P2682Long-term effects of enhanced external counterpulsation treatment on symptom burden, usage of nitrates, physical capacity and health-related quality of life in patients with refractory angina pectoris
Bibliographic record
Abstract
Abstract Background Patients with refractory angina pectoris (RAP) suffer from debilitating symptoms with considerable limitation of functional capacity and impaired health-related quality of life (HRQoL) despite optimized medical therapy. Recurrent angina symptoms are strongly associated with psychological distress and cardiac anxiety (i.e., a subtype of anxiety related to cardiac sensations). Enhanced external counterpulsation (EECP) is an alternative non-invasive treatment for these patients. An EECP course includes 35 1-hour sessions over 7 weeks. No previous study has explored long-term EECP effects on cardiac anxiety in patients with RAP. Objective To evaluate the effects of EECP treatment in patients with RAP regarding usage of nitrates, physical capacity, cardiac anxiety and HRQoL. Methods A quasi experimental design with long-term follow-up (6 months) involving 50 patients (men=37, 47–91 years) who had finished one course of EECP. Assessment of average use of nitrates, six-minute walk test, functional class with Canadian Cardiovascular Society (CCS) classification and questionnaires for cardiac anxiety and HRQoL were collected pre and post treatment. In addition, the questionnaires were collected 6 months after completion of EECP. Results Patients used significantly less nitrates (p<0.001) compared to at the start of treatment. They enhanced the walking distance on average by 46 m after EECP (p<0.001) and CCS class also improved (p<0.001). All subscales except for one in cardiac anxiety were significantly reduced (p<0.05). All dimensions in HRQoL improved significantly (p<0.01). The positive effects in both cardiac anxiety and HRQoL were maintained 6 months after the treatment. Conclusions Patients with RAP received beneficial effects from EECP. Reduced symptom burden and improved physical capacity enable engagement in physical activities. Furthermore, less cardiac anxiety and improved HRQoL may enhance life satisfaction for these patients. EECP treatment should be considered to a greater extent to improve the life situation for these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".