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Computed tomography-based intermuscular adipose tissue analysis and its predicting role in post-kidney transplantation diabetes mellitus.
Feng, Yang; Shi, Yuechen; Ma, Kexin; Xiao, Jiaming; Liu, Ming; Yi, Yuqing; Zhang, Xiaoyu; Wang, Ke; Gao, Zhenming.
Afiliação
  • Feng Y; 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.
  • Shi Y; 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.
  • Ma K; Department of Hepatobiliary Surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning, People's Republic of China.
  • Xiao J; 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.
  • Liu M; 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.
  • Yi Y; 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.
  • Zhang X; Department of Metabolism, Digestion, and Reproduction, Imperial College London, London, W12 0NN, United Kingdom.
  • Wang K; Department of Clinical Nutrition, The Second Hospital of Dalian Medical University, Dalian, Liaoning, People's Republic of China. Electronic address: wang_ke@dmu.edu.cn.
  • Gao Z; Department of Hepatobiliary Surgery, The Second Hospital of Dalian Medical University, Dalian, Liaoning, People's Republic of China. Electronic address: gaozhenmingdl@163.com.
Asian J Surg ; 2024 Sep 04.
Article em En | MEDLINE | ID: mdl-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).
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article