Comparison of different methodological approaches to identify risk factors of nosocomial infection in intensive care units

Abstract

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.