Effect of complex decongestive therapy on frailty and quality of life in women with breast cancer-related lymphedema: the before-and-after treatment study
Bibliographic record
Abstract
Objective: To investigate the impact of Complex Decongestive Therapy (CDT) on the severity of frailty and quality of life in individuals suffering from postmastectomy lymphedema syndrome. Methods: Participants who met the inclusion criteria were informed about CDT and informed consent was obtained. Edmonton Frailty Scale (EFS), extremity volüme (EV), lymphedema stage(LS), EQ-5D General Quality of Life Scale (EQ-5D-5L), and Quick Disabilities of Arm, Shoulder, and Hand (DASH) scores were evaluated by the same physician before and after treatment. A total of 15 sessions of CDT were performed for 3 weeks, five days a week. During the treatment period, hospitalized patients received guidance from a nurse on protecting the affected arm in their daily routine. Results: Eighty patients with breast cancer-related lymphedema who met the inclusion criteria were included in the study. Following a period of 3 weeks of practice and training, the specialist physician conducted the final evaluation and assessments. All patients showed a statistically significant reduction in EV, and regression in LS, EFS, and Quick DASH score (p<0.001). Statistically significant improvement was also observed in quality of life and general health status. (p<0.001). Conclusion: The application of 15 sessions of CDT and educational interventions to women with postmastectomy lymphedema syndrome due to breast cancer yielded positive outcomes. This approach led to an enhancement in patients' functional capacity, improving their quality of life and a subsequent reduction in the severity of frailty.
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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 | 0.001 | 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".