A 4-tier Protocolized Radiological Classification System for Leaks Following Sleeve Gastrectomy.

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.

journal_name

Ann Surg

journal_title

Annals of surgery

authors

Johari Y,Catchlove W,Tse M,Shaw K,Paul E,Chen R,Loh D,Packiyanathan A,Burton P,Nottle P,Ellis S,Brown W

doi

10.1097/SLA.0000000000003984

subject

Has Abstract

pub_date

2021-01-19 00:00:00

eissn

0003-4932

issn

1528-1140

pii

00000658-900000000-93755

pub_type

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