author | Shaw, E. | en_US |
dc.contributor.author | Wiegand, I. | en_US |
dc.contributor.author | Vallejo Torres, Laura | en_US |
dc.contributor.author | Gorostiza, A. | en_US |
dc.contributor.author | Vigo, JM | en_US |
dc.contributor.author | Morris, S. | en_US |
dc.contributor.author | Stoddart, M. | en_US |
dc.contributor.author | Grier, S. | en_US |
dc.contributor.author | Vank, C. | en_US |
dc.contributor.author | Cuperus, N. | en_US |
dc.contributor.author | Van den Heuvel, L. | en_US |
dc.contributor.author | Vuong, C. | en_US |
dc.contributor.author | MacGowan, A. | en_US |
dc.contributor.author | Leibovici, L. | en_US |
dc.contributor.author | Addy, I. | en_US |
dc.contributor.author | Pujol, M. | en_US |
dc.date.accessioned | 2023-03-16T13:28:38Z | - |
dc.date.available | 2023-03-16T13:28:38Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.issn | 1178-6973 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/121283 | - |
dc.description.abstract | Purpose: Complicated urinary tract infections (cUTIs) are among the most frequent healthcare-associated infections. In patients with cUTI, Pseudomonas aeruginosa deserves special attention, since it can affect patients with serious underlying conditions. Our aim was to gain insight into the risk factors and prognosis of P. aeruginosa cUTIs in a scenario of increasing multidrug resistance (MDR). Methods: This was a multinational, retrospective, observational study at 20 hospitals in south and southeastern Europe, Turkey, and Israel including consecutive patients with cUTI hospitalized between January 2013 and December 2014. A mixed-effect logistic regression model was performed to assess risk factors for P. aeruginosa and MDR P. aeruginosa cUTI. Results: Of 1,007 episodes of cUTI, 97 (9.6%) were due to P. aeruginosa. Resistance rates of P. aeruginosa were: antipseudomonal cephalosporins 35 of 97 (36.1%), aminoglycosides 30 of 97 (30.9%), piperacillin–tazobactam 21 of 97 (21.6%), fluoroquinolones 43 of 97 (44.3%), and carbapenems 28 of 97 (28.8%). The MDR rate was 28 of 97 (28.8%). Independent risk factors for P. aeruginosa cUTI were male sex (OR 2.61, 95% CI 1.60–4.27), steroid therapy (OR 2.40, 95% CI 1.10–5.27), bedridden functional status (OR 1.79, 95% CI 0.99–3.25), antibiotic treatment within the previous 30 days (OR 2.34, 95% CI 1.38–3.94), indwelling urinary catheter (OR 2.41, 95% CI 1.43–4.08), and procedures that anatomically modified the urinary tract (OR 2.01, 95% CI 1.04–3.87). Independent risk factors for MDR P. aeruginosa cUTI were age (OR 0.96, 95% CI 0.93–0.99) and anatomical urinary tract modification (OR 4.75, 95% CI 1.06–21.26). Readmission was higher in P. aeruginosa cUTI patients than in other etiologies (23 of 97 [23.7%] vs 144 of 910 [15.8%], P=0.04), while 30-day mortality was not significantly different (seven of 97 [7.2%] vs 77 of 910 [8.5%], P=0.6). Conclusion: Patients with P. aeruginosa cUTI had characteristically a serious baseline condition and manipulation of the urinary tract, although their mortality was not higher than that of patients with cUTI caused by other etiologies. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Infection and Drug Resistance | en_US |
dc.source | Infection and Drug Resistance [ISSN 1178-6973], v. 2018 (11), p. 2571—2581, (2018) | en_US |
dc.subject | 32 Ciencias médicas | en_US |
dc.subject | 320505 Enfermedades infecciosas | en_US |
dc.subject.other | Health care-associated infections | en_US |
dc.subject.other | Complicated urinary tract infections | en_US |
dc.subject.other | Pseudomonas aeruginosa | en_US |
dc.subject.other | Multidrug-resistance | en_US |
dc.title | Risk factors and prognosis of complicated urinary tract infections caused by Pseudomonas aeruginosa in hospitalized patients: a retrospective multicenter cohort study | en_US |
dc.type | info:eu-repo/semantics/article | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.2147/IDR.S185753 | en_US |
dc.identifier.scopus | 2-s2.0-85064759664 | - |
dc.identifier.isi | WOS:000453782100001 | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
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dc.contributor.orcid | #NODATA# | - |
dc.description.lastpage | 2581 | en_US |
dc.description.firstpage | 2571 | en_US |
dc.relation.volume | 2018 | en_US |
dc.investigacion | Ciencias de la Salud | en_US |
dc.type2 | Artículo | en_US |
dc.description.numberofpages | 12 | en_US |
dc.utils.revision | Sí | en_US |
dc.identifier.ulpgc | Sí | en_US |
dc.contributor.buulpgc | BU-MED | en_US |
dc.description.sjr | 1,354 | |
dc.description.jcr | 3,0 | |
dc.description.sjrq | Q1 | |
dc.description.jcrq | Q2 | |
dc.description.scie | SCIE | |
item.grantfulltext | open | - |
item.fulltext | Con texto completo | - |
crisitem.author.dept | GIR Economía de la salud y políticas públicas | - |
crisitem.author.dept | Departamento de Métodos Cuantitativos en Economía y Gestión | - |
crisitem.author.orcid | 0000-0001-5833-6066 | - |
crisitem.author.parentorg | Departamento de Métodos Cuantitativos en Economía y Gestión | - |
crisitem.author.fullName | Vallejo Torres, Laura | - |
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