[Preoperative expectations and clinical outcome of transmyocardial laser treatment in patients with angina pectoris].
Bibliographic record
Abstract
BACKGROUND: The aims of this study were to evaluate the effect of transmyocardial laser treatment on quality of life and to assess the correlation between preoperative expectations and clinical improvement after one year. MATERIAL AND METHODS: 13 patients (median age 56 years) with disabling angina pectoris were subjected to transmyocardial holmium: YAG laser. Quality of life was assessed preoperatively and at three and 12 months by Hospital Anxiety and Depression Scale (HAD), Physical Symptom Distress Index (PSDI) and Life Satisfaction Index (LSI). Expectations were evaluated by Leedham's scale. RESULTS: A significant improvement in Canadian Cardiovascular Society Score (CCS) from 3.4 +/- 0.5 (mean +/- SD) preoperatively to 1.6 +/- 1.0 and 1.7 +/- 0.8 three and 12 months after treatment was observed (p < 0.01). Quality of life (PSDI and LSI) improved. No significant changes in ejection fraction or exercise performance were found. Preoperative expectations were generally high, but did not correlate significantly with improvements in CCS or quality of life. INTERPRETATION: Although no changes in objective parameters were found, the lack of significant correlations between preoperative expectation and subjective clinical improvement indicate that the improvement of angina pectoris only partly can be explained by placebo effects.
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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) | 0.001 | 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".