Participación y proyección de enfermería en los programas de rehabilitación cardiaca
Bibliographic record
Abstract
In the 1970s, cardiac rehabilitation programs became important when a number of clinics and cardiac rehabilitation centers were opened in Europe, Canada and the United States. Many years later, some countries in Latin America opened their first cardiac rehabilitation centers, including Mexico. The goals of cardiac rehabilitation are to improve functional capacity, alleviate or lessen activity- related symptoms, reduce disability, identify and modify coronary risk factors and to reduce morbidity and mortality due to cardiovascular illnesses. The most important outcome of the cardiac rehabilitation programs is an improvement in the patient’s quality of life. Interventions in these programs include supervised exercise training, patient education, psychosocial and vocational evaluation and counseling. Cardiac rehabilitation programs have traditionally been classified by phases according to the clinical conditions and functional status of the patient. Different members of the health team participate in the cardiac rehabilitation programs: doctors, nurses, dieticians, social workers, physical therapists and psychologists. Nurses in cardiac rehabilitation need to have specific knowledge in order to ensure quality of care and safety for the patients. Currently, nurses are developing an important role in these programs carrying out administrative, educational, humanistic, care and research activities. Cardiac rehabilitation is a cardiology field that offers many possibilities of growth and development in nursing.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".