Predictors of Nosocomial Bloodstream Infections Among Critically Ill Adult Trauma Patients: A Model Testing Approach

2.50
Hdl Handle:
http://hdl.handle.net/10755/149249
Type:
Presentation
Title:
Predictors of Nosocomial Bloodstream Infections Among Critically Ill Adult Trauma Patients: A Model Testing Approach
Abstract:
Predictors of Nosocomial Bloodstream Infections Among Critically Ill Adult Trauma Patients: A Model Testing Approach
Conference Sponsor:Sigma Theta Tau International
Conference Year:2003
Author:El-Masri, Maher M., RN, PhD
P.I. Institution Name:University of Windsor
Title:Assistant Professor
Co-Authors:Denise M. Korniewicz, RN, DNSc
Objective: The objectives of this study were to 1) identify the independent predictors of nosocomial bloodstream infections (NBSI) in the critically ill adult trauma population (CIATP); and 2) examine a theory that specifies the abstract dimensions of these predictors. Design: A prospective non-experimental cohort design was conducted over a 9-months period to collect data on a sample of 361 CIATP. Method: Crude univariate analysis was performed to identify the unadjusted predictors and significant interaction effects. A forward stepwise multivariate logistic regression analysis was then conducted to identify the independent predictors of NBSI. Second-order latent variable confirmatory factor analysis (CFA) was performed to identify the dimensions of the resulting independent predictors and examine the empirical validity of the resulting theoretical model. Findings: The crude univariate analysis suggested significant association between NBSI and more than 24 variables from 32 included in the analysis. However, multivariate logistic regression analysis showed that only nine variables were independent predictors of NBSI at an alpha of (0.05) and 95% confidence interval (CI); Chest tube, use of immunosuppressives, presence of microbial resistance, outcome length of stay, presence of pre-existing infections, percent change of albumin level , patient disposition, transfusion of 10 or more PRBC, and number of CVC catheters. The resulting regression model had a positive predictive value of (76.7%) and a negative predictive value of (93%). Second-order CFA showed that the nine independent predictors load into three higher level dimensions; therapy, microbial and circumstantial. Conclusions: NBSI in CIATP has nine predicting variables. These nine variables are theoretically categorized into three dimensions; therapeutic, microbial and circumstantial. Implications: The development and testing of a model to predict NBSI is expected to enhances future research efforts and assist clinicians identify early “at risk” patients, minimize associated risks, and provide directions for improvement of practice and treatment policies.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titlePredictors of Nosocomial Bloodstream Infections Among Critically Ill Adult Trauma Patients: A Model Testing Approachen_GB
dc.identifier.urihttp://hdl.handle.net/10755/149249-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Predictors of Nosocomial Bloodstream Infections Among Critically Ill Adult Trauma Patients: A Model Testing Approach</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2003</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">El-Masri, Maher M., RN, PhD</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Windsor</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Assistant Professor</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">melmasri@uwindsor.ca</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">Denise M. Korniewicz, RN, DNSc</td></tr><tr><td colspan="2" class="item-abstract">Objective: The objectives of this study were to 1) identify the independent predictors of nosocomial bloodstream infections (NBSI) in the critically ill adult trauma population (CIATP); and 2) examine a theory that specifies the abstract dimensions of these predictors. Design: A prospective non-experimental cohort design was conducted over a 9-months period to collect data on a sample of 361 CIATP. Method: Crude univariate analysis was performed to identify the unadjusted predictors and significant interaction effects. A forward stepwise multivariate logistic regression analysis was then conducted to identify the independent predictors of NBSI. Second-order latent variable confirmatory factor analysis (CFA) was performed to identify the dimensions of the resulting independent predictors and examine the empirical validity of the resulting theoretical model. Findings: The crude univariate analysis suggested significant association between NBSI and more than 24 variables from 32 included in the analysis. However, multivariate logistic regression analysis showed that only nine variables were independent predictors of NBSI at an alpha of (0.05) and 95% confidence interval (CI); Chest tube, use of immunosuppressives, presence of microbial resistance, outcome length of stay, presence of pre-existing infections, percent change of albumin level , patient disposition, transfusion of 10 or more PRBC, and number of CVC catheters. The resulting regression model had a positive predictive value of (76.7%) and a negative predictive value of (93%). Second-order CFA showed that the nine independent predictors load into three higher level dimensions; therapy, microbial and circumstantial. Conclusions: NBSI in CIATP has nine predicting variables. These nine variables are theoretically categorized into three dimensions; therapeutic, microbial and circumstantial. Implications: The development and testing of a model to predict NBSI is expected to enhances future research efforts and assist clinicians identify early &ldquo;at risk&rdquo; patients, minimize associated risks, and provide directions for improvement of practice and treatment policies.</td></tr></table>en_GB
dc.date.available2011-10-26T09:58:48Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T09:58:48Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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