Changes in the Quality of Life: A Major Goal of Cardiac Rehabilitation
Bibliographic record
Abstract
BACKGROUND: Quality of life (QOL) is a major goal in the context of preventive and therapeutic cardiology. In this article, quality of life concepts are reviewed, factors limiting QOL in cardiac disease are identified, methods of measurement are explored, and clinically significant changes are defined. The changes effected by cardiac rehabilitation are considered, together with their physiological and psychological correlates. A final section suggests avenues for future research. METHODS: Relevant articles were identified by computer literature searches and review of extensive personal files. FINDINGS: In the past, there has been an excessive focus on extending the length rather than the quality of the cardiac patient's life. The overall QOL is a broad concept, influenced by personal perceptions, coping mechanisms, and environmental constraints. The ideal test instrument would be reliable, valid, and responsive to clinical change. Potential options include a Gestalt-type instrument, a disease-specific instrument, a function-specific instrument, or a detailed generic questionnaire. There have been relatively few comparisons between these potential approaches. Currently, the Standard Gamble (Gestalt-type), and Living With Heart Failure Questionnaire (disease-specific type), and the Medical Outcomes Study Short-Form 36 (SF-36) Health Survey (generic-type) are among the most popular approaches. Problems arise in distinguishing a clinically important from a statistically significant change; commonly a score change of 1 standard error of the mean is regarded as clinically important. Correlations of scores with clinical, physiological, and psychological change are sometimes weak, in part because of floor and ceiling effects. Nevertheless, potential gains in QOL provide a stronger argument for preventive and therapeutic programs than do increases in longevity. CONCLUSIONS: The current literature supports the value of QOL measurements in the management of patients with cardiac disease. However, further research is needed to determine the optimum test instrument, and the best method of interpreting resultant scores.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".