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Risk Factors for Surgical Site Infection in Children

Published online by Cambridge University Press:  07 April 2017

Juan Francisco Casanova ,
Rafael Herruzo  and
Jesús Díez
Juan Francisco Casanova*
Affiliation:
Department of Preventive Medicine and Public Health, Autonomous University of Madrid, Madrid, Spain
Rafael Herruzo
Affiliation:
Department of Preventive Medicine and Public Health, Autonomous University of Madrid, Madrid, Spain Service of Preventive Medicine, La Paz Hospital, Madrid, Spain
Jesús Díez
Affiliation:
Department of Preventive Medicine and Public Health, Autonomous University of Madrid, Madrid, Spain Service of Preventive Medicine, La Paz Hospital, Madrid, Spain
*
Departmento de Medicina Preventiva y Salud Pública, Facultad de Medicina., Universidad Autónoma de Madrid, C/. Arzobispo Morcillo, 4, 28029-Madrid, Spain ([email protected])
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Abstract

Objectives.

To assess the appropriateness of using the indices developed by the Study on the Efficacy of Nosocomial Infection Control (SENIC) and the National Nosocomial Infections Surveillance (NNIS) project to determine risk factors for surgical site infection (SSI) in children and, if not appropriate, to explore the factors related to SSI in children so these factors could be used in a risk index for pediatric patients.

Design.

Cohort study during more than 4 years.

Setting.

La Paz University Hospital, a national reference center that serves Health Area 5 of Madrid, Spain, which has approximately 500,000 inhabitants.

Patients.

Convenience sample consisting of the 3,646 children admitted for surgery who had a postsurgical stay of more than 2 days.

Results.

A model with 8 predictive factors (degree of surgical contamination; duration of surgery; type of surgery; use of a peripheral venous catheter, central venous catheter, or urinary catheter; number of diagnoses; and SSI exposition time) was created. Its relation to the SSI rate was better than that of the SENIC or NNIS indices. Its sensitivity, specificity, and area under the receiver–operating characteristic curve were higher than that of the SENIC index.

Conclusions.

The model that we created seems to be more adequate for predicting SSI and evaluating pediatric patients' intrinsic risk than the SENIC and NNIS indices.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 27 , Issue 7 , July 2006 , pp. 709 - 715
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

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References

1.Dellinger, EP, Ehrenkranz, NJ. Surgical infections. In: Bennet, JV, Brach-man, PS, eds. Hospital Infections. 5th ed. Philadelphia, PA: Lippincott Williams & Wilkins; 1998:685–710.Google Scholar
2.Berard, F, Gandon, J. Postoperative wound infections: the influence of ultraviolet irradiation of the operating room and of various other factors. Ann Surg 1964; 160:1–192.Google Scholar
3.Simmons, BP. Guideline for prevention of surgical wound infections. Am J Infect Control 1983; 11:133–143.Google Scholar
4.Garner, JS. CDC guideline for prevention of surgical wound infections, 1985. Infect Control 1986; 7:193–200.Google Scholar
5.Cruse, PJ, Foord, R. The epidemiology of wound infection: a 10-year prospective study of 62,939 wounds. Surg Clin North Am 1980; 60:27–40.Google Scholar
6.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; 121:206–215.Google Scholar
7.Culver, DH, Horan, TC, Gaynes, RP, et al. Surgical wound infection rates by wound class, operative procedure, and patient risk index: National Nosocomial Infections Surveillance System. Am J Med 1991; 91:152S–157S.CrossRefGoogle ScholarPubMed
8.Horan, TC, Emori, TG. Definitions of key terms used in the NNIS system. Am J Infect Control 1997; 25:112–116.Google Scholar
9.Horan, TC, Gaynes, RP, Culver, D, et al. Development of predictive risk factors for nosocomial surgical site infections (SSIs) [abstract]. Infect Control Hosp Epidemiol 1994; 15:46.Google Scholar
10.Centers for Disease Control and Prevention. National Nosocomial Infections Surveillance (NNIS) report, data summary from October 1986–April 1997, issued May 1997. Am J Infect Control 1997; 25:477–487.Google Scholar
11.New classification of physical status. Anesthesiology 1963; 24:1–111.Google Scholar
12.Owens, WD. ASA physical status classification: a study on consistency of ratings. Anesthesiology 1978; 49:239–243.Google Scholar
13.Campins, M, Vaque, J, Rossello, J, et al; EPINE Working Group. Nosocomial infections in pediatric patients: a prevalence study in Spanish hospitals. Am J Infect Control 1993; 21:58–63.Google Scholar
14.Delgado-Rodríguez, M, Sillero-Arenas, M, Medina-Cuadros, M, Martínez-Gallego, G. Nosocomial infections in surgical patients: comparison of two measures of intrinsic patient risk. Infect Control Hosp Epidemiol 1997; 18:19–23.Google Scholar
15.Delgado-Rodríguez, M, Medina-Cuadros, M, Martínez-Gallego, G, Sillero-Arenas, M. Usefulness of intrinsic surgical wound infection risk indices as predictors of postoperative pneumonia risk. J Hosp Infect 1997; 35:269–276.Google Scholar
16.Valls, V, Díez, M, Ena, J, et al. Evaluation of the SENIC risk index in a Spanish university hospital. Infect Control Hosp Epidemiol 1999; 20:196–199.Google Scholar
17.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; 13:606–608.Google Scholar
18.Comisión Clínica de Infecciones y Política Antibiótica. Guía Para la Prevención y el Control de la Infección Hospitalaria. Madrid, Spain: Hospital Universitario La Paz; 1998.Google Scholar
19.Hosmer, DW Jr, Lemeshow, S. Applied Logistic Regression. New York, NY: Wiley; 1989.Google Scholar
20.Casanova Domingo, JF. Metodología estadística: análisis multivariante: métodos confirmatorios II. Pediátrika 1999; 19:189–202.Google Scholar
21.Hanley, JA, McNeil, BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982; 143:29–36.Google Scholar
22.Hanley, JA, McNeil, BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983; 148:839–843.Google Scholar
23.Zweig, MH, Campbell, G. Receiver operator characteristic (ROC) plots; a fundamental evaluation tool in clinical medicine. Clin Chem 1993; 39:561–577.Google Scholar