Pulsatile hemodynamics and cardiovascular risk factors in very old patients
Bibliographic record
Abstract
BACKGROUND: In the nineteenth century, prior to the introduction of the cuff sphygmomanometer, stiffening of arteries was recognized as an indicator of vascular ageing and cardiovascular risk. Through the twentieth century, views on vascular ageing came to focus on brachial blood pressures and on occlusive atherosclerotic disease. Such focus deflected attention from primary ageing changes, represented by stiffening and dilation of the proximal aorta. AIM: This review emphasizes the cushioning function of elastic arteries, principally the aorta, now when life expectancy largely exceeds 80 years providing new challenges for medical treatment in the very old. METHODS AND RESULTS: First, life expectancy has increased significantly for both sexes and is particularly prolonged after menopause. Second, phenotypic changes are noticed such as that the age-related increase of waist circumference and hyperlipidemia is markedly slowed, whereas the concomitant rise in C-reactive protein is enhanced and hyperglycaemia develops in many patients. Third, the systolic, diastolic and pulse pressures rise with age is attenuated or even stopped, as is the degree of arterial stiffness. Finally, in very old patients, the main causes of death are cardiovascular, including cardiac deaths, which differ markedly by causation in men (due to lowered ejection fraction) and women (due to arrhythmia disorders). Deaths associated with renal impairment are observed in both sexes. CONCLUSION: No simple linear relationships exist between all these phenotypic variables and the ageing process. Treatment goals of hypertension and diabetes mellitus remain difficult to predict from such data. Prevention of cardiovascular risk in the very old is thus influenced by limited evidence and important ethical considerations.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".