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五种不同的风险模型在初级预防指南中的影响
Maneesh Sud1,2,3,4, Atul Sivaswamy3, Peter C Austin2,3
1Schulich Heart Program, Sunnybrook Health Sciences Centre, University of Toronto, Canada.
概括
比较心血管疾病风险模型显示,像SCORE2这样的新工具可以更好地识别用于他类药物治疗的高风险患者. 然而,像弗雷明汉风险评分 (Framingham Risk Score) 这样的旧模型总体上可以防止更多事件发生.
科学领域:
- 心脏病学 心脏病学
- 预防医学 预防医学
- 健康 结果 研究 研究 结果
背景情况:
- 指南缺乏关于初级预防最佳心血管疾病 (CVD) 风险模型的共识.
- 风险分层对于像他类药物治疗这样的有针对性的干预措施至关重要.
研究的目的:
- 为了比较不同心血管疾病风险模型在初级预防中的有效性.
- 在模型中评估治疗所需数量 (NNT) 和预防事件数量 (NEP) 的潜在改进.
主要方法:
- 在加拿大安大略省 (2010-2014) 的47,399名初级保健患者 (40-75岁) 的回顾性分析.
- 使用弗雷明汉风险评分 (FRS),聚合队列方程 (PCE),重新校准的FRS (R-FRS),SCORE2和低风险地区重新校准的SCORE2 (LR-SCORE2) 的风险估计.
- 随访长达5年,以评估心血管疾病事件.
主要成果:
- SCORE2显示了他类药物治疗的最低NNT (40) 值,更有效地识别高风险患者.
- 弗雷明汉风险评分 (FRS) 具有最高的NNT (65),但导致了最高的预防事件数量 (NEP) (406).
- 像SCORE2这样的较新的模型,与FRS (34.6%) 相比,对较少的患者 (7.9%) 建议使用他类药物.
结论:
- 较新的风险模型,如SCORE2,可能会提高对高风险个体的他类药物的分配,以较低的NNT表示.
- 尽管针对性得到了改进,但这些新型模型可能会防止与传统模型相比,在人口层面上减少整体心血管事件.
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