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

IF 3.5 3区 医学 Q1 SURGERY Asian Journal of Surgery Pub Date : 2024-09-04 DOI:10.1016/j.asjsur.2024.08.075
Yang Feng, Yuechen Shi, Kexin Ma, Jiaming Xiao, Ming Liu, Yuqing Yi, Xiaoyu Zhang, Ke Wang, Zhenming Gao
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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).

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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。
背景:虽然体重指数(BMI)是衡量移植后糖尿病(PTDM)肥胖因素最广泛使用的指标,但身体成分是衡量肥胖更准确的指标。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。方法:回顾性和前瞻性收集肾移植受者的移植前数据和血糖水平(2021 年 6 月至 2023 年 7 月),并进行单变量和多变量分析,以分析出院后一个月、六个月和一年的发病因素与 PTDM 之间的关系。随后,根据病态因素建立了一年期风险预测模型:一个月组有 131 人参加研究,其中血红蛋白 A1c(HbA1c)(p = 0.02)被确定为 PTDM 的风险因素。六个月组有 129 名参与者,肌肉间脂肪组织(IMAT)面积(p = 0.02)被确定为 PTDM 的风险因素。一年组有 128 名参与者,PTDM 的风险因素为体重指数 (BMI)(p = 0.02)、HbA1c(p = 0.01)和 IMAT 面积(p = 0.007)。HbA1c (%) 和 IMAT 面积被纳入一年组 PTDM 风险预测模型,AUC = 0.716 (95 % CI 0.591-0.841, p = 0.001):结论:与体重指数(BMI)和其他形态因素相比,该研究表明 IMAT 面积是预测 PTDM 的最潜在因素:Chictr.org(ChiCTR2300078639)。
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来源期刊
Asian Journal of Surgery
Asian Journal of Surgery 医学-外科
CiteScore
3.60
自引率
31.40%
发文量
1589
审稿时长
33 days
期刊介绍: Asian Journal of Surgery, launched in 1978, is the official peer-reviewed open access journal of the Asian Surgical Association, the Taiwan Robotic Surgery Association, and the Taiwan Society of Coloproctology. The Journal is published monthly by Elsevier and is indexed in SCIE, Medline, ScienceDirect, Scopus, Embase, Current Contents, PubMed, Current Abstracts, BioEngineering Abstracts, SIIC Data Bases, CAB Abstracts, and CAB Health. ASJSUR has a growing reputation as an important medium for the dissemination of cutting-edge developments in surgery and its related disciplines in the Asia-Pacific region and beyond. Studies on state-of-the-art surgical innovations across the entire spectrum of clinical and experimental surgery are particularly welcome. The journal publishes original articles, review articles, and case reports that are of exceptional and unique importance. The journal publishes original articles, review articles, and case reports that are of exceptional and unique importance.
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