Physical activity during treatment in children with leukemia: a pilot study
Bibliographic record
Abstract
The purpose of this pilot study was to measure physical activity (PA) levels in children undergoing treatment for acute lymphoblastic leukemia (ALL) and to compare the results with those from age-matched healthy children. We used the MTI Actigraph accelerometer to determine PA (during a 1 week period) in children (n = 7; age = 4-7 y) undergoing maintenance treatment for ALL and in age-matched controls (n = 7). The number of children accumulating at least 60 min of moderate-to-vigorous physical activity (MVPA) for 5 or more days of the week was 3 for the control group, whereas no children with ALL met this criterion. Significantly lower levels of total weekly time of MVPA were seen in children being treated for ALL (328 +/- 107 min) than in controls (506 +/- 175 min) (p < 0.05). When weekday data was analyzed, the ALL patients also had significantly lower mean daily times of MVPA (49 +/- 23 min vs. 79 +/- 25 min). It is thus important that young ALL sufferers are encouraged to participate in appropriate sports, games, and physical activities both in the family and school environments that will prime them with positive attitudes to PA during the critical early years of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".