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Performance of surgical site infection risk prediction models in colorectal surgery: external validity assessment from three European national surveillance networks

Published online by Cambridge University Press:  20 June 2019

Rebecca Grant
Affiliation:
Infection Control Programme, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland Centre for Global Health, Institut Pasteur, Paris, France
Martine Aupee
Affiliation:
Coordination Center for Prevention and Control of Nosocomial Infections (CClin) Ouest, Rennes, France
Nicolas C. Buchs
Affiliation:
Service of Visceral Surgery, Department of Surgery, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland
Kristine Cooper
Affiliation:
National Infection Service, Public Health England, London, United Kingdom
Marie-Christine Eisenring
Affiliation:
Swissnoso, National Center for Infection Prevention, Bern, Switzerland Service of Infectious Diseases, Central Institute of the Valais Hospital, Sion, Switzerland
Theresa Lamagni
Affiliation:
National Infection Service, Public Health England, London, United Kingdom
Frédéric Ris
Affiliation:
Service of Visceral Surgery, Department of Surgery, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland
Juliette Tanguy
Affiliation:
Coordination Center for Prevention and Control of Nosocomial Infections (CClin) Ouest, Rennes, France
Nicolas Troillet
Affiliation:
Swissnoso, National Center for Infection Prevention, Bern, Switzerland Service of Infectious Diseases, Central Institute of the Valais Hospital, Sion, Switzerland
Stephan Harbarth
Affiliation:
Infection Control Programme, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland Swissnoso, National Center for Infection Prevention, Bern, Switzerland
Mohamed Abbas
Affiliation:
Infection Control Programme, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland
Corresponding
E-mail address:

Abstract

Objective:

To assess the validity of multivariable models for predicting risk of surgical site infection (SSI) after colorectal surgery based on routinely collected data in national surveillance networks.

Design:

Retrospective analysis performed on 3 validation cohorts.

Patients:

Colorectal surgery patients in Switzerland, France, and England, 2007–2017.

Methods:

We determined calibration and discrimination (ie, area under the curve, AUC) of the COLA (contamination class, obesity, laparoscopy, American Society of Anesthesiologists [ASA]) multivariable risk model and the National Healthcare Safety Network (NHSN) multivariable risk model in each cohort. A new score was constructed based on multivariable analysis of the Swiss cohort following colorectal surgery, then based on colon and rectal surgery separately.

Results:

We included 40,813 patients who had undergone elective or emergency colorectal surgery to validate the COLA score, 45,216 patients to validate the NHSN colon and rectal surgery risk models, and 46,320 patients in the construction of a new predictive model. The COLA score’s predictive ability was poor, with AUC values of 0.64 (95% confidence interval [CI], 0.63–0.65), 0.62 (95% CI, 0.58–0.67), 0.60 (95% CI, 0.58–0.61) in the Swiss, French, and English cohorts, respectively. The NHSN colon-specific model (AUC, 0.61; 95% CI, 0.61–0.62) and the rectal surgery–specific model (AUC, 0.57; 95% CI, 0.53–0.61) showed limited predictive ability. The new predictive score showed poor predictive accuracy for colorectal surgery overall (AUC, 0.65; 95% CI, 0.64–0.66), for colon surgery (AUC, 0.65; 95% CI, 0.65–0.66), and for rectal surgery (AUC, 0.63; 95% CI, 0.60–0.66).

Conclusion:

Models based on routinely collected data in SSI surveillance networks poorly predict individual risk of SSI following colorectal surgery. Further models that include other more predictive variables could be developed and validated.

Type
Original Article
Copyright
© 2019 by The Society for Healthcare Epidemiology of America. All rights reserved. 

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Footnotes

PREVIOUS PRESENTATION: Preliminary results of this study were presented (oral presentation no. O1177) at the 29th European Conference on Clinical Microbiology and Infectious Diseases on April 16, 2019, in Amsterdam, The Netherlands.

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