Risk Factors Influencing the Thickness and Stranding of Perinephric Fat of Mayo Adhesive Probability Score in Minimally Invasive Nephrectomy

• Published in: Medical science monitor Vol. 25; pp. 3825 - 3831
• Main Authors: Yao, Yuanxin, Gong, Huijie, Pang, Yuewen, Gu, Liangyou, Niu, Shaoxi, Xu, Yansheng, Li, Pin, Liu, Kan, Tang, Lu, Xuan, Yundong, Gao, Yu, Zhang, Xu
• Format: Journal Article
• Language: English
• Published: United States International Scientific Literature, Inc 23.05.2019
• Subjects: Adipose Tissue - pathology; Body Mass Index; Carcinoma, Renal Cell - pathology; Clinical Research; Female; Humans; Intra-Abdominal Fat - pathology; Kidney - pathology; Kidney Neoplasms - pathology; Magnetic Resonance Imaging - methods; Male; Middle Aged; Multivariate Analysis; Nephrectomy - methods; Retrospective Studies; Risk Factors; Tomography, X-Ray Computed - methods
• ISSN: 1643-3750; 1234-1010; 1643-3750
• DOI: 10.12659/MSM.916359

BACKGROUND Mayo adhesive probability (MAP) score, an accurate and reliable predictor of adherent perinephric fat (APF), consists of posterior perinephric fat thickness and perinephric fat stranding. The present study aimed to identify the potential clinical characteristics associated with these 2 variables to further our understanding of APF. MATERIAL AND METHODS Clinical data of 346 patients subjected to minimally invasive nephrectomy was collected within our prospectively maintained database, between January 2015 and December 2016. Radiological data was assessed by 2 readers in an independent blinded - to each other and APF patient status - fashion. Ordinal logistic regression analyses were performed to evaluate risk factors of posterior perinephric fat thickness and perinephric fat stranding. RESULTS On multivariate analysis, posterior perinephric fat thickness was associated with older age (ß=1.05 [range, 1.03-1.07], P<0.01); male gender (ß=6.06 [3.18-11.54], P<0.01), and higher body mass index (BMI) (ß=1.31 [1.21-1.41], P<0.01). Perinephric fat stranding was associated with older age (ß=1.05 [1.02-1.07], P<0.01), male gender (ß=3.64 [2.09-6.34], P<0.01) and history of diabetes (ß=2.09 [1.24-3.52], P<0.01). MAP score was associated with older age (ß=1.05 [1.03-1.07], P<0.01), male gender (ß=5.07 [2.96-8.71], P<0.01), higher BMI (ß=1.14 [1.07-1.21], P<0.01), history of diabetes (ß=1.72 [1.06-2.78], P=0.03) and alcoholism (ß=1.88 [1.10-3.20], P=0.02). CONCLUSIONS The current study highlights that different risk factors influence the posterior perinephric fat thickness and perinephric fat stranding. Posterior perinephric fat thickness was correlated with age, gender, and BMI, while perinephric fat stranding was associated with age, gender, and history of diabetes.