title: 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).
  
  
  METHODS
  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.affiliation: Epidemiology and Public Health Unit, Faculty of Medicine, University of Navarre, Irunlarrea s/n, 31008 Pamplona, Navarra, Spain. jdeirala@unav.es
authors.forename: J
authors.initials: J
authors.lastname: de Irala-Estévez
authors.forename: D
authors.initials: D
authors.lastname: Martínez-Concha
authors.forename: C
authors.initials: C
authors.lastname: Díaz-Molina
authors.forename: J
authors.initials: J
authors.lastname: Masa-Calles
authors.forename: A
authors.initials: A
authors.lastname: Serrano del Castillo
authors.forename: R
authors.initials: R
authors.lastname: Fernández-Crehuet Navajas
mesh_terms: D003428:Cross Infection / Q000517:prevention & control*; D005260:Female; D006801:Humans; D017053:Infection Control / Q000706:statistics & numerical data*; D007362:Intensive Care Units; D007902:Length of Stay; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment / Q000706:statistics & numerical data; D012307:Risk Factors; D013997:Time Factors