A 4-tier Protocolized Radiological Classification System for Leaks Following Sleeve Gastrectomy. Issue 2 (February 2022) - Johari, Yazmin; Catchlove, William; Tse, Madeleine; Shaw, Kalai; Paul, Eldho; Chen, Richard; Loh, Damien; Packiyanathan, Andrew; Burton, Paul; Nottle, Peter; Ellis, Samantha; Brown, Wendy
Abstract : Objectives: To develop and validate a classification of sleeve gastrectomy leaks able to reliably predict outcomes, from protocolized computed tomography (CT) findings and readily available variables. Summary of Background Data: Leaks post sleeve gastrectomy remain morbid and resource-consuming. Incidence, treatments, and outcomes are variable, representing heterogeneity of the problem. A predictive tool available at presentation would aid management and predict outcomes. Methods: From a prospective database (2009–2018) we reviewed patients with staple line leaks. A Delphi process was undertaken on candidate variables (80–20). Correlations were performed to stratify 4 groupings based on outcomes (salvage resection, length of stay, and complications) and predictor variables. Training and validation cohorts were established by block randomization. Results: A 4-tiered classification was developed based on CT appearance and duration postsurgery. Interobserver agreement was high (κ = 0.85, P < 0.001). There were 59 patients, (training: 30, validation: 29). Age 42.5 ± 10.8 versus 38.9 ± 10.0 years ( P = 0.187); female 65.5% versus 80.0% ( P = 0.211), weight 127.4 ± 31.3 versus 141.0 ± 47.9 kg, ( P = 0.203). In the training group, there was a trend toward longer hospital stays as grading increased (I = 10.5 d; II = 24 d; III = 66.5 d; IV = 72 d; P = 0.005). Risk of salvage resection increased (risk ratio grade 4 = 9; P = 0.043) as did complication severity ( P = 0.027). Findings were reproduced in the validation group: risk of salvage resection ( P = 0.007), hospital stay ( P = 0.001), complications ( P = 0.016). Conclusion: We have developed and validated a classification system, based on protocolized CT imaging that predicts a step-wise increased risk of salvage resection, complication severity, and increased hospital stay. The system should aid patient management and facilitate comparisons of outcomes and efficacy of interventions. Abstract : Supplemental Digital Content is available in the text