Computed tomography-based multiple body composition parameters predict outcomes in Crohn's disease

基于计算机断层扫描的多项身体成分参数可预测克罗恩病的预后

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Abstract

BACKGROUND: The efficacy of computed tomography-based multiple body composition parameters in assessing disease behavior and prognosis has not been comprehensively evaluated in Crohn's disease. This study aimed to assess the association of body composition parameters with disease behavior and outcomes in Crohn's disease and to compare the efficacies of indexes derived from body and lumbar spinal heights in body composition analysis. RESULTS: One hundred twenty-two patients with confirmed Crohn's disease diagnoses and abdominal computed tomography scans were retrospectively included in this study. Skeletal muscle, visceral, and subcutaneous fat indexes were calculated by dividing each type of tissue area by height(2) and lumbar spinal height(2). Parameters reflecting the distribution of adiposity were also assessed. Principal component analysis was used to deal with parameters with multicollinearity. Patients were grouped according to their disease behavior (inflammatory vs. structuring/penetrating) and outcomes. Adverse outcome included need for intestinal surgery or anti-TNF therapy. Predictors of disease course from multiple parameters were evaluated using multivariate analysis. Indexes derived from body and lumbar spinal heights were strongly correlated (r, 0.934-0.995; p < 0.001). Low skeletal muscle-related parameters were significantly associated with complicated disease behavior in multivariate analysis (p = 0.048). Complicated disease behavior (p < 0.001) and adipose tissue parameters-related first principal component (p = 0.029) were independent biomarkers for predicting adverse outcomes. CONCLUSIONS: Skeletal muscle and adipose tissue principle component were associated with complicated Crohn's disease behavior and adverse outcome, respectively. Indexes derived from body and lumbar spinal heights have similar efficacies in body composition analysis.

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