2022年8月11日

披露:梅塞尔集团报告接收说话和咨询酬金和串联糖尿病护理,Dexcom公司将和毛细管生物医学担任顾问。梅塞尔集团机构接收研究和项目赠款从雅培,β仿生学,,Dexcom公司将Insulet Corp .)、美敦力公司和串联糖尿病护理。请参阅研究对于所有其他作者的相关财务信息披露。主题添加到邮件提醒收到一封电子邮件在发布新文章时请提供您的电子邮件地址来接收电子邮件当张贴新文章。请稍后再试。如果你继续这个问题请联系customerservice@slackinc.com。回到Healio青少年和年轻的成年人与1型糖尿病血糖水平较低的时候感觉也更与他们的糖尿病管理,根据调查结果发表在糖尿病药物。“在青少年和年轻成人糖尿病患者,每日的个人因素,如自尊、健康观念,并计划或希望自己管理糖尿病的所有影响日常血糖,“月桂h·梅塞尔集团博士RN,儿科助理教授芭芭拉·戴维斯中心糖尿病,科罗拉多大学医学院的许茨告诉Healio。“这些日常预测可以被视为新靶点干预帮助支持青少年糖尿病的护理,特别是在帮助激励计划和愿望管理糖尿病早上的第一件事。“梅塞尔集团是一个儿科助理教授芭芭拉·戴维斯中心糖尿病,科罗拉多大学医学院的许茨。梅塞尔集团及其同事进行了一项纵向观察研究的2 88名1型糖尿病青少年和年轻人使用连续血糖监测,胰岛素泵或智能笔,和智能手机来管理他们的糖尿病患者(平均年龄17.6岁; 54% female; 90% white). Participants downloaded CGM and insulin delivery data at the end of the 2-week period to assess time in range, mean sensor glucose and user-initiated boluses. On six randomly selected days, participants completed a 25-item engagement prediction survey to assess biopsychosocial factors that could potentially influence daily engagement with diabetes management. The survey was administered in the morning and participants answered each question on a 4-point Likert scale. At the end of each assessment day, participants completed an end-of-day goal survey on a 5-point Likert scale to assess diabetes management goal attainment. Predictors of time in range, glycemic variability Mean average time in range fluctuated by 16% and mean absolute sensor glucose fluctuated by 30.4 mg/dL per day for each participant (P < .001 for both). The mean absolute change in number of boluses given fluctuated by 2.2 per day (P < .001). Seven questions in the engagement prediction survey were identified as being most predictive of glycemic outcomes. Those item responses predicted 16.7% of time in range variability, 18.6% of mean sensor glucose variability, 2.1% of variance in the number of boluses, 14% of the variability in hyperglycemia response and 28.7% of variability in diabetes management goal attainment. Positive engagement linked to lower glucose levels Participants who reported positively to sleeping longer (beta = –6.6; P < .001), sleeping well the previous night (beta = –12.6; P = .001), planning to manage their diabetes that day (beta = –17.7; P = .004), intending to manage their diabetes (beta = –16.6; P = .008), wanting to manage their diabetes (beta = –15.7; P = .001) and that they were feeling healthy (beta = –22.1; P < .001) were more likely to have lower glucose levels. Conversely, those who said they were too sick to manage their diabetes (beta = 29.1; P < .001) or felt they need extra support for their diabetes management (beta = 11.9; P = .004) had higher morning glucose levels. The cohort estimated they spent a median of 30 minutes caring for their diabetes and a median of 30 minutes thinking about their diabetes each day. The number of minutes thinking about diabetes was associated with the percent of hyperglycemia alerts responded to (P = .035) and perceived goal attainment score (P = .044). The number of minutes caring for diabetes was also positively associated with goal attainment score (P = .022). Time in range was inversely correlated to the number of boluses each day (beta = –0.9; P < .001). “We were most surprised that these factors predicted overall time in range; however, we were not able to explain how often the adolescent gave insulin doses for meals,” Messer said. “Usually, you assume that meal doses of insulin are what improve time in range, so we need to do more work to understand this.” For more information: