European Society of Cardiology Chronic Coronary Syndromes Guidelines Review
Bibliographic record
Abstract
New guidelines for the diagnosis and management of chronic coronary syndromes (CCS)1were released during the 2019 European Society of Cardiology (ESC) Congress. The new guidelines were discussed in multiple sessions with different formats across the congress; this review summarises some of the discussion among experts at the congress around what the new guidelines mean for the way they manage their patients with respect to antithrombotic treatment. A significant change in the new guidelines versus previous guidelines published in 20132is an update in nomenclature from ‘stable’ coronary artery disease (CAD) to chronic coronary syndromes, to reflect the fact that patients with CCS are at continuous risk of heart attacks, strokes, and death. This highlights the need for effective preventive therapy to protect against these thrombotic events and maintain a state of relative stability in patients with CCS. To this end, a new recommendation in the 2019 guidelines is to consider intensification of antithrombotic therapy, using aspirin plus another antithrombotic agent, to provide enhanced long-term protection for patients with CCS at high risk of ischaemic events. This review places the new guideline recommendations in clinical perspective, including thorough presentations of case studies to illustrate how patients at greatest risk of ischaemic events can be identified, and treatment stratified accordingly. These case studies highlight the role of dual pathway inhibition (DPI) in managing CCS patients with the greatest need for cardiovascular protection, who are likely to derive the greatest benefit from this treatment strategy.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.010 |
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".