Literature DB >> 31218977

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

Rebecca Grant1, Martine Aupee2, Nicolas C Buchs3, Kristine Cooper4, Marie-Christine Eisenring5, Theresa Lamagni4, Frédéric Ris3, Juliette Tanguy2, Nicolas Troillet5, Stephan Harbarth1, Mohamed Abbas1.   

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.

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Mesh:

Year:  2019        PMID: 31218977     DOI: 10.1017/ice.2019.163

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN: 0899-823X            Impact factor:   3.254


  3 in total

1.  Changes in the gut bacterial communities in colon cancer surgery patients: an observational study.

Authors:  Mohamed Abbas; Nadia Gaïa; Nicolas C Buchs; Vaihere Delaune; Myriam Girard; Diego O Andrey; Jeremy Meyer; Jacques Schrenzel; Frédéric Ris; Stephan Harbarth; Vladimir Lazarevic
Journal:  Gut Pathog       Date:  2022-01-04       Impact factor: 4.181

2.  Artificial Intelligence-Based Multimodal Risk Assessment Model for Surgical Site Infection (AMRAMS): Development and Validation Study.

Authors:  Weijia Chen; Zhijun Lu; Lijue You; Lingling Zhou; Jie Xu; Ken Chen
Journal:  JMIR Med Inform       Date:  2020-06-15

3.  Reliability and validity of multicentre surveillance of surgical site infections after colorectal surgery.

Authors:  Janneke D M Verberk; Stephanie M van Rooden; David J Hetem; Herman F Wunderink; Anne L M Vlek; Corianne Meijer; Eva A H van Ravensbergen; Elisabeth G W Huijskens; Saara J Vainio; Marc J M Bonten; Maaike S M van Mourik
Journal:  Antimicrob Resist Infect Control       Date:  2022-01-21       Impact factor: 4.887

  3 in total

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