Acute Hemodynamic Effects and Angina Improvement with Enhanced External Counterpulsation
Bibliographic record
Abstract
Enhanced external counterpulsation (EECP) is an effective noninvasive treatment for coronary artery disease. The mechanism of action is felt to be hemodynamic. The complex hemodynamic effects have been simply quantified by calculating a previously described effectiveness ratio (ER). The EECP Clinical Consortium, a clinical registry of 37 centers, prospectively enrolled 395 chronic stable angina patients (79 women, 316 men, mean age 66 years) to examine the relation of the ER to posttreatment improvement in Canadian Cardiovascular Society angina class (CCS). Women and the elderly underwent planned subgroup analysis. The ER was calculated during the first and last hours of a 35-hour course of EECP treatment. After EECP, CCS improved by at least 1 class in 88% of patients, 87% of men and 92% of women (p = NS), and in 89% of patients < or = 66 years and 88% of patients > 66 years old (p = NS). The initial and final ER were similar in patients with and without improvement in CCS. Significant first-hour ER differences were seen between men and women (0.96 +/- 0.03 vs 0.76 +/- 0.04, p<0.005), and between ages < or = 66 and > 66 years old (1.04 +/- 0.04 vs 0.81 +/- 0.03, p<0.0001). However, all subgroups responded equally well to EECP treatment. EECP is effective in improving CCS in chronic stable angina patients; it has comparable effects in men and women and across a broad range of ages. The hemodynamic effect of EECP (ER) does not predict improvement in CCS and may indicate that other factors, such as neurohormonal changes, may have a significant role in mediating the observed EECP benefits.
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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 | 0.005 |
| 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".