Multidisciplinary Heart Team Approach for Complex Coronary Artery Disease: Single Center Clinical Presentation
Bibliographic record
Abstract
Background The Heart Team approach is ascribed a Class I recommendation in contemporary guidelines for revascularization of complex coronary artery disease. However, limited data are available regarding the decision-making and outcomes of patients based on this strategy. Methods and Results One hundred sixty-six high-risk coronary artery disease patients underwent Heart Team evaluation at a single institution between January 2015 and November 2018. We prospectively collected data on demographics, symptoms, Society of Thoracic Surgeons Predicted Risk of Mortality/Synergy Between PCI with Taxus and Cardiac Surgery (STS-PROM/SYNTAX) scores, mode of revascularization, and outcomes. Mean age was 70.0 years; 122 (73.5%) patients were male. Prevalent comorbidities included diabetes mellitus (51.8%), peripheral artery disease (38.6%), atrial fibrillation (27.1%), end-stage renal disease on dialysis (13.3%), and chronic obstructive pulmonary disease (21.7%). Eighty-seven (52.4%) patients had New York Heart Association III-IV and 112 (67.5%) had Canadian Cardiovascular Society III-IV symptomatology. Sixty-seven (40.4%) patients had left main and 118 (71.1%) had 3-vessel coronary artery disease. The median STS-PROM was 3.6% (interquartile range 1.9, 8.0) and SYNTAX score was 26 (interquartile range 20, 34). The median number of physicians per Heart Team meeting was 6 (interquartile range 5, 8). Seventy-nine (47.6%) and 49 (29.5%) patients underwent percutaneous coronary intervention and coronary artery bypass grafting, respectively. With increasing STS-PROM (low, intermediate, high operative risk), coronary artery bypass graft was performed less often (47.9%, 18.5%, 15.2%) and optimal medical therapy was recommended more often (11.3%, 18.5%, 30.3%). There were no trends in recommendation for coronary artery bypass graft, percutaneous coronary intervention, or optimal medical therapy by SYNTAX score tertiles. In-hospital and 30-day mortality was 3.9% and 4.8%, respectively. Conclusions Integrating a multidisciplinary Heart Team into institutional practice is feasible and provides a formalized approach to evaluating complex coronary artery disease patients. The comprehensive assessment of surgical, anatomical, and other risk scores using a decision aid may guide appropriate, evidence-based management within this team-based construct.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".