Evaluation of Transmyocardial Laser Revascularization by Following Objective Parameters of Perfusion and Ventricular Function1
Bibliographic record
Abstract
BACKGROUND: Does transmyocardial laser revascularization (TMLR), a new surgical technique for treating patients with otherwise intractable angina pectoris, improve myocardial perfusion, metabolism, and, consequently, function? METHODS: Patients referred for TMLR, alone or with coronary artery bypass grafting (CABG), were preoperatively evaluated clinically and by treadmill stress testing, echocardiography, ventriculography, radionuclide assessment of perfusion and metabolism, and hemodynamic assessment. Intraoperatively it was decided that some patients only required CABG. Follow-up evaluations were repeated after 6 (n = 40) and 12 months (n = 23) and compared with preoperative values. RESULTS: CABG only was performed in 35 cases, TMLR + CABG in 17, TMLR only in 45. 1-year mortality was 11% in the TMLR, zero in the TMLR + CABG, and 11% in the CABG groups. In all groups a significantly improved CCS angina- and NYHA class was observed immediately after operation and after 6 and 12 months. In all study groups treadmill tolerance (p<0.05) improved, but regional and global function, perfusion at rest, and metabolism were not significantly changed at 6 and 12-months follow-ups. Perfusion studies under stress demonstrated an improvement only in the CABG group after 12 months (p<0.05), whereas in both TMLR groups the lasered ischemic segments remained unchanged. CONCLUSIONS: TMLR significantly improves long-term clinical status and treadmill stress tolerance, but appears to have little if any effect upon regional and global function, perfusion, and metabolism.
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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 | 0.000 | 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) | 0.002 | 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".