Clinical prediction tool to identify patients with Pseudomonas aeruginosa respiratory tract infections at greatest risk for multidrug resistance
about
A prediction tool for nosocomial multi-drug Resistant Gram-Negative Bacilli infections in critically ill patients - prospective observational study.Acquisition of Pseudomonas aeruginosa and its resistance phenotypes in critically ill medical patients: role of colonization pressure and antibiotic exposureAbility of an antibiogram to predict Pseudomonas aeruginosa susceptibility to targeted antimicrobials based on hospital day of isolation.Relationship between various definitions of prior antibiotic exposure and piperacillin-tazobactam resistance among patients with respiratory tract infections caused by Pseudomonas aeruginosaUpdate on the treatment of Pseudomonas aeruginosa pneumonia.Prevalence and risk factors associated with colonization and infection of extensively drug-resistant Pseudomonas aeruginosa: a systematic review.Alterations in two-component regulatory systems of phoPQ and pmrAB are associated with polymyxin B resistance in clinical isolates of Pseudomonas aeruginosa.Impact of multidrug resistance on Pseudomonas aeruginosa ventilator-associated pneumonia outcome: predictors of early and crude mortality.Differential Role of Two-Component Regulatory Systems (phoPQ and pmrAB) in Polymyxin B Susceptibility of Pseudomonas aeruginosaClinical epidemiology of carbapenem-intermediate or -resistant Enterobacteriaceae.Hand hygiene, and not ertapenem use, contributed to reduction of carbapenem-resistant Pseudomonas aeruginosa rates.Prediction of imipenem-resistant microorganisms among the nosocomial critically ill patients with Gram-negative bacilli septicemia: a simple risk score.Risk factors for hospitalized patients with resistant or multidrug-resistant Pseudomonas aeruginosa infections: a systematic review and meta-analysis.
P2860
Q34611874-5D382EF0-1904-41FE-A46B-260BA10CD3EEQ35608657-15BE1DA9-CB4A-4631-A653-A905FA85BB53Q36776315-1735A212-5D8E-4A59-8D85-F274F9B0BEE0Q36803995-53101A25-6FB9-4357-8C4A-600E8D8A5263Q37516904-D55C9AFD-D024-483F-AACC-F5A928589F2BQ38543852-3520E0FB-893B-458A-89A6-184220CFB241Q41964844-C267BD23-1455-4342-B5AC-05EF134EB474Q42277755-041EA7AD-B129-499F-81FD-A977E4BF84FEQ42816882-D27DCF0A-45B2-44E9-89DE-CB81A770DD6CQ45223414-B969DA83-F62F-42B5-ACE5-34E0717EF07BQ51034635-2BE709B8-3D09-4D92-A319-1C671CAE6721Q53702251-562CC1E0-89EB-4F19-935B-053E012D9EBEQ55649599-EA062B49-1370-48AD-B325-69A648419941
P2860
Clinical prediction tool to identify patients with Pseudomonas aeruginosa respiratory tract infections at greatest risk for multidrug resistance
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年論文
@yue
2006年論文
@zh-hant
2006年論文
@zh-hk
2006年論文
@zh-mo
2006年論文
@zh-tw
2006年论文
@wuu
2006年论文
@zh
2006年论文
@zh-cn
name
Clinical prediction tool to id ...... risk for multidrug resistance
@ast
Clinical prediction tool to id ...... risk for multidrug resistance
@en
type
label
Clinical prediction tool to id ...... risk for multidrug resistance
@ast
Clinical prediction tool to id ...... risk for multidrug resistance
@en
prefLabel
Clinical prediction tool to id ...... risk for multidrug resistance
@ast
Clinical prediction tool to id ...... risk for multidrug resistance
@en
P2093
P2860
P356
P1476
Clinical prediction tool to id ...... risk for multidrug resistance
@en
P2093
Ben Lomaestro
Christopher D Miller
Eileen Graffunder
Jeffrey Graves
Jon P Furuno
Louise-Anne McNutt
Thomas P Lodise
P2860
P304
P356
10.1128/AAC.00851-06
P407
P577
2006-12-11T00:00:00Z