• Critical care medicine · May 1996

    Risk factors for nosocomial infection in critically ill children: a prospective cohort study.

    • N Singh-Naz, B M Sprague, K M Patel, and M M Pollack.
    • Department of Pediatrics, George Washington University School of Medicine, Washington, DC, USA.
    • Crit. Care Med. 1996 May 1;24(5):875-8.

    ObjectiveTo identify factors in pediatric intensive care unit (ICU) patients that are associated with an increased risk of nosocomial infections.DesignA prospective, 1-yr cohort study.SettingA 16-bed pediatric ICU in a multidisciplinary, regional referral center.SubjectsAll patients admitted to the pediatric ICU.InterventionsNone.Measurements And Main ResultsThe primary outcome variable was the development of nosocomial infection. Out of 945 consecutive admissions, 75 patients developed 96 nosocomial infections. The most frequent infection sites were the lower respiratory tract (35%), the bloodstream (21%), and the urinary tract (21%). The most common organisms isolated were Gram-negative bacteria (53%, Gram-positive bacteria (27%), and fungi (9%). Variables significantly associated with the development of nosocomial infections included age, weight, Pediatric Risk of Mortality (PRISM) score, device utilization ratio, antimicrobial therapy, histamine-2 (H2) receptor blocker use, immune status, parenteral nutrition, and length of stay. When combined in a multivariate logistic regression model, the significant variables were operative status, PRISM score, device utilization ratio, antimicrobial therapy, parenteral nutrition, and length of stay before the onset of infection. The area under the receiver operating characteristic curve was 0.868. At a probability of 0.15, the sensitivity was 66.67%, and the specificity was 87.82%.ConclusionsPatients at risk for developing nosocomial infection can be identified using a multivariate logistic regression model with a high degree of sensitivity and specificity. These data indicate that institutional nosocomial rates need to be adjusted for risk factors. This model could help target patients at high risk for developing nosocomial infections for preventive strategies.

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