Evaluation of extracorporeal shock wave therapy for refractory angina pectoris with quantitative analysis using cardiac magnetic resonance imaging: a short communication
Bibliographic record
Abstract
AIMS: There is a continuing search for new treatment options in patients who suffer from refractory angina pectoris to improve quality of life. Several studies have recently demonstrated promising results by stimulating angiogenesis using extracorporeal shockwave therapy in these patients. The purpose of this study is to quantitatively analyse the effect of extracorporeal shockwave therapy on myocardial perfusion in patients with refractory angina pectoris. METHODS: We included 15 patients with NYHA class 3-4 of whom 8 patients underwent baseline and follow-up cardiac magnetic resonance imaging (CMR). All patients received 9 shockwave treatments of their ischaemic zone over a period of 3 months. RESULTS: Quantitative analysis of myocardial perfusion using CMR revealed no significant improvement of myocardial perfusion after treatment (0.80 ± 0.22 vs 0.76 ± 0.31; p = 0.42). However, the total group of 15 patients did experience a significant improvement in NYHA class (p = 0.034) and reduction of nitroglycerin use (p = 0.012). CONCLUSION: Although treatment with extracorporeal shockwave was associated with an improvement in NYHA class, we could not observe an improvement in myocardial ischaemic zone and perfusion with CMR. To unravel the exact mechanisms of shockwave treatment, more in vitro and animal studies as well as larger (placebo-controlled) studies are required.
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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 | 0.001 |
| 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".