Eating Disturbances in Patients With Type 1 Diabetes Initiating Closed-loop Insulin Therapy: Prevalence and Influence on Glycemic Control
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Prevalence of eating disorders
研究概览
简要总结
The prevalence of eating disorders is particularly high among people with type 1 diabetes (T1D). These abnormalities, such as "diabulimia," are frequently responsible for poor insulin therapy management and, consequently, chronic glycemic imbalance, exposing them to an increased risk of complications. Their detection and management unfortunately remain insufficient in current practice.
However, to date, no study has addressed the question of the prevalence and impact of eating disorders in this context. Our research hypotheses are therefore as follows:
- The existence of an eating disorder is likely frequently overlooked and, therefore, not taken into account in patients with T1D initiating semi-automated insulin therapy with BF.
- The existence of an eating disorder could impair the performance of the BF device in terms of improving glycemic control in patients with T1D initiating this treatment method.
Patients clinical characteristics, glycemic monitoring parameters ad questionnaires answers will be recorded. The prevalence of eating disorders will be calculated, and the association between the presence of these abnormalities and baseline clinical characteristics and glycemic control parameters will be analyzed.
详细描述
The prevalence of eating disorders (EDs) and problematic eating behaviors (PEBs) is particularly high among people with type 1 diabetes (T1D), affecting 20 to 50% of women and 5 to 25% of men among young patients. These abnormalities, such as "diabulimia," are frequently responsible for poor insulin therapy management and, consequently, chronic glycemic imbalance, exposing them to an increased risk of complications. Their detection and management unfortunately remain insufficient in current practice.
The treatment of T1D is currently undergoing a veritable technological revolution linked to the arrival of the first semi-automated insulin therapy devices (or closed loop, LF). The use of these devices most often makes it possible to achieve recommended glycemic control targets (HbA1c, continuous glucose monitoring [CGM] data), reduce glycemic variability, and avoid hypoglycemia. Insulin administration is based on the data transmitted: food intake and quantity of carbohydrates consumed. The role of dietitians is therefore crucial in the therapeutic education of patients and the care pathway imposed by the initiation of this new treatment method. It is likely that many patients initiating automated insulin therapy with BF present an eating disorder or CAP that may interfere with the management of the device.
However, to date, no study has addressed the question of the prevalence and impact of eating disorders and CAP in this context. In the absence of available data, national and international recommendation texts dedicated to insulin therapy with BF do not specify appropriate conduct for patients presenting with these eating disorders. Our research hypotheses are therefore as follows:
- The existence of an eating disorder (ED and/or CAP) is likely frequently overlooked and, therefore, not taken into account in patients with T1D initiating semi-automated insulin therapy with BF.
- The existence of an eating disorder (ED and/or CAP) could impair the performance of the BF device in terms of improving glycemic control in patients with T1D initiating this treatment method.
Patients clinical characteristics and glycemic monitoring parameters (HbA1c and CGM data), available as part of routine care, will be recorded in an electronic case report (REDCap software). The mSCOFF and QACD questionnaires will be administered during the dietary interview preceding BF device implantation, and responses will be collected. The prevalence of eating disorders will be calculated, and the association between the presence of these abnormalities and baseline clinical characteristics and glycemic control parameters will be analyzed.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patient diagnosed with type 1 diabetes.
- •Patient with a CGM device for more than 3 months with > 80% of data captured in the last month.
- •Indication for the implementation of a BF device as part of routine care, in the Diabetology, Metabolic Diseases and Nutrition Department of the Toulouse University Hospital (initiating center).
排除标准
- •Pregnant or breastfeeding women, or those planning to become pregnant within 6 months of inclusion.
- •History of obesity surgery or a preparatory program for obesity surgery planned during the study period.
- •Pharmacological treatment likely to significantly influence food intake and body weight, whether ongoing or discontinued within the last 3 months (e.g., GLP-1R agonist): Liraglutide (Victoza®, Saxenda®), Semaglutide (Ozempic®, Wegovy®), Dulaglutide (Trulicity®), Tirzepatde (Mounjaro®), Orlistat (Xenical®)
- •Eating disorder requiring specific treatment in the previous 12 months.
- •Refusal or inability to consent to participate.
- •Persons under legal protection (guardianship, curatorship, or court-ordered protection).
结局指标
主要结局
Prevalence of eating disorders
时间窗: 6 months after the inclusion
The primary outcome measure for establishing the prevalence of eating disorders is a composite outcome measure based on determining the existence of eating disorders \[ED\] by analyzing responses to the mSCOFF questionnaire (score ≥ 2) and/or problematic eating behaviors \[PEB\] by analyzing responses to the QACD questionnaire (score ≥ 20).
次要结局
- Prevalence of eating disorders (EDs)(6 months after the inclusion)
- Clinical characteristics at inclusion(6 months after the inclusion)
- Description of glycemic control at inclusion(6 months after the inclusion)
- Description of variability indicators at inclusion(6 months after the inclusion)
- Evolution of biological parameters of glycemic variability between the inclusion visit and the follow-up visits(6 months after the inclusion)
- Evolution of biological control parameters variability between the inclusion visit and the follow-up visits(6 months after the inclusion)
- Evolution of BMI between inclusion and follow-up visits(6 months after the inclusion)
- Change in questionnaires scores between baseline and follow-up(6 months after the inclusion)
- Evolution of body weight between inclusion and follow-up visits(6 months after the inclusion)