Validation of a bacteremia prediction model.
OBJECTIVE
To validate a previously published model for predicting bacteremia in hospitalized patients.


METHODS
Application of a published bacteremia prediction model to a prospective validation cohort of patients and comparison of its predictability to that found in the derivation cohort.


METHODS
Urban, university-affiliated, 550-bed public hospital.


METHODS
The validation cohort consisted of 342 patients with 559 blood culture episodes between October 14, 1992, and December 5, 1992. Each blood culture episode was scored based on the presence or absence of seven predictors of bacteremia and the findings compared with published results (derivation cohort).


METHODS
None.


RESULTS
Application of the bacteremia prediction model to the validation cohort identified episodes with a low risk (3%) and a high risk (17%) for true bacteremia, similar to the findings in the derivation cohort (1% and 16%, respectively). Comparison of the predictions of the model in the two cohorts by receiver operator characteristic curve analysis revealed that the overall predictability of the model in the validation cohort was not as good as in the derivation cohort.


CONCLUSIONS
Although the bacteremia prediction model did not perform as well overall in the validation cohort, the model still was able to clearly define two extreme groups: those with a low risk and those with a high risk for true bacteremia. This predictive capability may aid physicians in prescribing empiric antimicrobial therapy and also may be useful to hospital epidemiologists in assessing quality of care.
Mylotte
J M
JM
Department of Medicine, School of Medicine and Biomedical Sciences, State University of New York at Buffalo, USA.
Pisano
M A
MA
Ram
S
S
Nakasato
S
S
Rotella
D
D
D000293:Adolescent; D000328:Adult; D016470:Bacteremia / Q000175:diagnosis* / Q000453:epidemiology; D001769:Blood / Q000382:microbiology; D015331:Cohort Studies; D006746:Hospital Bed Capacity, 500 and over; D006766:Hospitals, County / Q000706:statistics & numerical data*; D006784:Hospitals, Teaching; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009518:New York / Q000453:epidemiology; D011446:Prospective Studies; D012372:ROC Curve; D015203:Reproducibility of Results; D012307:Risk Factors