The Relation Between Arterial Hypertension and Cognitive Impairment: A Literature Review
Bibliographic record
Abstract
The global increase in dementia cases, driven by improved life expectancy and reduced elderly mortality rates, presents a significant public health challenge. Dementia, characterized by a gradual and irreversible decline in cognitive abilities, affects individuals aged 65 and older, disrupting lives and straining healthcare systems. Hypertension significantly influences dementia development. Research consistently links midlife hypertension to cognitive decline, mild cognitive impairment (MCI), and dementia, but findings in older adults vary. While some studies suggest that late-life hypertension accelerates cognitive decline and dementia risk, others propose a protective effect. The impact of hypertension on cognition varies across age groups, spanning from childhood to late life. High blood pressure during midlife and earlier life stages consistently predicts poorer cognitive outcomes. Executive function, attention, and motor speed are the cognitive domains most affected by hypertension, particularly in subcortical diseases. Memory impairments in hypertension-related dementias are complex, often overlapping with other causes. Understanding the inconsistent findings in older adults regarding hypertension, cognitive decline, and dementia risk requires comprehensive exploration of methodological and biological factors. Addressing hypertension and its management may hold the key to reducing the risk of cognitive decline and dementia, especially in midlife and earlier life stages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".