OBJECTIVE: Comparison of statistical methods and measurement scales to identify nosocomial infection risk factors in intensive care units (ICU). DESIGN: Prospective study in 558 patients admitted to the ICU of a referral hospital between February and November 1994. METHODS: Analysis using three logistic regression models, three standard Cox regression models, and two Cox regression models with time-dependent extrinsic factors. Different scales were used to measure exposures to risk factors (dichotomous, ordinal, quantitative, and time-dependent variables). RESULTS: The most appropriate models were those that measured exposure using dichotomous variables. Models using ordinal or quantitative variables estimated biased coefficients and/or failed to comply with the statistical assumptions underlying the analyses. The Cox regression model with quantitative time-dependent variables met all the statistical assumptions, obtained a precise assessment of risk by exposure time, and estimated unbiased coefficients. CONCLUSIONS: The Cox regression analysis with quantitative time-dependent variables is the most valid alternative for assessing the risk of nosocomial infection per day of exposure to an extrinsic risk factor in the ICU.
OBJECTIVE: Comparison of statistical methods and measurement scales to identify nosocomial infection risk factors in intensive care units (ICU). DESIGN: Prospective study in 558 patients admitted to the ICU of a referral hospital between February and November 1994. METHODS: Analysis using three logistic regression models, three standard Cox regression models, and two Cox regression models with time-dependent extrinsic factors. Different scales were used to measure exposures to risk factors (dichotomous, ordinal, quantitative, and time-dependent variables). RESULTS: The most appropriate models were those that measured exposure using dichotomous variables. Models using ordinal or quantitative variables estimated biased coefficients and/or failed to comply with the statistical assumptions underlying the analyses. The Cox regression model with quantitative time-dependent variables met all the statistical assumptions, obtained a precise assessment of risk by exposure time, and estimated unbiased coefficients. CONCLUSIONS: The Cox regression analysis with quantitative time-dependent variables is the most valid alternative for assessing the risk of nosocomial infection per day of exposure to an extrinsic risk factor in the ICU.
Authors: Chaker Ben Hamida; Jean-Yves Lauzet; Saida Rézaiguia-Delclaux; Christophe Duvoux; Daniel Cherqui; Philippe Duvaldestin; François Stéphan Journal: Intensive Care Med Date: 2003-04-03 Impact factor: 17.440
Authors: Alexander M Aiken; Neema Mturi; Patricia Njuguna; Shebe Mohammed; James A Berkley; Isaiah Mwangi; Salim Mwarumba; Barnes S Kitsao; Brett S Lowe; Susan C Morpeth; Andrew J Hall; Iqbal Khandawalla; J Anthony G Scott Journal: Lancet Date: 2011-11-29 Impact factor: 79.321