Endocrinology and Nutrition Service, Hospital Universitario Príncipe de Asturias, Madrid, Spain.
Computer Architecture and Automation Department, Universidad Complutense de Madrid, Madrid, Spain.
Front Endocrinol (Lausanne). 2023 Feb 22;14:998881. doi: 10.3389/fendo.2023.998881. eCollection 2023.
Sleep quality disturbances are frequent in adults with type 1 diabetes. However, the possible influence of sleep problems on glycemic variability has yet to be studied in depth. This study aims to assess the influence of sleep quality on glycemic control.
An observational study of 25 adults with type 1 diabetes, with simultaneous recording, for 14 days, of continuous glucose monitoring (Abbott FreeStyle Libre system) and a sleep study by wrist actigraphy (Fitbit Ionic device). The study analyzes, using artificial intelligence techniques, the relationship between the quality and structure of sleep with time in normo-, hypo-, and hyperglycemia ranges and with glycemic variability. The patients were also studied as a group, comparing patients with good and poor sleep quality.
A total of 243 days/nights were analyzed, of which 77% ( = 189) were categorized as poor quality and 33% ( = 54) as good quality. Linear regression methods were used to find a correlation ( =0.8) between the variability of sleep efficiency and the variability of mean blood glucose. With clustering techniques, patients were grouped according to their sleep structure (characterizing this structure by the number of transitions between the different sleep phases). These clusters showed a relationship between time in range and sleep structure.
This study suggests that poor sleep quality is associated with lower time in range and greater glycemic variability, so improving sleep quality in patients with type 1 diabetes could improve their glycemic control.
睡眠质量障碍在 1 型糖尿病成人中很常见。然而,睡眠问题对血糖变异性的可能影响尚未深入研究。本研究旨在评估睡眠质量对血糖控制的影响。
这是一项对 25 名 1 型糖尿病成人的观察性研究,同时记录 14 天的连续血糖监测(Abbott FreeStyle Libre 系统)和腕部动作记录仪(Fitbit Ionic 设备)的睡眠研究。该研究使用人工智能技术分析睡眠质量和结构与正常、低血糖和高血糖范围内的时间以及血糖变异性之间的关系。还将患者作为一个整体进行研究,比较睡眠质量好和差的患者。
共分析了 243 天/夜,其中 77%(=189)被归类为睡眠质量差,33%(=54)为睡眠质量好。线性回归方法用于寻找睡眠效率变异性和平均血糖变异性之间的相关性(=0.8)。使用聚类技术,根据患者的睡眠结构(通过不同睡眠阶段之间的转换次数来描述这种结构)对患者进行分组。这些聚类显示了时间在范围内和睡眠结构之间的关系。
这项研究表明,睡眠质量差与时间在范围内的时间减少和血糖变异性增加有关,因此改善 1 型糖尿病患者的睡眠质量可能改善他们的血糖控制。