Single centre analysis of revascularization strategy in Newfoundland and Labrador multivessel disease patients
Bibliographic record
Abstract
Background: Coronary artery disease (CAD) can be managed with Percutaneous Coronary Intervention (PCI) or Coronary Artery Bypass Grafting (CABG). Management of subtypes of CAD, including Multivessel Disease (MVD) and isolated Left Main Coronary Artery (LMCA) disease, continue to evolve in the literature. An observational registry may provide implications for management of CAD. Methods: All isolated LMCA and triple-vessel disease patients who received either PCI or CABG in Newfoundland & Labrador (NL) were analyzed in two separate studies. The first study evaluated isolated LMCA patients for freedom from Major Adverse Cardiac Events (MACE). The second study evaluated triple vessel disease patients for in-hospital mortality post revascularization. Results: Firstly, 115 patients with isolated LMCA disease (n=7 PCI, n=99 CABG, n=9 medical management) were identified from May 2006 to October 2015. The rate of MACE at 1 year was 5.1% in the CABG cohort. Secondly, a total of 1604 triple vessel disease patients (n=45 PCI, n=1559 CABG) were analyzed with a median follow up of 5.4 years. The in-hospital mortality rate was 2.2% and 1.2% in the PCI and CABG cohorts, respectively (p=0.533). Conclusion: CABG represented the most common revascularization strategy for both study populations. Freedom from MACE at one year in the CABG isolated LMCA patients was comparable to the literature. Early survival rates were comparable in low-risk triple vessel disease patients revascularized with either therapy and further evaluation is warranted to account for an increasing number of this population being revascularized via PCI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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 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".