World Heart Federation Cholesterol Roadmap: The Portuguese case
Bibliographic record
Abstract
Atherosclerotic cardiovascular disease (ASCVD) remains the major cause of premature death and disability; effective cardiovascular (CV) risk prevention is fundamental. The World Heart Federation (WHF) Cholesterol Roadmap provides a framework for national policy development and aims to achieve ASCVD prevention. At the invitation of the WHF, a group of experts from the Portuguese Society of Cardiology (SPC), addressed the cholesterol burden at nationally and discussed possible strategies to include in a Portuguese cholesterol roadmap. The literature review showed that the cholesterol burden in Portugal is high and especially uncontrolled in those with the highest CV risk. An infographic scorecard was built to include in the WHF collection, for a clear idea about CV risk and cholesterol burden in Portugal, which would also be useful for health policy advocacy. The expert discussion and preventive strategies proposal followed the five pillars of the WHF document: awareness improvement; population-based approaches for CV risk and cholesterol; risk assessment/population screening; system-level approaches; surveillance of cholesterol and ASCVD outcomes. These strategies were debated by all the expert participants, with the goal of creating a national cholesterol roadmap to be used for advocacy and as a guide for CV prevention. Several key recommendations were outlined: include all stakeholders in a multidisciplinary national program; create a structured activities plan to increase awareness in the population; improve the quality of continuous CV health education; increase the interaction between different health professionals and non-health professionals; increment the referral of patients to cardiac rehabilitation; screen cholesterol levels in the general population, especially high-risk groups; promote patient self-care, engage with patients' associations; use specific social networks to spread information widely; create a national database of cholesterol levels with systematic registry of CV events; redefine strategies based on the evaluation of results; create and involve more patients' associations - invert the pyramid order. In conclusion, ASCVD and the cholesterol burden remain a strong global issue in Portugal, requiring the involvement of multiple stakeholders in prevention. The Portuguese cholesterol roadmap can provide some solutions to help urgently mitigate the problem. Population-based approaches to improve awareness and CV risk assessment and surveillance of cholesterol and ASCVD outcomes are key factors in this change. A call to action is clearly needed to fight hypercholesterolemia and ASCVD burden.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".