Peripheral Skeletal Muscle Impairment in Children After Treatment for Leukemia and Lymphoma
Bibliographic record
Abstract
Exercise intolerance is a common adverse effect of childhood cancer, contributing to impaired health and well-being. While reduced aerobic fitness has been attributed to central cardiovascular deficiencies, the involvement of peripheral musculature has not been investigated. We studied peripheral muscle function in children following cancer treatment using noninvasive phosphorus-31 magnetic resonance spectroscopy. Ten acute lymphoblastic leukemia (ALL) and 1 lymphoma patient 8 to 18 years of age who completed treatment 6 to 36 months prior and 11 healthy controls participated in the study. Phosphorus-31 magnetic resonance spectroscopy was used to characterize muscle bioenergetics at rest and following an in-magnet knee-extension exercise. Exercise capacity was evaluated using a submaximal graded treadmill test. Both analysis of variance and Cohen d were used as statistical methods to determine the statistical significance and magnitude of differences, respectively, on these parameters between the patient and control groups. The patients treated for ALL and lymphoma exhibited lower anaerobic function ( P =0.14, d =0.72), slower metabolic recovery ( P =0.08, d =0.93), and lower mechanical muscle power ( d =1.09) during exercise compared with healthy controls. Patients demonstrated lower estimated VO 2peak (41.61±5.97 vs. 47.71±9.99 mL/min/kg, P =0.11, d =0.76), lower minutes of physical activity (58.3±35.3 vs. 114.8±79.3 min, P =0.12, d =0.99) and higher minutes of inactivity (107.3±74.0 vs. 43.5±48.3 min, d =1.04, P <0.05). Children treated for ALL and lymphoma exhibit altered peripheral skeletal muscle metabolism during exercise. Both deconditioning and direct effects of chemotherapy likely contribute to exercise intolerance in this population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".