The Comparison of the Effectiveness of Respiratory Physiotherapy Plus Myofascial Release Therapy Versus Respiratory Physiotherapy Alone on Cardiorespiratory Parameters in Patients With COVID-19
Bibliographic record
Abstract
Background: Respiratory involvement is a common consequence of COVID-19; changes in cardiorespiratory parameters of these patients during respiratory rehabilitation program are very important. Previous studies showed that myofascial release therapy (MFRT) could affect the respiratory muscle and adjunct fascia. Purpose: The aim of this study was to evaluate the effects of MFRT techniques and respiratory physiotherapy, in comparison with respiratory physiotherapy alone, on improving cardiorespiratory parameter in patients with COVID-19. Setting: A hospital affiliated to Tehran University of Medical Sciences in Tehran, Iran, from February to July 2021. Participants: Fifty patients with COVID-19 participated in this study. Research Design: A single-blind, randomized control design. Intervention: The patients with COVID-19 randomly assigned to an intervention group who received respiratory physiotherapy combined with MFRT or a control group receiving respiratory physiotherapy alone. Main Outcome Measures: Heart rate, systolic and diastolic blood pressure, respiration rate, oxygen saturation, chest expansion, and ease of breathing were assessed at baseline and after the first and third session of treatment. Dyspnea and fatigue perception and 6-minute walking were assessed at baseline and at the end of treatment. Patient's thoughts about the treatment were examined through the 4-point Likert scale. Results: = .02). Conclusions: The present study provided evidence that both programs could result in improving ease of breathing and dyspnea perception, although the inclusion of MFR techniques into a respiratory physiotherapy program did not result in better outcomes in cardiorespiratory function of patients with COVID-19.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 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".