Effects of traditional Chinese mind-body exercises for patients with chronic fatigue syndrome: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Chronic fatigue syndrome (CFS) is a global public health concern. We performed this systematic review of randomised controlled trials (RCTs) to evaluate the effects and safety of traditional Chinese mind-body exercises (TCME) for patients with CFS. Methods: to assess heterogeneity and conducted subgroup analyses based on different types of TCME, background therapy, and types of fatigue. We also assessed the quality of evidence using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach. Results: We included 13 studies (n = 1187) with a maximal follow-up of 12 weeks. TCME included Qigong and Tai Chi. At the end of the treatment, compared with passive control, TCME probably reduces the severity of fatigue (standardised mean differences (SMD) = 0.85; 95% confidence interval (CI) = 0.64, 1.07, moderate certainty), depression (SMD = 0.53; 95% CI = 0.34, 0.72, moderate certainty), anxiety (SMD = 0.29; 95% CI = 0.11, 0.48, moderate certainty), sleep quality (SMD = 0.34; 95% CI = 0.10, 0.57, low certainty) and mental functioning (SMD = 0.90; 95% CI = 0.50, 1.29, low certainty). Compared with other active control therapies, TCME results in little to no difference in the severity of fatigue (SMD = 0.08; 95% CI = -0.18, 0.34, low certainty). For long-term outcomes, TCME may improve anxiety (SMD = 1.74; 95% CI = 0.44, 3.03, low certainty) compared to passive control. We did not identify TCME-related serious adverse events. Conclusions: In patients with CFS, TCME probably reduces post-intervention fatigue, depression, and anxiety and may improve sleep quality and mental function compared with passive control, but has limited long-term effects. These findings will help health professionals and patients with better clinical decision-making. Registration: PROSPERO: CRD42022329157.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| 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".