Effects of a Concurrent Mixed-Modality (Telerehabilitation and Face-to-Face) Exercise Rehabilitation Program in a Patient with Multiple Myeloma Prior to Spinal Cord Transplantation: A Case Study
Bibliographic record
Abstract
Introduction: Multiple myeloma constitutes approximately 12% of hematologic malignancies and predominantly affects older adults, significantly compromising their quality of life. Although exercise interventions have shown benefits in oncology, evidence specific to MM remains limited and of low certainty. The presence of complex comorbidities in MM patients necessitates highly individualized approaches. Prehabilitation has emerged as a promising strategy to enhance functional capacity prior to autologous stem cell transplantation. This case study evaluates the feasibility of a personalized, scheduled exercise intervention delivered via telerehabilitation. Intervention: This case study seeks to examine the feasibility of implementing a personalized and scheduled exercise intervention within a telerehabilitation framework for a medically complex patient with multiple myeloma (MM). The 12-week prehabilitation protocol is designed to enhance physical function prior to autologous bone marrow transplantation by integrating therapeutic exercise targeting key parameters related to quality of life and clinical resilience, such as muscular strength, aerobic capacity, coordination, and overall well-being. The intervention includes concurrent training (strength and aerobic exercises) delivered 2–3 times per week, with aerobic activities conducted independently at home through a virtual format. Assessments were performed at baseline and post-intervention. Results and conclusion: A personalized exercise program, implemented through a hybrid model of in-person and telerehabilitation, is both feasible and safe. It has the potential to enhance physical function and quality of life in patients with multiple myeloma. Further research is necessary to validate these findings across broader patient populations.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".