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Updated: Feb 28, 2026

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In Silico Clinical Trials for Cardiovascular Disease
Published on: May 27, 2022
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心血管研究中的多样性和代表性:证据差距,新兴模型和政策影响
Simran Grewal1, James Wildish2, Catherine Chalmers2
1Shoulder and Elbow Unit, Department of Orthopaedic Surgery, Onze Lieve Vrouwe Gasthuis, 1091 AC Amsterdam, The Netherlands.
International journal of environmental research and public health
|February 27, 2026
概括
心血管疾病 (CVD) 研究缺乏多样性,导致有偏见的数据和无效的全球指南. 整合多样化的数据集对于准确的CVD预测,诊断和治疗所有人群至关重要.
科学领域:
- 心血管研究的心血管研究.
- 卫生公平性健康公平性
- 基因组数据科学是基因组数据科学.
背景情况:
- 心血管疾病 (CVD) 是全球主要的死亡原因.
- 目前的心血管疾病研究依赖于同质的数据集,主要来自高收入国家的白人男性参与者.
- 这种缺乏多样性的结果是有偏见的证据,诊断准确度降低,发现的概括性有限.
研究的目的:
- 强调心血管数据多样性的科学必要性,以获得有效的,全球适用的知识.
- 为重塑心血管研究方法提出全球路线图.
- 倡导CVD研究和指导方针开发中的包容性实践.
主要方法:
- 讨论现有的科学文献和新兴的倡议.
- 分析数据同质性对心血管疾病研究结果的影响.
- 建议包括数据捐赠,包容性生物银行,公平的人工智能发展和国际政策变革在内的战略.
主要成果:
- 心血管疾病研究中的均质数据集导致有偏见的证据和不公平的健康结果.
- 整合各种数据对于准确的风险预测,诊断和治疗至关重要.
- 目前的研究实践限制了全球心血管疾病指南的有效性和通用性.
结论:
- 心血管数据的多样性是一个科学要求,而不仅仅是一个伦理考虑.
- 需要一个整合基因组学,数字健康和参与式研究的全球路线图.
- 实施包容性方法将确保心血管指南对所有人群有效,公平,公正.
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