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BACKGROUND: The component separation technique (CST) is considered an excellent technique for complex ventral hernia repair. However, postoperative infectious complications and reherniation rates are significant. Risk factor analysis for postoperative complication and reherniation has focused mostly on patient history and co-morbidity and shows equivocal results. The use of abdominal morphometrics derived from CT scans to assist in risk assessment seems promising. The aim of this study is to determine the predictability of reherniation and surgical site infections (SSI) using pre-operative CT measurements. METHODS: Electronic patient records were searched for patients who underwent CST between 2000 and 2013 and had a pre-operative CT scan available. Visceral fat volume (VFV), subcutaneous fat volume (SFV), loss of domain (LOD), rectus thickness and width (RT, RW), abdominal volume, hernia sac volume, total fat volume (TFV), sagittal distance (SD) and waist circumference (WC) were measured or calculated. Relevant variables were entered in multivariate regression analysis to determine their effect on reherniation and SSI as separate outcomes. RESULTS: (p = 0.034, OR = 0.26) were significant predictors of SSI. CONCLUSION: Visceral fat volume, subcutaneous fat volume and hernia sac volume derived from CT scan measurements may be used to predict reherniation and SSI in patients undergoing complex ventral hernia repair using CST. These findings may aid in optimizing patient-tailored preoperative risk assessment.
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Winters et al. (2019) studied this question.
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