A single‐arm feasibility study protocol for a multiphasic multimodal exercise prehabilitation intervention in individuals receiving allogeneic stem cell transplant
Bibliographic record
Abstract
BACKGROUND: Allogeneic hematopoietic stem cell transplantation (allo-HSCT) can be a life-saving treatment for individuals diagnosed with acute leukemia. However, allo-HSCT can lead to adverse effects, such as reduced physical function. Exercise has demonstrated benefits in post-allo-HSCT recovery, but feasibility issues persist in tailored prehabilitation interventions. OBJECTIVE: To present a multiphasic exercise prehabilitation protocol.The study aims to assess feasibility, safety, and impact while establishing screening and referral pathways to community-based exercise oncology resources. DESIGN: Single arm feasibility study. PARTICIPANTS: Individuals diagnosed with acute leukemia and eligible for allo-HSCT will be recruited for the study. INTERVENTION: Multimodal exercise and health behavior change support that will span across the allo-HSCT timeline (ie, pre-, during, and post-transplant phases). Clinical exercise physiologists trained in exercise oncology and health behavior change will deliver the intervention. MAIN OUTCOME MEASURES: Assessment of physical function, self-reported and objective physical activity, quality of life, fatigue, anxiety, depression, and symptom burden across four timepoints (baseline, pre-transplant, post-transplant inpatient recovery, and post-transplant outpatient recovery). CONCLUSIONS: This study is designed to address current limitations in prehabilitation literature specific to individuals with acute leukemia receiving allo-HSCT. In turn, this study may offer an approach to maintain or improve physical function and quality of life throughout the transplant continuum.
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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 | 0.022 | 0.012 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.009 |
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".