Antihypertensive drug classes and risk of incident dementia: a multinational population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin-II receptor blockers (ARBs) are first-line antihypertensive drugs for many patients, and influencing angiotensin systems may play a role in dementia risk. This study aimed to investigate whether exposure to different antihypertensive drug classes compared with ACEI affects the risk of dementia and pathological dementia subtypes in a large multinational database study. METHODS: This was a multinational population-based cohort study using electronic health databases in Hong Kong, the UK, Sweden and Australia. A common protocol was used to harmonise the study design. An active comparator, a new user design, was applied to compare the risk of all-cause dementia between different antihypertensive drug classes, with secondary outcomes of Alzheimer's disease (AD) and vascular dementia (VaD). Adjusted Cox proportional hazards models with inverse probability of treatment weighting were used to generate results in each study site and were pooled in meta-analysis. RESULTS: One million nine hundred twenty-five thousand, five hundred sixty-three individuals were included across the four databases with a median follow-up ranging from 5.6 to 8.4 years. Compared to ACEI, initiation with ARB was associated with a reduced risk of incident all-cause dementia [hazard ratio (HR): 0.92, 95% confidence interval (CI): 0.89-0.94] and VaD (HR 0.87, 95% CI 0.78-0.96) but not AD. CONCLUSIONS: This is the largest multinational cohort study conducted to date investigating different classes of antihypertensive drugs and the risk of incident dementia. When initiating antihypertensives, physicians and patients should consider the reduced risk of all-cause dementia and VaD with ARB compared with ACEI in their risk-benefit assessment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".