From Surgeon Discretion to Indication: Utilization of an Objective Clinical Decision Tool Predicts Risk-Stratified Benefit of Retrorectus Mesh Reinforcement After Abdominal Free-Flap Breast Reconstruction

BACKGROUND: Previous work has demonstrated mixed evidence on prophylactic mesh reinforcement to prevent abdominal laxity. Our study created a clinical decision tool to identify who may benefit from mesh reinforcement compared to an active prophylactic control. After risk-stratifying vulnerable populations, we hypothesized that high risk populations would most benefit from mesh placement. METHODS: We performed a retrospective cohort study of 100 consecutive abdominal free flaps at our institution (33 retrorectus P4HB mesh, 67 plication ± onlay mesh). We created a CT-dervied Abdominal Wall Vulnerability Index (AWVI) that incorporated into known preoperative risk factors to stratify patients into risk tertiles. Primary endpoint was clinical diagnosis of bulge collected in a time-to-event fashion. Treatment effect was assessed using a multivariate Cox regression, with propensity-weighted modeling and Firth-penalized regression as sensitivity analyses. RESULTS: Abdominal bulge occurred in 37.3% of patients in the plication patients, and 6.1% in the retrorectus mesh group (p<0.001). Retrorectus reinforcement reduced bulge risk in Cox modeling (HR≈0.19, p<0.04) and sensitivity analyses (OR≈0.09, p<0.01). Kaplan-Meier curves demonstrated early and persistent bulge-free survival beyond two years. Prospective application of risk stratification system demonstrated a 36.4% ARR with mesh placement in moderate laxity groups, and a 47.7% ARR in high laxity groups. Addition of intraoperative stressors—lateral perforator use, multiple perforators, technique (ms-TRAM vs. DIEP) further informed selection. CONCLUSIONS: Retrorectus P4HB reinforcement substantially reduces bulge compared with active prophylaxis and shows durable benefit. The proposed vulnerability framework within this study supports selective reinforcement in patients at highest predicted risk.