Heart team discussion in managing patients with coronary artery disease: outcome and reproducibility
Bibliographic record
Abstract
Recent ESC/EACTS revascularization guidelines advocate a 'Heart Team' (HT) approach in the decision-making process when managing patients with coronary disease. We prospectively assessed HT decision-making in 150 patients analysing personnel attendance, data presented, the 'actioning' of the HT decision and, if not completed, then the reasons why. Additionally, 50 patients were specifically re-discussed after 1 year in order to assess consistency in decision-making. We have two HT meetings each week. At least one surgeon, interventional cardiologist and non-interventional cardiologist were present at all meetings. Data presented included patient demographics, symptoms, co-morbidities, coronary angiography, left ventricular function and other relevant investigations, e.g. echocardiograms. HT decisions included continued medical treatment (22%), percutaneous coronary intervention (PCI; 22%), coronary-artery bypass grafting (CABG; 34%) or further investigations such as pressure wire studies, dobutamine stress echo or cardiac magnetic resonance imaging (22%). These decisions were fully undertaken in 86% of patients. Reasons for aberration in the remaining 21 patients included patient refusal (CABG 29%, PCI 10%) and further co-morbidities (28%). On re-discussion of the same patient data (n = 50) a year later, 24% of decisions differed from the original HT recommendations reflecting the fact that, for certain coronary artery disease pattern, either CABG or PCI could be appropriate.
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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 | 0.092 | 0.314 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".