Standard cardiovascular risk calculators, including the Framingham Risk Score and the ACC/AHA Pooled Cohort Equations, estimate the conditional probability P(CHD | SysBP = s) rather than the interventional quantity P(CHD | do(SysBP = s)). When confounding is present, this distinction has direct clinical consequences: observational estimates may systematically overstate the absolute benefit of antihypertensive treatment. We applied Pearl's do-calculus to the Framingham Heart Study Offspring Cohort (n = 4,240; primary analysis on 3,776 complete cases; 574 ten-year coronary heart disease events). A structurally corrected directed acyclic graph (DAG) was specified and evaluated using conditional independence testing. The average causal effect (ACE) of a 20 mmHg systolic blood pressure reduction was estimated by g-computation with bootstrap confidence intervals, corroborated by propensity score matching and inverse probability weighting. G-computation yielded an ACE of 3.40 percent absolute risk reduction (95 percent CI: 2.64 to 4.14), compared with a naive observational estimate of 4.14 percent, corresponding to an approximate 21.8 percent relative overestimation. Conditional average treatment effects were estimated using R-Learner and T-Learner metalearners. These findings suggest that observational cardiovascular risk tools may overestimate the absolute benefit of blood pressure reduction, with implications for clinical risk stratification and prescribing thresholds.

翻译：标准心血管风险计算工具（包括Framingham风险评分与ACC/AHA联合队列方程）估算的是条件概率P(CHD | SysBP = s)，而非干预性量值P(CHD | do(SysBP = s))。在存在混杂因素的情况下，这一区别具有直接临床意义：观察性估计可能系统性高估降压治疗的绝对获益。我们将Pearl的do-演算应用于Framingham心脏研究后代队列（n=4,240；主分析包含3,776例完整病例；574例十年冠心病事件）。通过条件独立性检验指定并评估了结构校正有向无环图（DAG）。采用g-计算结合bootstrap置信区间估计收缩压降低20 mmHg的平均因果效应（ACE），并通过倾向性评分匹配和逆概率加权予以验证。g-计算得出的ACE为3.40%绝对风险降低（95%置信区间：2.64-4.14），而朴素观察性估计值为4.14%，对应约21.8%的相对高估。采用R-Learner和T-Learner元学习器估计条件平均处理效应。研究结果表明，观察性心血管风险工具可能高估降压治疗的绝对获益，对临床风险分层与药物阈值设定具有启示意义。