Robotic approach for retromuscular ventral hernia repair may be associated with improved wound morbidity in high-risk patients: a propensity score analysis

Background Retromuscular sublay (RMS) technique for repair of ventral hernias has gained popularity due to lower risk of recurrence and wound complications. Robotic approaches to RMS have been shown to decrease hospital stay; however, previous studies have failed to show a significant reduction in wound morbidity. Utilizing the Abdominal Core Health Quality Collaborative (ACHQC) database, this study sought to determine the effect of robotic approach on wound morbidity, while specifically focusing on a high-risk population.Methods A retrospective review of elective robotic and open RMS repairs in the ACHQC database was performed. Patients deemed to be high-risk for wound complications were included: adult patients with BMI greater than 35 and who were either current smokers or diabetics. A propensity score match was then done to balance covariates between the two groups. Main outcomes of concern were surgical site occurrences (SSO), surgical site infections (SSI), and surgical site occurrence requiring procedural intervention (SSOPI) at 30-day follow-up.Results A total of 917 patients met inclusion criteria. After propensity score matching, 211 patients matched for each approach. There was no difference in overall SSO (18% for Open vs 23% for Robotic, p = 0.23). Open repair was associated with higher rates of SSI (4% vs 1%, p = 0.032) and SSOPI (9% SSOPI vs 3%, p < 0. 015). As seen in previous studies, there was a higher rate of seroma associated with Robotic RMS repair (87% vs 48%, p < 0.001) in patients that developed an SSO.Conclusions In this analysis, a robotic approach was associated with decreased rates of SSI and SSOPI in obese patients who were either current smokers or diabetics. In effort to reduce wound morbidity and the associated physical and economic costs, robotic approach for retromuscular ventral hernia repair should be considered in this patient population.