プライマリケアにおける一般的心血管リスクプロファイル: フレイミングハム心臓研究
Ralph B D'Agostino1, Ramachandran S Vasan, Michael J Pencina
1Boston University, Department of Mathematics and Statistics, 111 Cummington St, Boston, MA 02215, USA.
Circulation
|January 24, 2008
まとめ
新しい性別アルゴリズムは,全般的な動脈硬化性心血管疾患 (CVD) リスクと個々のイベントリスクを予測します. このツールは,リスクを定量化し,より良い心血管健康のための予防ケアをガイドするのに役立ちます.
科学分野:
- 心臓病学 心臓病学
- 予防医学は,予防的な医療です.
- エピデミオロジー エピデミオロジー
背景:
- 現在の慣行では,異なる動脈硬化性心血管疾患 (CVD) イベントに対して,別々のリスクアルゴリズムを使用しています.
- 総合的なCVDリスクとその構成要素を評価するには,統一されたアプローチが必要です.
研究 の 目的:
- 一般的なCVDリスクを予測するための,単一の,性別多変数リスクアルゴリズムを開発し,検証する.
- 冠動脈疾患,脳卒中,外周動脈疾患,心不全を含む個々のCVDイベントを予測するアルゴリズムの能力を評価する.
主な方法:
- 8491人のフレミングハム研究参加者のコックス比例リスク回帰分析.
- 伝統的な危険因子の含有:年齢,コレステロール,血圧,高血圧治療,喫煙,糖尿病の状態.
- 12年間にわたって一般的および特定のCVDイベントを予測するための性別のアルゴリズムの検証.
主要な成果:
- 開発された"一般的なCVD"アルゴリズムは,良好な予測性能を示した (C統計:男性0.763,女性0.793).
- 評価されたすべての伝統的なリスク要因は,CVDリスクを有意に予測した (P<0.0001).
- 単純な調整により,個々のCVDコンポーネントのリスクの推定が可能になりました.
結論:
- 性別固有の多変数アルゴリズムは,一般的なCVDリスクと個々のイベントリスクを効果的に評価します.
- このツールは,予防戦略を導くために,CVDイベントの絶対的な割合を定量化することができます.
- アルゴリズムは,臨床実務におけるリスク評価のための便利な方法を提供します.
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