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The Postoperative Bacteriuria Score A New Way to Predict Nosocomial Infection After Prostate Surgery

Published online by Cambridge University Press:  21 June 2016

E. Girou ,
C. Rioux ,
C. Brun-Buisson  and
B. Lobel
E. Girou*
Affiliation:
Infection Control Unit, Créteil Henri Mondor Hospital, Assistance Public–Hôpitaux de Paris, Paris 12 University, Créteil Centre de Ressources en Biostatistique, Epidémiologic et Pharmaco-Epidémiologie appliquées aux Maladies Infectieuses, Institut Pasteur, and U657, INSERM, Paris
C. Rioux
Affiliation:
Infection Control Unit, Créteil
C. Brun-Buisson
Affiliation:
Medical Intensive Care Unit, Créteil Henri Mondor Hospital, Assistance Public–Hôpitaux de Paris, Paris 12 University, Créteil
B. Lobel
Affiliation:
Urology Ward, Pontchaillou Hospital, Rennes, France
*
Unité de Contrôle, Epidémiologie et Prévention de l'lnfection (CEPI), Hôpital Henri Mondor, 51 avenue du Mai de Lattre de Tassigny, 94010 Créteil, France, ([email protected])
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Abstract

Objective.

Urinary tract infections are the leading nosocomial urologic infections and may be a cause of added morbidity and costs, and sometimes sepsis. The aim of this study was to design a predictive score for these complications after prostate surgery.

Design.

Multicenter prospective survey.

Setting.

Eleven French urology centers.

Patients.

All patients undergoing transurethral resection of prostate (TURP) during a 3-month period.

Results.

The overall incidence of postoperative bacteriuria was 25.0% (95% confidence interval, 17.7%-29.5%). Almost all patients (95.7%) received antibiotic prophylaxis. A predictive postoperative bacteriuria score (POBS), with a 6-point scale of 0 to 5, was constructed on the basis of independent risk factors identified in multivariate analysis of a test sample of patients (n = 135) and tested in a validation sample (n = 73). Significantly more infections occurred in patients with a POBS of 2 or higher (87 [8%] vs 48 [50%]; P<.0001). With the test sample, this yielded a sensitivity of 77%, a specificity of 77%, a positive predictive value of 50%, a negative predictive value of 92%, and a global accuracy of 77%.

Conclusions.

POBS could be used to distinguish patients at risk of developing infection after TURP. This information might be useful for implementing selective prevention measures or for adjustment for differences in nosocomial infection rates when comparing data between urology centers.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 27 , Issue 8 , August 2006 , pp. 847 - 854
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

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