251. Predicting Bacteremia among Patients Hospitalized for Skin and Skin-Structure Infections: Derivation and Validation of a Risk Score
- Author
-
Benjamin A. Lipsky, Ying P. Tabak, Loren G. Miller, Richard S. Johannes, Xiaowu Sun, and Marin H. Kollef
- Subjects
Male ,Microbiology (medical) ,medicine.medical_specialty ,Respiratory rate ,Epidemiology ,Bacteremia ,Models, Biological ,Predictive Value of Tests ,Risk Factors ,White blood cell ,Internal medicine ,medicine ,Humans ,Risk factor ,Gram-Positive Bacterial Infections ,Aged ,Framingham Risk Score ,business.industry ,Skin Diseases, Bacterial ,Middle Aged ,Stepwise regression ,medicine.disease ,Surgery ,Community-Acquired Infections ,Gram-Positive Cocci ,Hospitalization ,Logistic Models ,Infectious Diseases ,medicine.anatomical_structure ,Cohort ,Female ,business - Abstract
Objective.Bacteremia is relatively common in patients with skin and skin-structure infection (SSSI) severe enough to require hospitalization. We used selected demographic and clinical characteristics easily assessable at initial evaluation to develop a model for the early identification of patients with SSSI who are at higher risk for bacteremia.Participants.A large database of adults hospitalized with SSSI at 97 hospitals in the United States during the period from 2003 through 2007 and from whom blood samples were obtained for culture at admission.Methods.We compared selected candidate predictor variables for patients shown to have bacteremia and patients with no demonstrated bacteremia. Using stepwise logistic regression to identify independent risk factors for bacteremia, we derived a model by using 75% of a randomly split cohort, converted the model coefficients into a risk score system, and then we validated it by using the remaining 25% of the cohort.Results.Bacteremia was documented in 1,021 (11.7%) of the 8,747 eligible patients. Independent predictors of bacteremia (PP< .001). The model C statistic was 0.71; the Hosmer-Lemeshow testPvalue was .36, indicating excellent model calibration.Conclusions.Using data available at hospital admission, we developed a risk score that differentiated SSSI patients at low risk for bacteremia from patients at high risk. This score may help clinicians identify patients who require more intensive monitoring or antimicrobial regimens appropriate for treating bacteremia.
- Published
- 2010