In the present study we investigate overall population effects on episodic memory of an intervention over 15 years that reduces systolic blood pressure in individuals with hypertension. A limitation with previous research on the potential risk reduction of such interventions is that they do not properly account for the reduction of mortality rates. Hence, one can only speculate whether the effect is due to changes in memory or changes in mortality. Therefore, we extend previous research by providing both an etiological and a prognostic effect estimate. To do this, we propose a Bayesian semi-parametric estimation approach for an incremental threshold intervention, using the extended G-formula. Additionally, we introduce a novel sparsity-inducing Dirichlet hyperprior for longitudinal data, that exploits the longitudinal structure of the data. We demonstrate the usefulness of our approach in simulations, and compare its performance to other Bayesian decision tree ensemble approaches. In our analysis of the data from the Betula cohort, we found no significant prognostic or etiological effects across all ages. This suggests that systolic blood pressure interventions likely do not strongly affect memory, whether at the overall population level or in the population that would survive under both the natural course and the intervention (the always survivor stratum).

翻译：本研究探讨了针对高血压患者实施为期15年的收缩压降低干预对群体情景记忆的总体影响。既往关于此类干预潜在风险降低效果的研究存在局限性，即未能充分考虑死亡率下降的影响。因此，我们只能推测其效应是源于记忆改变还是死亡率变化。为此，我们通过提供病因学与预后效应双重估计来拓展既往研究。我们提出采用广义G公式的贝叶斯半参数估计方法，用于渐进阈值干预分析。同时，我们引入一种新型的纵向数据稀疏诱导狄利克雷超先验分布，以充分挖掘数据的纵向结构特征。通过模拟实验验证了该方法的有效性，并将其性能与其他贝叶斯决策树集成方法进行了比较。在对Betula队列数据的分析中，我们发现所有年龄段均未表现出显著的预后或病因学效应。这表明收缩压干预可能并不会对记忆产生强烈影响——无论是在总体人群层面，还是在自然进程与干预条件下均能存活的"始终存活者"亚群中。