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

Infect Control Hosp Epidemiol. 1997 Dec;18(12):825-30.

Abstract

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.

MeSH terms

  • APACHE
  • Cross Infection / epidemiology*
  • Cross Infection / etiology
  • Cross Infection / prevention & control
  • Female
  • Humans
  • Incidence
  • Intensive Care Units / statistics & numerical data*
  • Length of Stay
  • Male
  • Models, Statistical
  • Prospective Studies
  • Risk Factors
  • Spain