Abstract 16624: Patients’ Perspectives on the Impact and Management of Angina - Preliminary Results of the PACT-ANGINA International Survey
Bibliographic record
Abstract
Introduction: PACT-ANGINA is a quality improvement initiative aimed to improve the understanding of challenges in the management of angina and chronic coronary syndromes. Hypothesis: An international patient survey is conducted to assess how angina and its management affect patients’ lives and what patients want in terms of the management of their angina. Methods: A working group that included 9 cardiologists and 7 patient representatives developed an online, anonymous questionnaire. Patients with angina were invited to take part in the survey by patient organizations and treating physicians. Results: Between January and June 2023, the survey was completed by 891 patients in 21 countries. The proportion of female patients was 46%. Among participants, 57% had been diagnosed with angina for 2 years or less, and 54% had never undergone a percutaneous coronary intervention. The proportion of patients with no history of smoking was 65% and the most common self-reported concomitant diseases were hypertension (49%), diabetes (38%) and dyslipidemia (23%). Pain, tightness, pressure or discomfort in the chest (89%), shortness of breath (44%), and fatigue (39%) were the most frequently reported symptoms, and 34% of participants felt that their physical activities were very or extremely limited by angina symptoms. The proportion of respondents who felt that angina was having a great or extreme impact on their quality of life was 37%. When asked to rate the relative importance of 9 treatment objectives, respondents assigned the highest priority to 1) reducing angina attacks and symptoms, 2) avoiding hospitalizations, and 3) prolonging their life as much as possible. Among different aspects of care, those considered the most important by respondents to improve the management of their angina were 1) a better follow-up of their symptoms, 2) practical and easy-to-understand information, and 3) lifestyle changes counseling. Conclusions: This study demonstrates that patients with angina are often limited by their symptoms, which impact their quality of life. Patient-centered management of angina is necessary to improve clinical care of such a common cardiac condition.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".