Novel classification system for walled-off necrosis: a step toward standardized nomenclature and risk-stratification...

The optimal therapeutic approach for walled-off necrosis (WON) is not fully understood, given the lack of a validated classification system. We propose a novel and robust classification system based on radiologic and clinical factors to standardize the nomenclature, provide a framework to guide comparative effectiveness trials, and inform the optimal WON interventional approach.

This was a retrospective analysis of patients who underwent endoscopic management of WON by lumen-apposing metal stent placement at a tertiary referral center. Patients were classified according to the proposed QNI classification system: quadrant ("Q"), represented an abdominal quadrant distribution; necrosis ("N"), denoted by the percentage of necrosis of WON; and infection ("I"), denoted as positive blood culture and/or systemic inflammatory response syndrome reaction with a positive WON culture. Two blinded reviewers classified all patients according to the QNI system. Patients were then divided into 2 groups: those with a lower QNI stratification (≤2 quadrants and ≤30% necrosis; group 1) and those with a higher stratification (≥3 quadrants, 2 quadrants with ≥30% necrosis, or 1 quadrant with >60% necrosis and infection; group 2). The primary outcome was mean time to WON resolution. Secondary procedural and clinical outcomes between the groups were compared.

Seventy-one patients (75% men) were included and stratified by the QNI classification; group 1 comprised 17 patients and group 2, 54 patients. Patients in group 2 had a higher number of necrosectomies, longer hospital stays, and more readmissions. The mean time to resolution was longer in group 2 than in group 1 (79.6 ± 7.76 days vs 48.4 ± 9.22 days, P = .02). The mortality rate was higher in group 2 (15% vs 0%, P = .18).

Despite the heterogeneous nature of WON in severe acute pancreatitis, a proposed QNI system may provide a standardized framework for WON classification to inform clinical trials, risk-stratify the disease course, and potentially inform an optimal management approach.