Patients’ perception of health status and ischaemic burden in stable coronary artery disease
Bibliographic record
Abstract
Background: Angina pectoris, the main manifestation of coronary artery disease has an unfavorable impact on quality of life. The aim of this study was to assess Health-Related Quality Of Life (HRQoL) in patients with Stable Coronary Artery Disease (SCAD) and to explore possible relationships between HRQoL and the risk factors for ischaemic heart disease, the Canadian Cardiovascular Society (CCS) angina severity class, and the extent of myocardial ischaemia on Single Photon Emission Computed Tomography Myocardial Perfusion Imaging (SPECT-MPI). Methods: HRQoL was assessed with the use of two generic questionnaires, EQ-5D-3L and SF-36v2 in one hundred consecutive patients with SCAD. Results: Most of the patients presented problems on the dimensions of mobility, pain/discomfort, and anxiety/depression of the EQ5D questionnaire. The EQ-VAS score was 61.96 ± 20.99, and the mean EQ-5D index value was 0.54 ± 0.31. The mean scores of the Physical Component Summary and the Mental Component Summary of the SF-36 questionnaire were 43.49 and 41.01 respectively. Higher CCS angina class, female gender and poor physical activity were significantly correlated with worse HRQoL. No statistically significant association was detected between HRQoL and the extent of ischaemia on myocardial perfusion imaging. Conclusions: Patients with SCAD have an impaired HRQoL, which can be reliably assessed by generic HRQoL questionnaires. Angina severity could be used as a surrogate of HRQoL, but individual perception of health status should be measured independently of the amount of ischaemiaon cardiac perfusion scintigraphy Keywords: health related quality of life; myocardial perfusion imaging; coronary artery disease.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".