ACCURACY OF CARBOHYDRATE COUNTING IN TYPE 1 DIABETES MELLITUS

1 型糖尿病碳水化合物计数的准确性

基本信息

  • 批准号:
    7607302
  • 负责人:
  • 金额:
    $ 5.57万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2007
  • 资助国家:
    美国
  • 起止时间:
    2007-04-01 至 2008-03-31
  • 项目状态:
    已结题

项目摘要

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Dietary behaviors impact health outcomes in patients with type 1 diabetes mellitus. OBJECTIVE: To determine the impact of accurately of counting carbohydrates on glycemic control and growth patterns in children with type 1 diabetes mellitus. Cross-sectional analysis of 100 children with type 1 diabetes mellitus aged 2 to 12 years who report carbohydrate counting as their dietary method. Patients will be enrolled during routine outpatient visits at Children's Hospital, Boston, Massachusetts. Relevant surveys and questionnaires will be completed at the time of enrollment. 24-hour dietary recalls will be performed by phone interview on 3 separate occasions for each patient enrolled in the study. Parent's assessments of carbohydrate content will be compared to computer analysis of the 24-hour dietary recall. The anticipated enrollment period will be 6 months. MAIN OUTCOME MEASURES: Assessment of carbohydrate content by parent and computer analysis of 24-dietary recall, hemoglobin A1c level, anthropometric data, insulin regimen and severe hypoglycemic reactions and relevant demographic data. RESULTS: As a group, parents' estimation of their child's carbohydrate intake will be compared to computer analysis of the same meals, expressed as a percentage (primary aim). Estimations will be categorized as "accurate" or "inaccurate" if they are within or deviate by greater than 25% of the computer analysis, respectively. Clinical variables and demographic variables will be incorporated into a logistic regression model to determine predictors of accuracy in carbohydrate counting. Finally, parents who are accurate and inaccurate will be compared on the basis of clinically relevant outcomes for their children with type 1 diabetes: HbA1c (measure of glycemic control), rates of severe hypoglycemia and body mass index (secondary aims).
该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金, 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说,它不一定是研究者的机构。 饮食行为影响 1 型糖尿病患者的健康结果。 目的:确定准确计算碳水化合物对 1 型糖尿病儿童血糖控制和生长模式的影响。 对 100 名 2 至 12 岁 1 型糖尿病儿童的横断面分析,他们报告称碳水化合物计数是他们的饮食方法。 患者将在马萨诸塞州波士顿儿童医院的常规门诊就诊期间被纳入。 相关调查和问卷将在入学时完成。 将通过电话采访对参与研究的每位患者进行 3 次 24 小时饮食回顾。 家长对碳水化合物含量的评估将与 24 小时饮食回忆的计算机分析进行比较。 预计入学期限为6个月。 主要观察指标:由家长评估碳水化合物含量,并通过计算机分析 24 日饮食回忆、糖化血红蛋白水平、人体测量数据、胰岛素治疗方案和严重低血糖反应以及相关人口统计数据。 结果:作为一个群体,家长对孩子碳水化合物摄入量的估计将与相同膳食的计算机分析进行比较,以百分比表示(主要目标)。 如果估计值在计算机分析范围内或偏差超过 25%,则将分别归类为“准确”或“不准确”。 临床变量和人口统计变量将被纳入逻辑回归模型中,以确定碳水化合物计数准确性的预测因素。 最后,准确和不准确的父母将根据其患有 1 型糖尿病的孩子的临床相关结果进行比较:HbA1c(血糖控制指标)、严重低血糖发生率和体重指数(次要目标)。

项目成果

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Sanjeev Narendra Mehta的其他文献

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