Kundalini Yoga for Improving Patient-Reported Outcomes in Patients Diagnosed with Myelodysplastic Syndromes: A Pilot Study
Bibliographic record
Abstract
INTRODUCTION: Despite adequate pharmacologic treatment and transfusion support for myelodysplastic syndromes (MDS), there is an ongoing need to explore non-pharmacologic approaches for managing MDS symptom burden. Yoga has proved effective in oncologic patients. The aim of this observational study was to explore the feasibility of an 8-week online Kundalini yoga program, including its impact on symptom burden in MDS patients. METHODS: All patients diagnosed with MDS in our medical center were offered an 8-week online program, in which a 1-h weekly kundalini yoga session was held live via Zoom. All segments included postures in the sitting position, specifically planned for this patient population. Symptom burden was assessed before and after each session and at a later timepoint - 8 weeks post-course completion, using the Edmonton Symptom Self-Assessment Scale - global distress score (ESAS-GDS). RESULTS: Fourteen patients participated in the program. The median number of sessions per patient was 4. The questionnaires were reasonably easy for the patients to complete. Mean GDSs significantly improved after yoga sessions. Patients consistently endorsed reduced fatigue (78%), increased alertness (65%), increased general well-being (60%), and reduced anxiety (42%) after practicing yoga. Furthermore, symptom burden remained significantly improved 8 weeks after course completion. CONCLUSION: This Kundalini yoga program for MDS patients was feasible and resulted in significantly better patient-reported health outcomes, ongoing for at least 8 weeks after the last intervention. Longer follow-up within a longer practice program is planned.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".