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Carbohydrate Metabolism01:36

Carbohydrate Metabolism

Carbohydrates are polymers composed of molecules containing atoms of carbon, hydrogen and oxygen. One gram of carbohydrate can provide four kilo-calories of energy, which makes it the most efficient instant energy source.
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Type 2 diabetes, characterized by insulin resistance, arises when the insulin receptors on cells lose responsiveness to insulin, diminishing the cell's capacity to take up glucose, resulting in elevated blood glucose levels. To receive a diagnosis of Type 2 diabetes, a series of blood glucose tests are necessary to assess whether the blood glucose falls within normal parameters. If the result is out of the normal range, a patient may be diagnosed as prediabetic or diabetic, depending on the...
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Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance, in which target tissues such as the liver, muscle, and adipose tissue respond poorly to insulin. It is also associated with inadequate compensatory insulin secretion, where pancreatic β-cells fail to produce sufficient insulin. Together, these abnormalities lead to persistent hyperglycemia.EtiologyT2DM develops through a complex interaction of genetic predisposition and environmental or...
Type II Diabetes II: Pathophysiology01:24

Type II Diabetes II: Pathophysiology

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在2型糖尿病中检测身体活动的数字生物阻抗:准实验验证研究.

Akira Kimura1, Shinobu Onozawa1, Takayuki Ogiwara2

  • 1Graduate School of Health Science, Gunma Paz University, 1-7-1 Tonyamachi, Takasaki, 370-0006, Japan, 81 273653366, 81 273880865.

JMIR diabetes
|December 16, 2025
PubMed
概括

生物电阻分析 (BIA) 显示,作为2型糖尿病患者体力活动和血糖控制的数字生物标志物具有前途. 这项研究表明,BIA可用于例行糖尿病护理,有助于精确管理.

关键词:
生物电阻的生物电阻.建筑环境 建筑环境血糖糖尿病,第二种类型.数字健康数字健康运动疗法 运动疗法血红蛋白A,糖化血红蛋白 A,糖化血红蛋白 A,糖化血红蛋白 A.监测,生理学监测,生理学监测初级医疗保健是一项主要的医疗保健服务.

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科学领域:

  • 生物医学工程 生物医学工程
  • 数字健康数字健康
  • 内分泌学 在内分泌学.

背景情况:

  • 在2型糖尿病管理的初级保健中,缺乏客观,可扩展的方法来持续监测身体活动.
  • 生物电阻分析 (BIA) 是糖尿病护理中的常规测试,具有作为行为表型化自动化数字生物标志物的潜力,但需要验证.

研究的目的:

  • 评估多频生物阻抗用于体力活动检测的可行性和预测有效性.
  • 评估生物阻抗衍生体力活动指标与2型糖尿病患者的血糖控制之间的关联.

主要方法:

  • 这是一项务实的准实验性研究,涉及三个四个月的时间分配:全面的BIA指导咨询,部分跟踪和标准护理.
  • 每月分段多频BIA在2型糖尿病 (HbA1c 7.0%-10.0%) 的成年人身上进行.
  • 主要结局:HbA1c <7% 在4个月. 分析包括千平方趋势测试,多变量逻辑回归,ANCOVA和ROC曲线分析,以预测左臂反应率的有效性.

主要成果:

  • 在综合性BIA组 (80%),部分跟踪 (58%) 和标准护理 (56%) (P<.001) 之后,HbA1c<7%的达到是最高的.
  • 左臂50kHz反应率显著预测了目标HbA1c的实现 (调整的OR每1SD增加=3.04;P<.001;AUC=0.847).
  • 效果因邻里可行性 (步行得分×干预相互作用,P=.028) 而有所不同,反应率的变化与成就者的HbA1c变化相关.

结论:

  • 自动化BIA可用于例行糖尿病护理,并显示其作为活动相关血糖控制的数字生物标志物的潜力.
  • 结果表明BIA在精确糖尿病管理中的实用性,左臂反应率需要进一步的随机验证.
  • 该研究强调了BIA作为可扩展的被动监控工具的潜力,用于监测身体活动及其对血糖控制的影响.