Antihypertensive Treatment is associated with MRI-Derived Markers of Neurodegeneration and Impaired Cognition: A Propensity-Weighted Cohort Study
Bibliographic record
Abstract
BACKGROUND: Hypertension is an important risk factor for Alzheimer's disease (AD) and cerebral small vessel disease. Angiotensin converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) are common anti-hypertensive treatments, but have differential effects on cortical amyloid. OBJECTIVE: The objective of this study was to evaluate associations between anti-hypertensive treatment, brain volume, and cognition, using a propensity-weighted analysis to account for confounding by indication. METHODS: We identified a cohort of normal elderly adults and individuals with mild cognitive impairment (MCI) or AD (N = 886; mean age = 75.0) from the Alzheimer's Disease Neuroimaging Initiative. Primary outcomes were brain parenchymal fraction, total hippocampal volume, and white matter hyperintensity (WMH) volume. Secondary outcomes were standardized scores on neuropsychological tests. Propensity-weighted adjusted multivariate linear regression was used to estimate associations between anti-hypertensive treatment class and MRI volumes and cognition. RESULTS: Individuals treated with ARBs showed larger hippocampal volumes (R2 = 0.83, p = 0.05) and brain parenchymal fraction (R2 = 0.83, p = 0.01) than those treated with ACEIs. When stratified by diagnosis, this effect remained only in normal elderly adults and MCI patients, and a significant association between ARBs and lower WMH volume (R2 = 0.83, p = 0.03) emerged for AD patients only. ARBs were also associated with significantly better performance on tests of episodic and verbal memory, language, and executive function (all p < 0.05). CONCLUSIONS: Findings are consistent with evidence for a neuroprotective effect of treatment with ARBs for brain structure and cognition. This study has potential implications for the treatment of hypertension, particularly in elderly adults at risk of cognitive decline and AD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".