Surbhi Leekha1, Brian D Lahr2, Rodney L Thompson3, Priya Sampathkumar3, Audra A Duncan4, Robert Orenstein5. 1. Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Md. Electronic address: sleekha@epi.umaryland.edu. 2. Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minn. 3. Division of Infectious Diseases, Mayo Clinic, Rochester, Minn. 4. Division of Vascular and Endovascular Surgery, Mayo Clinic, Rochester, Minn. 5. Division of Infectious Diseases, Mayo Clinic, Scottsdale, Ariz.
Abstract
OBJECTIVE: The objective of this study was to develop a surgical site infection (SSI) prediction score for risk assessment before elective vascular surgery. METHODS: We conducted a nested case-control study among patients who underwent elective vascular (abdominal aortic and peripheral arterial) surgery from January 1, 2003, to December 31, 2007, at Mayo Clinic (Rochester, Minn) an academic tertiary surgical center. Cases were patients with SSI requiring hospitalization; controls (one or two per case) were matched on type of procedure and date of surgery. Clinical data were collected by chart review. A risk score based on preoperative variables was developed using multivariable logistic regression and bootstrap resampling. The C statistic, equivalent to the area under the receiver operating characteristic curve, was used to assess discrimination. Calibration was assessed by plotting percentile risk groups of model-predicted values against observed proportions of subjects with SSI. RESULTS: Eighty-four cases were compared with 160 controls. Preoperative variables independently associated with SSI risk were critical limb ischemia, previous SSI, prior revascularization procedure, and chronic obstructive pulmonary disease. A prediction model containing these variables was developed (model and risk score C statistic of 0.737 and 0.727, respectively). The calibration curve did not appear to deviate appreciably from the 45-degree line of identity. CONCLUSIONS: We developed an SSI risk score based on noninvasive preoperative variables with acceptable discrimination and calibration. This tool needs prospective and external validation.
OBJECTIVE: The objective of this study was to develop a surgical site infection (SSI) prediction score for risk assessment before elective vascular surgery. METHODS: We conducted a nested case-control study among patients who underwent elective vascular (abdominal aortic and peripheral arterial) surgery from January 1, 2003, to December 31, 2007, at Mayo Clinic (Rochester, Minn) an academic tertiary surgical center. Cases were patients with SSI requiring hospitalization; controls (one or two per case) were matched on type of procedure and date of surgery. Clinical data were collected by chart review. A risk score based on preoperative variables was developed using multivariable logistic regression and bootstrap resampling. The C statistic, equivalent to the area under the receiver operating characteristic curve, was used to assess discrimination. Calibration was assessed by plotting percentile risk groups of model-predicted values against observed proportions of subjects with SSI. RESULTS: Eighty-four cases were compared with 160 controls. Preoperative variables independently associated with SSI risk were critical limb ischemia, previous SSI, prior revascularization procedure, and chronic obstructive pulmonary disease. A prediction model containing these variables was developed (model and risk score C statistic of 0.737 and 0.727, respectively). The calibration curve did not appear to deviate appreciably from the 45-degree line of identity. CONCLUSIONS: We developed an SSI risk score based on noninvasive preoperative variables with acceptable discrimination and calibration. This tool needs prospective and external validation.
Authors: Alex Wade; Margaret A Plymale; Daniel L Davenport; Sara E Johnson; Vashisht V Madabhushi; Erica Mastoroudis; Charlie Tancula; John Scott Roth Journal: Surg Endosc Date: 2017-09-15 Impact factor: 4.584
Authors: Brenig Llwyd Gwilym; Athanasios Saratzis; Ruth Benson; Rachael Forsythe; George Dovell; Nikesh Dattani; Tristan Lane; Ryan Preece; Joseph Shalhoub; David Charles Bosanquet Journal: Int J Surg Protoc Date: 2019-07-26