Initial Clinical Experience With Extracorporeal Shock Wave Therapy in Treatment of Ischemic Heart Failure
Bibliographic record
Abstract
Previous experimental studies have suggested a beneficial effect of extracorporeal shock wave therapy (ESWT) in patients with ischemic heart failure. Twenty-four patients with ischemic heart failure and left ventricular ejection fraction (LVEF) <40% received ESWT in addition to their stable treatment. ESWT was performed in 9 sessions with 100 shocks per spot in viable segments detected by dobutamine stress echocardiography. Patients were evaluated at baseline and at 3 and 6 months after ESWT. Tc-99m MIBI single photon emission computed tomography was performed on inclusion and at 6 months. ESWT significantly decreased New York Heart Association class from 2.2±0.8 to 1.7±0.7 at 3 months (P<.01) and 6 months after ESWT (1.7±0.7). Six-minute walk test improved from 414±141 to 509±141 and 538±116 (P<.01) at 3 and 6 months, respectively. A steady decrease of Canadian Cardiovascular Society angina class from 2.6±0.7 to 2.1±0.8 and 1.9±0.7 (P<.01) at 3 and 6 months, respectively, was observed. A significant increase in LVEF at rest at 3 and 6 months after ESWT (from 32.2±6.0 to 34.8±9.6 and 37.7±9.5, P=.03, respectively) was noted. Summed rest score (from 23.9±8.1 to 21.4±7.1, P=.03) and stress score improvement (from 28.2±8.4 to 24.6±6.4, P=.04) by single photon emission computed tomography was registered. Significant clinical improvement accompanied by beneficial changes of LVEF and rest/stress perfusion was found after ESWT.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".