A Pérez-García1, M F Landecho2, J J Beunza3, D Conde-Estévez4, J P Horcajada5, S Grau4, A Gea6, E Mauleón7, L Sorli5, J Gómez8, R Terradas9, J F Lucena2, F Alegre2, A Huerta2, J L Del Pozo10. 1. Department of Clinical Microbiology, Clínica Universidad de Navarra, Pamplona, Spain. 2. Internal Medicine, Division of Intermediate Care and Hospitalists Unit, Clinica Universidad de Navarra, Pamplona, Spain. 3. Interdusciplinar Education, Universidad Europea, Pamplona, Spain. 4. Service of Pharmacy, Hospital Universitari del Mar, Barcelona, Spain. 5. Service of Infectious diseases, Hospital Universitari del Mar, Institut Hospital del Mar d'Investigacions Médiques, CEXS-Universitat Pompeu Fabra, CIBERES, Barcelona, Spain. 6. Department of Preventive Medicine and Public Health, Universidad de Navarra, Pamplona, Spain. 7. Internal Medicine, Clínica Universidad de Navarra, Pamplona, Spain. 8. Depatament of Microbiology, Laboratori de Referencia de Catalunya, Barcelona, Spain. 9. Service of Evaluation and Clinical Epidemiology, Hospital Universitari del Mar, Barcelona, Spain. 10. Division of Infectious diseases, Department Clinical Microbiology, Clínica Universidad de Navarra, Pamplona, Spain.
Abstract
BACKGROUND: To develop a prediction rule to describe the risk of death as a result of enterococcal bloodstream infection. METHODS: A prediction rule was developed by analysing data collected from 122 patients diagnosed with enterococcal BSI admitted to the Clínica Universidad de Navarra (Pamplona, Spain); and validated by confirming its accuracy with the data of an external population (Hospital del Mar, Barcelona). RESULTS: According to this model, independent significant predictors for the risk of death were being diabetic, have received appropriate treatment, severe prognosis of the underlying diseases, have renal failure, received solid organ transplant, malignancy, source of the bloodstream infection and be immunosuppressed. The prediction rule showed a very good calibration (Hosmer-Lemeshow statistic, P = 0.93) and discrimination for both training and testing sets (area under ROC curve = 0.84 and 0.83 respectively). CONCLUSIONS: The predictive rule was able to predict risk of death as a result of enterococcal bloodstream infection as well as to identify patients, who being below the threshold value, will have a low risk of death with a negative predictive value of 96%.
BACKGROUND: To develop a prediction rule to describe the risk of death as a result of enterococcal bloodstream infection. METHODS: A prediction rule was developed by analysing data collected from 122 patients diagnosed with enterococcal BSI admitted to the Clínica Universidad de Navarra (Pamplona, Spain); and validated by confirming its accuracy with the data of an external population (Hospital del Mar, Barcelona). RESULTS: According to this model, independent significant predictors for the risk of death were being diabetic, have received appropriate treatment, severe prognosis of the underlying diseases, have renal failure, received solid organ transplant, malignancy, source of the bloodstream infection and be immunosuppressed. The prediction rule showed a very good calibration (Hosmer-Lemeshow statistic, P = 0.93) and discrimination for both training and testing sets (area under ROC curve = 0.84 and 0.83 respectively). CONCLUSIONS: The predictive rule was able to predict risk of death as a result of enterococcal bloodstream infection as well as to identify patients, who being below the threshold value, will have a low risk of death with a negative predictive value of 96%.