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对糖尿病风险预测模型的元分析,应用于糖尿病前期查
Yujin Liu1,2, Sunrui Yu3, Wenming Feng4
1Nursing Department, The second Hosiptal of Jinhua, Jinhua, China.
Diabetes, obesity & metabolism
|February 1, 2024
概括
现有的糖尿病风险预测模型显示,由于方法限制和人口差异,糖尿病前期查的有效性较差. 需要进一步的研究来提高它们的临床相关性和用于预防糖尿病的预测性.
科学领域:
- 内分泌学 在内分泌学.
- 公共卫生 公共卫生
- 生物统计学 生物统计学
背景情况:
- 糖尿病前期显著增加了患2型糖尿病的风险.
- 早期识别患有糖尿病前期风险较高的个体对于初级预防策略至关重要.
- 现有的糖尿病风险预测模型越来越多地被用于糖尿病前期查.
研究的目的:
- 系统地审查和概述用于糖尿病前期查的糖尿病风险预测模型.
- 评估目前用于初级糖尿病预防的模型的现状和局限性.
主要方法:
- 在多个数据库 (Cochrane,PubMed,Embase,Web of Science,CNKI) 进行全面的文献搜索,截至2023年8月30日.
- 包括开发或验证糖尿病预测模型对糖尿病前期风险的研究.
- 使用QUADAS-2工具进行偏差风险评估,并使用Stata和R软件对模型效应大小进行元分析.
主要成果:
- 在选了29375篇文章后,从24项研究中包括了20个模型.
- 确定了常见的预测因素:年龄,体重指数,糖尿病家族史,高血压史和体力活动.
- 模型性能显著异质;在79.2%的研究中报告了歧视,校准仅在4.2%,表明了方法上的差距.
结论:
- 当前的糖尿病预测模型在糖尿病前查时表现出不良的有效性和准确性.
- 糖尿病前期和糖尿病人群之间的代谢概况和临床特征的差异会影响模型的性能.
- 目前还没有推最佳模型;未来的研究应该提高对不同人群的临床相关性和预测准确性.
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