The efficacy and safety of enhanced external counterpulsation in patients with peripheral arterial disease
Bibliographic record
Abstract
Peripheral arterial disease (PAD) is common in patients with severe coronary artery disease (CAD) and is considered a relative contraindication to external enhanced counterpulsation (EECP), but there are no data that define the efficacy and safety of EECP in patients with PAD. The International EECP Patient Registry (IEPR) was used to compare initial post-therapy and 2-year follow-up clinical outcomes and adverse event rates in patients with and without PAD. From January 2002 to October 2004, 2126 patients were enrolled in the IEPR, of whom 493 (23%) had a history of PAD. Immediately following EECP, the reduction in angina (> or = 1 Canadian Cardiovascular Society class) was similar in patients with and without PAD (76.6% vs 79.0%, p = 0.27) as was improvement in the Duke Activity Score Index (DASI) score (+4.7% vs +6.1%, p < 0.001). Both angina reduction and DASI score improvement were sustained at 2 years. PAD patients discontinued EECP more frequently (12.0% vs 8.5%, p < 0.05), but lower extremity ulceration did not occur more frequently in patients with PAD (3.7% vs 2.7%, p = 0.26). Rates of death (17.1% vs 8.6%, p < 0.001) and myocardial infarction (9.5% vs 5.0%, p < 0.001) were, as expected, higher in patients with PAD compared to patients without PAD at 2 years. In conclusion, while PAD patients constitute a high-risk cohort with known higher adverse event rates, EECP led to similar short- and long-term improvements in angina and quality of life for individuals with PAD compared to those without PAD.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".