Decongestive progressive resistance exercise with an adjustable compression wrap for breast cancer-related lymphoedema (DREAM): protocol for a randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Breast cancer-related lymphoedema (BCRL) is a chronic swelling in the arm on the side of the breast cancer surgery, affecting one in five women. Recent studies in BCRL have demonstrated that resistance exercise can improve symptoms and quality of life without worsening lymphoedema. No studies have explored whether combining the principles of progressive resistance exercise training with therapeutic strategies of compression therapy and the decongestive lymphatic exercise sequence are beneficial in reducing arm lymphoedema volume. The aim of this three-arm, provincial randomised controlled trial is to determine the efficacy of a 12-week decongestive progressive resistance exercise (DRE) programme in combination with the one of two types of compression garments compared with standard care. METHODS AND ANALYSIS: Sixty women with BCRL will be recruited and randomly assigned to one of the following three groups: (1) Standard care, (2) DRE with use of a daytime compression garment during exercise and (3) DRE with use of an adjustable compression wrap during exercise. The primary outcome is the percentage reduction in arm lymphoedema volume. Secondary outcomes include bioimpedance analysis, muscular strength, shoulder range of motion, physical activity level and health-related quality of life. Exploratory outcomes include evaluating changes in arm tissue composition using MRI and examining outcomes between the two DRE experimental groups. The primary analysis will compare changes between the groups from baseline to week 12 reflecting the end of the randomised control trial period. ETHICS AND DISSEMINATION: The trial has received ethics approval from the Health Research Ethics Board of Alberta: Cancer Committee. The study results will be disseminated through scientific peer-reviewed publications, and presented at national and international conferences, and other media portals. The programme protocol will be shared with healthcare professionals and patient groups through clinical workshops and webinars. TRIAL REGISTRATION NUMBER: NCT05022823. PROTOCOL VERSION: 12 November 2021. ISSUE DATE: 26 April 2021.
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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 | 0.031 | 0.029 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.091 | 0.014 |
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".