基于计算机断层扫描的肌间脂肪组织分析及其在肾移植后糖尿病中的预测作用。

Computed tomography-based intermuscular adipose tissue analysis and its predicting role in post-kidney transplantation diabetes mellitus.

作者信息

Feng Yang, Shi Yuechen, Ma Kexin, Xiao Jiaming, Liu Ming, Yi Yuqing, Zhang Xiaoyu, Wang Ke, Gao Zhenming

机构信息

Department of Clinical Nutrition, The Second Hospital of Dalian Medical University, Dalian, Liaoning, People's Republic of China; Department of Nutrition and Food Hygiene, School of Public Health, Dalian Medical University, Dalian, Liaoning, People's Republic of China.

Department of Hepatobiliary Surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning, People's Republic of China.

出版信息

Asian J Surg. 2024 Sep 4. doi: 10.1016/j.asjsur.2024.08.075.

DOI:10.1016/j.asjsur.2024.08.075

PMID:39237404

Abstract

BACKGROUND

While body mass index (BMI) is the most widely used indicator as a measure of obesity factors in post-transplantation diabetes mellitus (PTDM), body composition is a more accurate measure of obesity. This study aims to investigate the effects of Computed tomography (CT)--based morphemic factors on PTDM and establish a prediction model for PTDM after kidney transplantation.

METHODS

The pre-transplant data and glycemic levels of kidney transplant recipients (June 2021 to July 2023) were retrospectively and prospectively collected. Univariate and multivariate analyses were conducted to analyze the relationship between morphemic factors and PTDM at one month, six months, and one year after hospital discharge. Subsequently, a one-year risk prediction model based on morphemic factors was developed.

RESULTS

The study consisted of 131 participants in the one-month group, where Hemoglobin A1c (HbA1c) (p = 0.02) was identified as the risk factor for PTDM. In the six-month group, 129 participants were included, and the intermuscular adipose tissue (IMAT) area (p = 0.02) was identified as the risk factor for PTDM. The one-year group had 128 participants, and the risk factors for PTDM were identified as body mass index (BMI) (p = 0.02), HbA1c (p = 0.01), and IMAT area (p = 0.007). HbA1c (%) and IMAT area were included in the risk prediction Model for PTDM in the one-year group with AUC = 0.716 (95 % CI 0.591-0.841, p = 0.001).

CONCLUSIONS

Compared to BMI and other morphemic factors, this study demonstrated that the IMAT area was the most potential predictor of PTDM.

CLINICAL TRIAL NOTATION

Chictr.org (ChiCTR2300078639).

摘要

背景

虽然体重指数（BMI）是移植后糖尿病（PTDM）中最广泛使用的肥胖因素衡量指标，但身体成分是更准确的肥胖衡量指标。本研究旨在探讨基于计算机断层扫描（CT）的形态学因素对PTDM的影响，并建立肾移植后PTDM的预测模型。

方法

回顾性和前瞻性收集肾移植受者（2021年6月至2023年7月）的移植前数据和血糖水平。进行单因素和多因素分析，以分析出院后1个月、6个月和1年时形态学因素与PTDM之间的关系。随后，建立了基于形态学因素的1年风险预测模型。

结果

1个月组有131名参与者，其中糖化血红蛋白（HbA1c）（p = 0.02）被确定为PTDM的危险因素。6个月组纳入129名参与者，肌间脂肪组织（IMAT）面积（p = 0.02）被确定为PTDM的危险因素。1年组有128名参与者，PTDM的危险因素被确定为体重指数（BMI）（p = 0.02）、HbA1c（p = 0.01）和IMAT面积（p = 0.007）。HbA1c（%）和IMAT面积被纳入1年组PTDM的风险预测模型，AUC = 0.716（95%CI 0.591 - 0.841，p = 0.001）。