La posizione della Società Italiana di Cardiologia Invasiva (SICI-GISE) sulle indicazioni alla coronarografia nel paziente con angina stabile
Bibliographic record
Abstract
Available data suggest a steep increase in stable coronary artery disease with age. Its prevalence reaches a peak of almost 12-14% in men aged 65-84 years with an annual mortality ranging from 1.2% to 2.4%. The diagnosis of stable angina is primarily based on history and therefore relies on clinical judgment. In addition, its diagnosis can be extremely challenging because of the frequent transition from unstable to stable angina. Current European guidelines on the management of stable coronary artery disease give increased importance to the pre-test probability, which strongly affects the diagnostic algorithms. Imaging techniques play a greater role in the diagnosis of stable angina than in the past. Conversely, despite recent advances in technology and in the physiological assessment of coronary stenosis, an ever decreasing relevance is conferred to coronary angiography. Another difficult and controversial issue relates to the prognostic benefit of myocardial revascularization. The aim of this position paper is to review the most relevant clinical aspects of the European guidelines on the management of stable coronary artery disease.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".