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

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.

Nosocomial infection in an intensive-care unit: identification of risk factors.

OBJECTIVE: To identify risk factors predictive of nosocomial infection in an intensive-care unit (ICU) and to identify patients with a higher risk of nosocomial infection using a predictive model of nosocomial infection in our ICU. DESIGN: Prospective study; daily concurrent surveillance of intensive-care-unit patients. SETTING/PATIENTS: All patients admitted for at least 24 hours to the ICU of a tertiary-level hospital from February to November 1994 were followed daily. METHODS: Variables measuring extrinsic and intrinsic risk factors for nosocomial infection were collected on each patient during their ICU stay, and the Cox Proportional Hazards multivariable technique was used to identify the variables significantly associated with infection. RESULTS: The population studied consisted of 944 patients. The main risk factors identified were intrinsic; the significant extrinsic risk factors identified were head of the bed in a horizontal (< 30 degrees) position (this variable presented the highest increase of the infection hazard ratio) and the use of sedative medication. Patients presenting the highest risk scores using the predictive model are those with the highest risk of nosocomial infection. CONCLUSIONS: The important preventive measures derived from our results are that underlying conditions suffered by the patient at the ICU admission should be corrected promptly, the depression of the patient's level of consciousness with sedatives should be monitored carefully, and the horizontal position of the head of the bed should be avoided totally. Patients with a high risk of infection can be the target of special preventive measures.