Permeabilidade dos Bypass Aorto-Coronários - Experiência do Centro Hospitalar de Vila Nova de Gaia/Espinho
Bibliographic record
Abstract
Introduction: Coronary heart disease is the leading cause of death and disability in the U.S. and Europe.When significant, the coronary disease can be treated medically or surgically.The medical treatment is performed in the catheterization laboratory and consists in the re-permeabilization of the coronary arteries by percutaneous approach whereas the surgical myocardium revascularization consists in performing aorto-coronary bypass using arterial or venous conduits.Objective: This study is sought to assess the patency and longevity of bypass in patients requiring new catheterization after surgery for recurrence of ischemic heart disease and to evaluate its relationship with factors such as the type of bypass, cardiovascular risk factors and left ventricular ejection fraction.Methods: This study retrospectively analysed a sample of 260 surgically revascularized patients who required a new catheterization Hospital of Vila Nova de Gaia -Espinho between 2007 and 2012 for recurrence of ischemic heart disease.The degree of patency of the bypass was evaluated and sought a relationship with other variables such as gender, age, cardiovascular risk factors, left ventricular ejection fraction, the time interval between bypass surgery and the new catheterization. Results:The patency of the arterial bypass using the left internal mammary artery proved to be superior to the venous conduit bypass.There was no statistically significant relationship between the patency of the bypass, the cardiovascular risk factors and the left ventricle ejection fraction.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".