Echo-guided extracorporeal shock wave therapy for refractory angina improves regional myocardial blood flow as assessed by PET imaging
Bibliographic record
Abstract
Purpose: Low-intensity extracorporeal shock wave (SW) therapy (SWT) has been shown to improve symptoms and exercise tolerance in patients (pts.) with coronary artery disease (CAD) not suitable for conventional revascularization strategies. Induction of neovascularization and improvement of myocardial perfusion are mechanisms hypothetized to be involved. Methods: 43 pts. with advanced CAD (mean age 67±10 years) not suitable for catheter-based or surgical revascularization were suffering from severe stable angina pectoris (CCS class III or IV) refractory to individually optimized medical treatment underwent a series of 9 echocardiography-targeted SW applications (3 SW applications/week during weeks 1, 5, and 9). The antero-septal wall (LAD territory) was targeted in 19, the lateral wall (RCX territory) in 18, and the inferior wall (RCA territory) in 6 pts. A series of 300-500 shock waves was applied per session. Anti-anginal medication (combination of 2 or 3 drugs) was kept unchanged. Regional myocardial blood flow (MBF) was measured quantitatively by NH3-PET at baseline and 4-6 weeks after completion of SWT. Results: Complications of SWT did not occur, markers of myocardial cell damage were all negative during SWT. At follow-up, 30 pts. (64%) reported improvement of angina to a tolerable level. CCS angina class decreased from 3.1±0.6 to 2.5±0.6 (p<0.0001). Maximum ergometric workload increased from 78±53 to 90±46 watts (p=0.04). MBF in the LV region targeted by SWT improved from 119+42 mL/min/100g at baseline to 129±48 mL/min/100g at follow up (p=0.047), while there was no change in the opposite wall (136±52 vs. 137±53 ml/min/100g; p=0.9). Conclusions: SWT improves symptoms in a sizeable number of pts. with chronic refractory angina. Regional improvement of MBF in the region targeted by SWT was also documented by PET imaging. Additional studies are warranted to clarify the role of SWT in the armamentarium for this challenging patient group.
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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 | 0.000 |
| 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".