Coronary endarterectomy in patients with diffuse coronary artery disease: assessment of graft patency with computed tomography angiography
Bibliographic record
Abstract
BACKGROUND: With a growing population of patients with advanced coronary artery disease (CAD), many of whom have undergone prior percutaneous coronary interventions, coronary endarterectomy (CE) allows for the extension of revascularization in patients with otherwise limited options. Whether adjunctive CE associated with standard surgery, combined with contemporary antiplatelet therapy, improves outcomes remains largely unknown. METHODS: We studied 147 consecutive patients who underwent 154 adjunctive CE procedures for advanced CAD between January 2015 and January 2018. We used computed tomography angiography (CTA) in a subgroup of 32 consecutive patients who underwent CE during coronary artery bypass grafting after June 2016 to assess graft and coronary patency. RESULTS: Patients (mean age 67 ± SD 10 yr) underwent CE of the right (102 patients), the left anterior descending (LAD, 22 patients) and the circumflex (17 patients) coronary arteries. Seven patients (5%) experienced a procedural myocardial infarction and there were no perioperative deaths. Among the 32 patients who underwent CTA 3 months after surgery, the mean patency of the endarterectomized coronary arteries and bypass grafts was 90% and 88%, respectively. All 6 arterial grafts on the LAD artery were patent. The mean survival rate and the mean rate of freedom from major adverse cardiovascular events was 95% ± 2% and 95% ± 6%, respectively. The patency rate was 100 % for patients evaluated at 3-year follow up. CONCLUSION: Coronary endarterectomy offers a surgical option for patients with diffuse CAD who may be unsuitable for coronary bypass alone. Grafts and endarterectomized coronary artery patency remain adequate and explain the excellent patient survival and the freedom rate from major adverse cardiovascular events.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".