Skip to main content Accessibility help

Suitability of the NNIS Index for Estimating Surgical-Site Infection Risk at a Small University Hospital in Brazil

  • Maria Léa Campos (a1), Zulmira Miotello Cipriano (a1) and Paulo Fontoura Freitas (a2)



To detect the occurrence of surgical-site infection (SSI) in our study sample, using the traditional variables of the National Nosocomial Infection Surveillance (NNIS) index with a locally modified cut-off point for the “T time” defining length of surgical procedure; to compare the modified and the traditional NNIS index under the hypothesis that a cut-off point discriminating procedures of short and long duration, based upon the actual experience of the study sample, can adequately predict the risk of SSI.


A retrospective chart review of 9,322 patients undergoing surgical procedures in the period January 1993 to December 1998.


A small university hospital (UH) in southern Brazil.


The composite index using the local sample procedure-duration cut-off point (UH-index) performed better than any of the individual components of the composite index (anesthesia risk index and surgical-wound class [SWC]). The UH-index also predicted adequately the risk of SSI when compared to the traditional NNIS index, particularly when stratifying by SWC.


A modified NNIS index, using the sample cut-off point, can adequately predict the risk of SSI in a given population. Further studies are needed to compare and validate the NNIS index of risk for populations other than those of the NNIS-participating hospitals. Larger samples using different hospitals with similar characteristics are needed to investigate the risk of SSI associated with specific operations.


Corresponding author

Rua Rui Barbosa, 135, 401, CEP 88025-300, Florianópolis, Santa Catarina, Brazil


Hide All
1.Emori, TG, Gaynes, RP. An overview of nosocomial infections, including the role of the microbiology laboratory. Clin Microbiol Rev 1993;6:428442.
2.Haley, RW, Culver, DH, Morgan, WM, White, JW, Emori, TG, Hooton, TM. Identifying patients at high risk of surgical wound infection: a simple multivariate index of patient susceptibility and wound contamination. Am J Epidemiol 1985;121:206215.
3.Consensus paper on the surveillance of surgical wound infections. The Society for Hospital Epidemiology of America, the Association for Practitioners in Infection Control, the Centers for Disease Control, the Surgical Infection Society. Infect Control Hosp Epidemiol 1992;13:599605.
4.Culver, DH, Horan, TC, Gaynes, RP, Martone, WJ, Jarvis, WR, Emori, TG, et al. Surgical wound infection rates by wound class, operative procedure, and patient risk index. National Nosocomial Infections Surveillance System. Am J Med 1991;91(suppl 3B):152S157S.
5.Roy, MC, Perl, TM. Basics of surgical site infection surveillance. In: Herwaldt, LA, ed. A Practical Handbook for Hospital Epidemiologists. Thorofare, NJ: SLACK Inc; 1998:99114.
6.Starling, CEF, Couto, BRGM, Pinheiro, SMC. Applying the Centers for Disease Control and Prevention and National Nosocomial Surveillance system methods in Brazilian Hospitals. Am J Infect Control 1997;25:303311.
7.Velasco, E, Thuler, LCS, de Souza Martins, CA, de Castro Dias, LM, Gonçalves, VM. Risk index for prediction of surgical site infection after oncology operations. Am J Infect Control 1998;26:217223.
8.Ministry of Health, Brazil. Vigilância Epidemiológica por componentes NNISS (Epidemiological Surveillance by NNISS components). Trad. Solange de Lima Torres, Valéria Rumjanek e Fabiola de Aguiar Nunes. Brasília; 1994.
9.Starling, CEF, Pinto, CAG, Couto, BRMG, Pinheiro, SMC. Sistema de vigilância epidemiológica de infecções hospitalares por componentes. Metodologia NNISS aplicada a hospitais brasileiros. 2 ed, Belo Horizonte: [s.e]; 1992.
10.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.
11.American Society of Anesthesiologists. New classification of physical status. Anesthesiology 1963;24:111.
12.Owens, WD, Felts, JA, Spitznagel, EL JrASA physical status classification: a study of consistency of ratings. Anesthesiology 1978;49:239243.
13.Keats, AS. The ASA classification of physical status—a recapitulation. Anesthesiology 1978;49:233236.
14.Mangram, AJ, Horan, TC, Pearson, ML, Silver, LC, Jarvis, WR, the Hospital Infection Control Practices Advisory Committee. Guideline for the prevention of surgical site infection, 1999. Infect Control Hosp Epidemiol 1999;20:247280.
15.Goodman, LA, Kruskal, WH. Measures of association for cross classifications. American Statistical Association Journal 1954;49:732764.
16.Wasser, TE. A software to calculate Goodman and Kruskal's Gamma: a method to monitor surgical-site infection rates. Infect Control Hosp Epidemiol 1998;19:869871.
17.Kirkwood, B. Essentials of Medical Statistics. Oxford, UK: Blackwell Scientific Publications; 1998:138.


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed