The Efficacy of a Single Session of 20-Minute Mindful Breathing in Reducing Dyspnea Among Patients With Acute Decompensated Heart Failure: A Randomized Controlled Trial
Bibliographic record
Abstract
Heart failure is the leading cause of morbidity and mortality worldwide. Standard treatment for heart failure includes pharmacotherapy and cardiac device implants. However, supportive approaches in managing dyspnea in heart failure are limited. This study aimed to test the efficacy of 20-minute mindful breathing in reducing dyspnea among patients admitted for acute decompensated heart failure. We conducted a parallel-group, non-blinded, randomized controlled trial of a single session of 20-minute mindful breathing plus standard care versus standard care alone among patients admitted for moderate to severe dyspnea due to acute decompensated heart failure, using the dyspnea score based on the Edmonton Symptom Assessment System (ESAS), at the Cardiology Unit of University Malaya Medical Centre in Malaysia. Thirty participants were randomly assigned to a single session of 20-minute mindful breathing plus standard care (n = 15) or standard care alone (n = 15), with no difference in their demographic and clinical characteristics. There was statistically significant reduction in dyspnea in the intervention group compared to the control group at minute 20 (U = 49.5, n 1 = 15, n 2 =15, median reduction in ESAS dyspnea score 1 = 2, median reduction in ESAS dyspnea score 2 = 0, mean rank 1 = 11.30, mean rank 2 = 19.70, z = −2.692, r = 0.4, P = 0.007). Our results provided evidence that a single session of 20-minute mindful breathing was efficacious in reducing dyspnea for patients admitted for acute decompensated 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".