The effects of blood pressure lowering on development of cognitive impairment and dementia in patients without apparent prior cerebrovascular disease

Inferring Personalized Treatment Effect of Antihypertensives on Alzheimer's Disease Using Deep Learning

Alzheimer's disease (AD) is one of the leading causes of death in the United States, especially among the elderly. Recent studies have shown how hypertension is related to cognitive decline in elderly patients, which in turn leads to increased mortality as well as morbidity. There have been various studies that have looked at the effect of antihypertensive drugs in reducing cognitive decline, and their results have proved inconclusive. However, most of these studies assume the treatment effect is similar for all patients, thus considering only the average treatment effects of antihypertensive drugs. In this paper, we assume that the effect of antihypertensives on the onset of AD depends on patient characteristics. We develop a deep learning method called LASSO-Dragonnet to estimate the individualized treatment effects of each patient. We considered six antihypertensive drugs, and each of the six models considered one of the drugs as the treatment and the remaining as control. Our studies showed that although many antihypertensives have a positive impact in delaying AD onset on average, the impact varies from individual to individual, depending on their various characteristics. We also analyzed the importance of various covariates in such an estimation. Our results showed that the individualized treatment effects of each patient could be estimated accurately using a deep learning method, and that the importance of various covariates could be determined.

Midlife Risk Factors for Impaired Physical and Cognitive Functioning at Older Ages: A Cohort Study

Background:

Previous studies examined midlife risk factors separately for old-age impaired physical and cognitive functioning. We determined the overlap of risk factors for both domains of functioning within the same setting.

Methods:

Biological and behavioral risk factors at age 50 years and cognitive and physical functioning were assessed 18 (SD = 5) years later in the Whitehall II study (N = 6,316). Impaired physical functioning was defined as ≥1 limitation on the activities of daily living scale. Impaired cognitive functioning was defined as Mini-Mental State Examination score <27. Two statistical analyses were employed: minimally adjusted analysis (for age, sex, and ethnicity) and mutually adjusted analysis (including all risk factors). Missing data on risk factors were imputed.

Results:

After confounder adjustment, impaired physical and cognitive functioning at older ages were predicted by hypertension (odds ratios [ORs] 1.80 95% confidence interval [CI] 1.39–2.33 and 1.57 95% CI 1.07–2.31, respectively), poor lung function (1.51 95% CI 1.28–1.78 and 1.31 95% CI 1.08–1.59), and physical inactivity, marginally in the case of cognitive function (1.50 95% CI 1.19–1.90 and 1.27 95% CI 0.99–1.62) at age 50 years. Impaired physical functioning but not cognitive functioning was additionally predicted by depression and higher body mass index (1.72 95% CI 1.46–2.03 and 1.29 95% CI 1.16–1.44, respectively).

Conclusions:

Several midlife risk factors are associated with impaired physical and cognitive functioning in old age, supporting a unified prevention policy. Analysis of 12 risk factors at age 50 suggests that strategies targeting physical inactivity, hypertension, and poor lung function will reduce impairments in both cognitive and physical functioning in old age.