Body morphometry may predict parastomal hernia following radical cystectomy with ileal conduit
Objective To investigate whether preoperative body morphometry analysis can identify patients at risk of parastomal hernia (PH), which is a common complication after radical cystectomy (RC). Patients and Methods All patients who underwent RC between 2010 and 2020 with available cross‐sectional imagi...
Gespeichert in:
Veröffentlicht in: | BJU international 2024-11, Vol.134 (5), p.841-847 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Objective
To investigate whether preoperative body morphometry analysis can identify patients at risk of parastomal hernia (PH), which is a common complication after radical cystectomy (RC).
Patients and Methods
All patients who underwent RC between 2010 and 2020 with available cross‐sectional imaging preoperatively and at 1 and 2 years postoperatively were included. Skeletal muscle mass and total fat mass (FM) were determined from preoperative axial computed tomography images obtained at the level of the L3 vertebral body using Aquarius Intuition software. Sarcopenia and obesity were assigned based on consensus definitions of skeletal muscle index (SMI) and FM index (FMI). PH were graded using both the Moreno‐Matias and European Hernia Society criteria. Binary logistic regression and recursive partitioning were used to identify patients at risk of PH. The Kaplan–Meier method with log‐rank and Cox proportional hazards models included clinical and image‐based parameters to identify predictors of PH‐free survival.
Results
A total of 367 patients were included in the final analysis, with 159 (43%) developing a PH. When utilising binary logistic regression, high FMI (odds ratio [OR] 1.63, P |
---|---|
ISSN: | 1464-4096 1464-410X 1464-410X |
DOI: | 10.1111/bju.16434 |