[Surgical treatment of left main stenosis in coronary artery disease].
Bibliographic record
Abstract
OBJECTIVE: To study the efficacy of surgical treatment in the patients with left main stenosis of 50% or more. METHODS: Forty-two patients with left main stenosis (LMS) underwent coronary artery bypass grafting (CABG). Their mean age was 68.7 years. 16 patients had 50% to 75% LMS and 26 patients more than 75%. Twenty-nine patients had unstable angina. Seventeen patients with angina were in class III according to CCSS and 18 were in class IV. Preoperative left ventricular ejection fraction in 24 patients was beyond 50%. RESULTS: The mean preoperative hospital stay was 2.3 days. The mean number of grafts was 3.3 per patient. There was no operative death. The patients were all free from angina postoperatively. The mean follow up time was 42 (3 to approximately 78) months without death. CONCLUSIONS: Coronary artery bypass grafting is the first choice to treat left main stenosis. It is a safe and effective method. To determine properly the time of surgical intervention is helpful to reduce preoperative cardiac affairs and improve operative efficacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.006 | 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".