Enhanced External Counterpulsation Is Cost‐Effective in Reducing Hospital Costs in Refractory Angina Patients
Bibliographic record
Abstract
BACKGROUND: Enhanced external counterpulsation (EECP) is effective in the treatment of refractory angina, a condition suffered by 1.7 million Americans. Declining cardiovascular mortality and appropriate use criteria may further increase this number. HYPOTHESIS: EECP is hypothesized to be cost-effective in reducing hospitalizations in refractory angina patients. METHODS: The data used in this analysis were collected in phase II of the International EECP Patient Registry (IEPR-II). Data were collected on changes in Canadian Cardiovascular Society functional class, Duke Activity Status Index, and number of hospitalizations in the 6 months prior to EECP and in the 6- and 12-month intervals following EECP. Estimates of the changes in annual cost of all-cause hospitalization before and after EECP therapy were calculated by the product of the differences in hospitalization rates in the 6-month interval before and after EECP treatment and estimated hospitalization and physician charges after subtracting the average cost of EECP. RESULTS: Data for 1015 patients were analyzed. Hospitalization occurred in 55.2% of patients, an average of 1.7 ± 1.4 hospitalizations/patient, in the 6-month period before 35 hours of EECP; and in 24.4%, an average of 1.4 ± 1.0 hospitalizations/patient, during the 6- to 12-month period after EECP. The average hospitalization and physician charge in the US was $17,995, and the average EECP cost was $4880, yielding an annual cost savings/patient of $17,074. CONCLUSIONS: Treatment of refractory angina patients with EECP resulted in improvement in angina and functional class accompanied by a sustained reduction in health care costs over 1 year of follow-up.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".