预测未来2型糖尿病和慢性病的方法:一个范围审查
Anna Bußmann1, Christian Speckemeier1, Alexandra Ehm2
1Essener Forschungsinstitut für Medizinmanagement (EsFoMed) GmbH, Essen, Germany.
PloS one
|June 11, 2025
概括
早期检测2型糖尿病和慢性病的高风险人群至关重要. 本综述汇集了包括机器学习在内的既定和新的预测方法,以帮助及时干预.
科学领域:
- 医学科学 医学科学 医学科学
- 公共卫生 公共卫生
- 预防医学 预防医学
背景情况:
- 由于人口结构的变化和生活方式的变化,二型糖尿病和慢性病的发病率不断上升.
- 在潜伏期的早期干预可以延迟或预防疾病发作.
- 准确的风险预测对于积极的医疗保健策略至关重要.
研究的目的:
- 对2型糖尿病和慢性病的各种风险预测方法进行范围审查.
- 识别和分类现有和新兴的疾病风险评估方法.
主要方法:
- 在主要数据库 (PubMed,Embase,Web of Science,Google Scholar) 进行全面的文献搜索.
- 主要文献和系统审查的系统审查,并通过针对性的谷歌搜索新方法来补充.
- 包括标准集中在风险预测方法,风险因素,目标人群和语言 (英语/德语) 上.
主要成果:
- 确定了许多预测方法,涵盖临床,生物 (血液,尿液,微生物组,遗传学) 和生活方式因素.
- 已建立的方法主要包括使用易于获得的参数进行风险调查.
- 新的方法包括透皮光学成像,面部血流分析和DNA甲基化数据.
结论:
- 该综述提供了对预测2型糖尿病和慢性病风险的工具的全面概述.
- 创新的方法,特别是那些利用机器学习的方法,正在与传统的风险调查一起出现.
- 对心代谢疾病的综合预测模型对高效的医疗保健提供有希望.
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