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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*
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, (emmanuelle.girou@hmn.aphp.fr)

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
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

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References

1. Haley, RW, Schaberg, DR, Crossley, KB, Von Allmen, SD, McGowan, JE. Extra charges and prolongation of stay attributable to nosocomial infections: a prospective interhospital comparison. Am J Med 1981; 70:5158.Google Scholar
2. Knopf, HJ, Weib, P, Schafer, W, Funke, PJ. Nosocomial infections after transurethral prostatectomy. Eur Urol 1999; 36:207212.Google Scholar
3. Mebust, WK, Holtgrewe, HL, Cockett, AT, Peters, PC. Transurethral prostatectomy: immediate and postoperative complications. A cooperative study of 13 participating institutions evaluating 3,885 patients. J Urol 1989; 141:243247.Google Scholar
4. Horninger, W, Unterlechner, H, Strasser, H, Bartsch, G. Transurethral prostatectomy: mortality and morbidity. Prostate 1996; 28:195200.3.0.CO;2-E>CrossRefGoogle ScholarPubMed
5. Ibrahim, AI, Bilal, NE, Shetty, SD, Patil, KP, Gommaa, H. The source of organisms in the post-prostatectomy bacteriuria of patients with preoperative sterile urine. Br J Urol 1993; 72:770774.Google Scholar
6. Vivien, A, Lazard, T, Rauss, A, Laisne, MJ, Bonnet, F. Infection after transurethral resection of the prostate: variation among centers and correlation with long-lasting procedure. Eur Urol 1998; 33:365369.CrossRefGoogle Scholar
7. Slavis, SA, Miller, JB, Golgi, H, Dunshee, CJ. Comparison of single-dose antibiotic prophylaxis in uncomplicated transurethral resection of the prostate. J Urol 1992; 147:13031306.Google Scholar
8. Hargreave, TB, Botto, H, Rikken, GH, et al. European collaborative study of antibiotic prophylaxis for transurethral resection of the prostate. Eur Urol 1993; 23:437443.Google Scholar
9. Colau, A, Lucet, JC, Rufat, P, Botto, H, Benoit, G, Jardin, A. Incidence and risk factors of bacteriuria after transurethral resection of the prostate. Eur Urol 2001; 39:272276.Google Scholar
10. Keats, AS. The ASA classification of physical status—a recapitulation. Anesthesiology 1978; 49:233236.CrossRefGoogle ScholarPubMed
11. Altemeier, WA, Burke, JF, Pruitt, BJ, Sandosky, WR. Definition and classification of surgical infection. In: Altemeier, WA, ed. Manual on Control of Infection in Surgical Patients. Philadelphia: Lippincott; 1984:2930.Google Scholar
12. Culver, DH, Horan, TC, Gaynes, RP, et al. Surgical wound infection rates by wound class, operative procedure, and patient risk index. Am J Med 1991; 91:152S157S.CrossRefGoogle ScholarPubMed
13. Horan, TC, Gaynes, RP, Martone, WJ, Jarvis, WR, Emori, TG. CDC definitions of nosocomial surgical site infections, 1992: a modification of CDC definitions of surgical wound infections. Infect Control Hosp Epidemiol 1992; 13:606608.CrossRefGoogle ScholarPubMed
14. Hanley, JA, McNeil, BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982; 143:2936.CrossRefGoogle Scholar
15. Lemeshow, S, Hosmer, DW Jr. A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 1982; 115:92106.Google Scholar
16. Grabe, M, Forsgren, A, Hellsten, S. Species distribution and antibiotic sensitivity of bacteria isolated pre- and postoperatively from patients undergoing transurethral prostatic resection. Scand J Urol Nephrol 1984; 18:187192.Google Scholar
17. Naber, KG, Bauernfeind, A, Diellein, G, Wittenberger, R, Neu, HC, Williams, JD. Urinary tract infection in elderly urological patients. In: Neu, HC, ed. New trends in Urinary Tract Infections. Basel: Karger; 1988:4861.Google Scholar
18. Berry, A, Barratt, A. Prophylactic antibiotic use in transurethral prostatic resection: a meta-analysis. J Urol 2002; 167:571577.Google Scholar
19. Qiang, W, Jianchen, W, MacDonald, R, Monga, M, Wilt, TJ. Antibiotic prophylaxis for transurethral prostatic resection in men with preoperative urine containing less than 100,000 bacteria per mL: a systematic review. J Urol 2005; 173:11751181.Google Scholar
20. Liu, GG, Nguyen, T, Nichol, MB. An economic analysis of antimicrobial prophylaxis against urinary tract infection in patients undergoing transurethral resection of the prostate. Clin Ther 1999; 21:15891604.Google Scholar
21. Bouza, E, San Juan, R, Munoz, P, Voss, A, Kluytmans, J. A European perspective on nosocomial urinary tract infections II. Report on incidence, clinical characteristics and outcome (ESGNI-004 study). European Study Group on Nosocomial Infection. Clin Microbiol Infect 2001; 7:532542.Google Scholar
22. National Nosocomial Infections Surveillance System. National Nosocomial Infections Surveillance (NNIS) System Report, data summary from January 1992 through June 2004, issued October 2004. Am J Infect Control 2004; 32:470485.CrossRefGoogle Scholar
23. Goldwasser, B, Bogokowsky, B, Nativ, O, Sidi, AA, Jonas, P, Many, M. Urinary infections following transurethral resection of bladder tumors—rate and source. J Urol 1983; 129:11231124.Google Scholar
24. Taylor, EW, Lindsay, G. Antibiotic prophylaxis in transurethral resection of the prostate with reference to the influence of preoperative catheterization. J Hosp Infect 1988; 12:7583.Google Scholar
25. Viitanen, J, Talja, M, Jussila, E, et al. Randomized controlled study of chemoprophylaxis in transurethral prostatectomy. J Urol 1993; 150:17151717.Google Scholar
26. National Nosocomial Infections Surveillance (NNIS) System. National Nosocomial Infections Surveillance (NNIS) System report: data summary from January 1992—April 2000, issued June 2000. Am J Infect Control 2000; 28:429448.Google Scholar
27. Brandt, C, Hansen, S, Sohr, D, Daschner, F, Ruden, H, Gastmeier, P. Finding a method for optimizing risk adjustment when comparing surgical-site infection rates. Infect Control Hosp Epidemiol 2004; 25:313318.Google Scholar
28. Geubbels, EL, Mintjes-de Groot, AJ, van den Berg, JM, de Boer, AS. An operating surveillance system of surgical site infections in The Netherlands: results of the PREZIES national surveillance network. Preventie van Ziekenhuisinfecties door Surveillance. Infect Control Hosp Epidemiol 2000; 21:311318.CrossRefGoogle Scholar