Impacto de um Programa de Redução do Estresse, Meditação e Mindfulness em Pacientes com Insuficiência Cardíaca Crônica: Um Ensaio Clínico Randomizado
Bibliographic record
Abstract
Heart Failure is a significant public health problem leading to a high burden of physical and psychological symptoms despite optimized therapy. To evaluate primarily the impact of a Stress Reduction, Meditation, and Mindfulness Program on stress reduction of patients with Heart Failure. A randomized and controlled clinical trial assessed the effect of a stress reduction program compared to conventional multidisciplinary care in two specialized centers in Brazil. The data collection period took place between April and October 2019. Thirty-eight patients were included and allocated to the intervention or control groups. The intervention took place over 8 weeks. The protocol assessed the scales of perceived stress, depression, quality of life, anxiety, mindfulness, quality of sleep, a 6-minute walk test, and biomarkers analyzed by a blinded team, considering a p-value <0.05 statistically significant. The intervention resulted in a significant reduction in perceived stress from 22.8 ± 4.3 to 14.3 ± 3.8 points in the perceived stress scale-14 items in the intervention group vs. 23.9 ± 4.3 to 25.8 ± 5.4 in the control group (p-value<0.001). A significant improvement in quality of life (p-value=0.013), mindfulness (p-value=0.041), quality of sleep (p-value<0.001), and the 6-minute walk test (p-value=0.004) was also observed in the group under intervention in comparison with the control. The Stress Reduction, Meditation, and Mindfulness Program effectively reduced perceived stress and improved clinical outcomes in patients with chronic Heart Failure.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".