Effectiveness of percutaneous laser revascularization therapy for refractory angina
Bibliographic record
Abstract
Refractory angina is a debilitating disease characterized by persistent cardiac pain resistant to all conventional treatments for coronary artery disease. Percutaneous myocardial laser revascularization (PMLR) has been proposed to improve symptoms in these patients. We used meta-analysis to assess the effectiveness of PMLR versus optimal medical therapy for improving angina symptoms, health-related quality of life (HRQL), and exercise performance; the impact on all-cause mortality was also examined. Seven trials, involving a total of 1,213 participants were included. Our primary analyses showed that at 12-month follow-up, those who had received PMLR had ≥2 Canadian Cardiovascular Society class angina symptom reductions, OR 2.13 (95% CI, 1.22 to 3.73), as well as improvements in aspects of HRQL including angina frequency, SMD = 0.29 (95% CI, 0.05 to 0.52), disease perception, SMD = 0.37 (95% CI, 0.14 to 0.61), and physical limitations, SMD = 0.29 (95% CI, 0.05 to 0.53). PMLR had no significant impact on all-cause mortality. Our secondary analyses, in which we considered data from one trial that featured a higher-dose laser group, yielded no significant overall impact of PMLR across outcomes. While PMLR may be effective for improving angina symptoms and related burden, further work is needed to clarify appropriate dose and impact on disease-specific mortality and adverse cardiac events.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".