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.

Impact of Coronary Computerized Tomography Angiography-Derived Plaque Quantification and Machine-Learning Computerized Tomography Fractional Flow Reserve on Adverse Cardiac Outcome.

This study investigated the impact of coronary CT angiography (cCTA)-derived plaque markers and machine-learning-based CT-derived fractional flow reserve (CT-FFR) to identify adverse cardiac outcome. Data of 82 patients (60 ± 11 years, 62% men) who underwent cCTA and invasive coronary angiography (ICA) were analyzed in this single-center retrospective, institutional review board-approved, HIPAA-compliant study. Follow-up was performed to record major adverse cardiac events (MACE). Plaque quantification of lesions responsible for MACE and control lesions was retrospectively performed semiautomatically from cCTA together with machine-learning based CT-FFR. The discriminatory value of plaque markers and CT-FFR to predict MACE was evaluated. After a median follow-up of 18.5 months (interquartile range 11.5 to 26.6 months), MACE was observed in 18 patients (21%). In a multivariate analysis the following markers were predictors of MACE (odds ratio [OR]): lesion length (OR 1.16, p = 0.018), low-attenuation plaque (<30 HU) (OR 4.59, p = 0.003), Napkin ring sign (OR 2.71, p = 0.034), stenosis ≥50% (OR 3.83, p 0.042), and CT-FFR ≤0.80 (OR 7.78, p = 0.001). Receiver operating characteristics analysis including stenosis ≥50%, plaque markers and CT-FFR ≤0.80 (Area under the curve 0.94) showed incremental discriminatory power over stenosis ≥50% alone (Area under the curve 0.60, p <0.0001) for the prediction of MACE. cCTA-derived plaque markers and machine-learning CT-FFR demonstrate predictive value to identify MACE. In conclusion, combining plaque markers with machine-learning CT-FFR shows incremental discriminatory power over cCTA stenosis grading alone.