Impact of Exercise Training on Hematological Outcomes Following Hematopoietic Cell Transplantation: A Scoping Review
Bibliographic record
Abstract
PURPOSE: Hematopoietic cell transplantation (HCT) is associated with significant risk prior to hematopoietic engraftment. Endurance exercise can modify the bone marrow microenvironment, alter hematopoiesis and accelerate hematopoietic regeneration in mouse models of transplantation. METHODS: A systematic review was conducted to clarify the impact of exercise on clinically relevant hemato-logical outcomes in patients following HCT. RESULTS: A systematic search of the literature identified 13 studies (total of 615 participants; 313 in study arms). Studies included exercise regimens that were primarily low-to-moderate intensity. A total of five studies re-ported on engraftment and length of stay, which were largely unchanged with intervention. Rates of graft-ver-sus host disease were reported in six studies whereas red cell and platelet transfusion needs were reported in four studies, neither of which was different with exercise. Survival was reported in four studies and was significantly improved by exercise in one study. CONCLUSIONS: Exercise in patients receiving HCT appears feasible and safe. Heterogeneity in type and intensity of exercise was observed and few studies examined high intensity exercise. Outcome reporting was inconsis-tent regarding transplant-related outcomes. Standardized hematological outcome measures are needed to clarify the impact of higher intensity exercise on HCT.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".