Cardiovascular disease in the elderly: proceedings of the European Society of Cardiology—Cardiovascular Round Table
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The growing elderly population worldwide represents a major challenge for caregivers, healthcare providers, and society. Older patients have a higher prevalence of cardiovascular (CV) disease, high rates of CV risk factors, and multiple age-related comorbidities. Although prevention and management strategies have been shown to be effective in older people, they continue to be under-used, and under-studied. In addition to hard endpoints, frailty, cognitive impairments, and patients' re-assessment of important outcomes (e.g. quality of life vs. longevity) are important aspects for older patients and emphasize the need to include a substantial proportion of older patients in CV clinical trials. To complement the often skewed age distribution in clinical trials, greater emphasis should be placed on real-world studies to assess longer-term outcomes, especially safety and quality of life outcomes. In the complex environment of the older patient, a multidisciplinary care team approach with the involvement of the individual patient in the decision-making process can help optimize prevention and management strategies. This article aims to demonstrate the growing burden of ageing in real life and illustrates the need to continue primary prevention to address CV risk factors. It summarizes factors to consider when choosing pharmacological and interventional treatments for the elderly and the need to consider quality of life and patient priorities when making decisions.
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.
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 | 0.091 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it