Exercise before, during, and after Hospitalization for Allogeneic Hematological Stem Cell Transplant: A Feasibility Randomized Controlled Trial
Bibliographic record
Abstract
People with cancer who undergo allogeneic hematological stem cell transplant (allo-HSCT) experience significant deconditioning that can compromise quality of life. Exercise has shown to be beneficial before or after allo-HSCT; however, little is known about exercise therapy delivered across the continuum of care. We conducted a feasibility randomized controlled trial of exercise delivered prior to admission, during the inpatient stay, and after discharge versus control in people with planned allo-HSCT. Feasibility was assessed via recruitment and retention rates, the incidence of adverse events, and adherence to the exercise prescription. Estimates of efficacy were measured at baseline, one week prior to hospital admission, and 100 days and one year after transplant. The recruitment and retention rates were 20% and 33%, respectively. One serious adverse event occurred during the baseline six-minute walk test that precluded participation in the study and no adverse events were associated with the intervention. From baseline to pre-transplant, the intervention group improved six-minute walk test distances by 45 m (95% CI: -18.0 to 108.7)-a finding that warrants further investigation with an adequately powered trial. Our study contributes important feasibility considerations and pilot data for future exercise intervention research in allo-HSCT recipients.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".