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首页> 外文期刊>Diabetes therapy >Study Protocol for the Effects of Artificial Intelligence (AI)-Supported Automated Nutritional Intervention on Glycemic Control in Patients with Type 2 Diabetes Mellitus
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Study Protocol for the Effects of Artificial Intelligence (AI)-Supported Automated Nutritional Intervention on Glycemic Control in Patients with Type 2 Diabetes Mellitus

机译：人工智能（AI）支持的自动营养干预对2型糖尿病患者血糖控制的影响研究方案

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IntroductionNutritional intervention is effective in improving glycemic control in patients with type 2 diabetes but requires large inputs of manpower. Recent improvements in photo analysis technology facilitated by artificial intelligence (AI) and remote communication technologies have enabled automated evaluations of nutrient intakes. AI- and mobile-supported nutritional intervention is expected to be an alternative approach to conventional in-person nutritional intervention, but with less human resources, although supporting evidence is not yet complete. The aim of this study is to test the hypothesis that AI-supported nutritional intervention is as efficacious as the in-person, face-to-face method in terms of improving glycemic control in patients with type 2 diabetes. MethodsThis is a multicenter, unblinded, parallel, randomized controlled study comparing the efficacy of AI-supported automated nutrition therapy with that of conventional human nutrition therapy in patients with type 2 diabetes. Patients with type 2 diabetes mainly controlled with diet are to be recruited and randomly assigned to AI-supported nutrition therapy ( n =?50) and to human nutrition therapy ( n =?50). Asken, a mobile application whose nutritional evaluation has been already validated to that by the classical method of weighted dietary records, has been specially modified for this study so that it follows the recommendations of Japan Diabetes Society (total energy restriction with proportion of carbohydrates to fat to protein of 50–60, 20, and 20–30%, respectively). Planned OutcomesThe primary outcome is the change in glycated hemoglobin levels from baseline to 12?months, and this outcome is to be compared between the two groups. The secondary outcomes are changes in fasting plasma glucose, plasma lipid profile, body weight, body mass index, waist circumference, blood pressures, and urinary albumin excretion. The results of this randomized controlled trial will fill the gap between the demand for support of AI in nutritional interventions and the scientific evidence on its efficacy. Trial RegistrationUMIN000032231.
机译：简介营养干预可有效改善2型糖尿病患者的血糖控制，但需要大量人力。人工智能（AI）和远程通信技术促进了照片分析技术的最新改进，从而实现了对营养摄入量的自动评估。人工智能和移动支持的营养干预有望成为传统的面对面营养干预的替代方法，但人力资源较少，尽管支持证据尚不完善。这项研究的目的是检验以下假设的假设：就改善2型糖尿病患者的血糖控制而言，人工智能支持的营养干预与面对面面对面方法一样有效。方法这是一项多中心，无盲，平行，随机对照研究，比较了AI支持的自动营养疗法与常规人类营养疗法在2型糖尿病患者中的疗效。将招募主要受饮食控制的2型糖尿病患者，并将其随机分配至AI支持的营养治疗（n = 50）和人类营养治疗（n = 50）。 Asken是一种移动应用程序，其营养评估已通过经典的加权饮食记录方法得到验证，其营养评估已针对此研究进行了专门修改，使其遵循日本糖尿病学会的建议（总能量限制以及碳水化合物与脂肪的比例分别达到50-60％，20％和20-30％的蛋白质）。计划结果主要结果是糖化血红蛋白水平从基线到12个月的变化，这是两组之间的比较结果。次要结果是空腹血糖，血浆脂质分布，体重，体重指数，腰围，血压和尿白蛋白排泄的变化。这项随机对照试验的结果将填补营养干预中对AI的支持需求及其功效的科学证据之间的空白。试用注册UMIN000032231。

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