IMPACT OF SEX AND ANTIHYPERTENSIVE MEDICATION ON GLOBAL COGNITION IN PRIMARY CARE OLDER ADULTS
Bibliographic record
Abstract
Abstract Hypertension is one of the strongest modifiable risk factors for the development of cognitive impairment and dementia. However, there are conflicting reports regarding which class of antihypertensive medication is the best for reducing the risk of cognitive decline. The objective of this study is to determine whether sex determines the pharmacological therapy that is the most effective in preserving cognitive outcomes. This study examined 1607 participants from the ESA Services Study, a longitudinal survey of older adults over 65 years old in Quebec-Canada. They were examined for the Mini-Mental State Examination(MMSE) at baseline (T1) and followed up three (T2) and four years after (T3). Hypertensive women had the highest mean MMSE score at each time point (T1 28.591 (SE .064); T2 28.282 (SE .118); T3 28.524 (SE.119)), while hypertensive men had the worst (T1 28.038(SE.070); T2 27.694(SE.125); 27.809(SE.128)). Women taking angiotensin II receptor antagonists (ARBs) showed the highest MMSE scores (p<.003), and men taking diuretics and other antihypertensives had the lowest MMSE scores(p<.001) after a 3-year follow-up. Combination therapy of two or three antihypertensives drugs was associated with higher scores in women at T1 and T2 (p<.001). In men, taking three antihypertensives showed a sharp decrease in MMSE scores from T1 to T3 (p<.001). Sex differences in global cognition outcomes in older adults are in part due to the heterogeneity in effects related to the type and number of antihypertensive drugs used. Effective antihypertensive treatment should consider the impact of sex to optimize the effect of pharmacological interventions on cognition.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".