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2005 Volume 17 >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/2285

Title: Logistic Regression in Modelling Data for CVC - Related Infection
Authors: Prodanova, Krasimira
Stoinov, Ionko
Terziiski, Dimitar
Keywords: Central Venious Catheter (CVC) infection
multinomial logistic regression
Issue Date: 2005
Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Citation: Pliska Studia Mathematica Bulgarica, Vol. 17, No 1, (2005), 221p-228p
Abstract: A prospective study of all new central venous catheters (CVC) inserted for patients in intensive care unit in order to identify risk factors for CVC infection and to determine the rate of CVC related infection is undertaken. A catheter-related infection and sepsis was suspected in 62 cases of 118 CVC inserted in intensive care patients. A multiple logistic regression to obtain adjusted estimate of odds ratios and to identify which factors were associated independently with CVC related infection was performed. The variables which entered in the model were those found to be statistically significant on univariate analysis and those which were established risk factors from previous research reports. The dependent variable was the CVC related infection. The independent variables were ten: age, sex, insertion site, number of lumens, duration of catheterization etc. The software package STATISTICA 6.0 was used for analyzing the real data.
Description: 2000 Mathematics Subject Classification: 62J12, 62P10.
URI: http://hdl.handle.net/10525/2285
ISSN: 0204-9805
Appears in Collections:2005 Volume 17

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