{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T20:09:52Z","timestamp":1790885392012,"version":"4.1.0"},"reference-count":39,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T00:00:00Z","timestamp":1682640000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Medical Practice Plan, American University of Beirut","award":["320153"],"award-info":[{"award-number":["320153"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Background<\/jats:title>\n<jats:p>Infections caused by <jats:italic>Pseudomonas aeruginosa<\/jats:italic> are difficult to treat with a significant cost and burden. In Lebanon, <jats:italic>P<\/jats:italic>. <jats:italic>aeruginosa<\/jats:italic> is one of the most common organisms in ventilator-associated pneumonia (VAP). <jats:italic>P<\/jats:italic>. <jats:italic>aeruginosa<\/jats:italic> has developed widespread resistance to multiple antimicrobial agents such as fluoroquinolones and carbapenems. We aimed at identifying risk factors associated for <jats:italic>P<\/jats:italic>. <jats:italic>aeruginosa<\/jats:italic> infections as well as identifying independent risk factors for developing septic shock and in-hospital mortality.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>We used a cross-sectional study design where we included patients with documented <jats:italic>P<\/jats:italic>. <jats:italic>aeruginosa<\/jats:italic> cultures who developed an infection after obtaining written consent. Two multivariable regression models were used to determine independent predictors of septic shock and mortality.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>During the observed period of 30 months 196 patients were recruited. The most common predisposing factor was antibiotic use for more than 48 hours within 30 days (55%). The prevalence of multi-drug resistant (MDR) <jats:italic>P<\/jats:italic>. <jats:italic>aeruginosa<\/jats:italic> was 10%. The strongest predictors of mortality were steroid use (aOR = 3.4), respiratory failure (aOR = 7.3), identified respiratory cultures (aOR = 6.0), malignancy (aOR = 9.8), septic shock (aOR = 18.6), and hemodialysis (aOR = 30.9).<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>Understanding resistance patterns and risk factors associated with mortality is crucial to personalize treatment based on risk level and to decrease the emerging threat of antimicrobial resistance.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0282276","type":"journal-article","created":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T17:31:25Z","timestamp":1682703085000},"page":"e0282276","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":23,"title":["Clinical predictors of mortality in patients with pseudomonas aeruginosa infection"],"prefix":"10.1371","volume":"18","author":[{"given":"Jim Abi","family":"Frem","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3931-2709","authenticated-orcid":true,"given":"George","family":"Doumat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jamil","family":"Kazma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amal","family":"Gharamti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Souha S.","family":"Kanj","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antoine G.","family":"Abou Fayad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ghassan M.","family":"Matar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8814-1286","authenticated-orcid":true,"given":"Zeina A.","family":"Kanafani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,4,28]]},"reference":[{"key":"pone.0282276.ref001","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.jgar.2018.06.001","article-title":"Systematic review of the use of time series data in the study of antimicrobial consumption and Pseudomonas aeruginosa resistance.","volume":"15","author":"CI Athanasiou","year":"2018","journal-title":"J Glob Antimicrob Resist"},{"issue":"9","key":"pone.0282276.ref002","doi-asserted-by":"crossref","first-page":"942","DOI":"10.1016\/j.ajic.2014.05.029","article-title":"International Nosocomial Infection Control Consortium (INICC) report, data summary of 43 countries for 2007\u20132012.","volume":"42","author":"VD Rosenthal","year":"2014","journal-title":"Device-associated module. 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