The effect of progressive muscle relaxation on sleep quality and postoperative pain in patients undergoing heart valve replacement surgery
Bibliographic record
Abstract
Background and aims: To investigate the effect of progressive muscle relaxation on sleep quality and postoperative pain in patients undergoing heart valve replacement surgery. Methods: In this quasi-experimental study, 60 patients undergoing surgery that enter were randomly divided into the muscle relaxation (n=30) or control group (n=30). Data were collected by Pittsburgh Sleep Quality Index and McGill Pain Questionnaire before and after the intervention. Patients in the control group received routine care, but patients in the muscle relaxation group performed a progressive relaxation technique twice a week for one month. Results: Most of the male participants in both groups had diplomas. There is no significant difference between the two groups of relaxation and control regarding age, gender, occupation, and education levels. The mean sleep quality score in the control group was not significantly reduced after the intervention. However, the mean sleep quality in the relaxation group before 13.90±2.23 and after the intervention was 8.03±2.01 significantly decreased (P<0.001). Also, the pain score was significantly reduced after the progressive relaxation group in the intervention group (P<0.001). Although the two groups were the same in all the dimensions of sleep quality before the intervention, significant differences were observed between groups after the intervention in all the dimensions. Conclusion: Progressive muscle relaxation has an influential role in the pain decrease and sleep quality of patients undergoing heart valve replacement surgery and can be used as a safe and cost-free method for patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".