Assessment of gross motor skills and phenotype profile in children 9–11 years of age in survivors of acute lymphoblastic leukemia
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to evaluate the usefulness of a new gross motor skill test battery in acute lymphoblastic leukemia (ALL) children who have been off therapy for at least 1 year and to assess its discriminatory power (discriminant analysis) from healthy children. PROCEDURE: Twenty children (10 males and 10 females) 9-11 years of age (median age = 10.6 years) were assessed by the UQAC-UQAM test battery and then compared to recent provincial norms. This pilot study was also an opportunity to validate this test battery as a reliable tool for clinical or research purposes in the area of chronic or disabling diseases in children. Eleven motor skill variables grouped into five factors have been measured (speed, agility, balance, coordination, and reaction time). RESULTS: Scores from 10 of the 11 motor skill tests showed significant differences when compared to the control group (P ≤ 0.05). Nearly 50% of patients obtained an average score below the 15th percentile. Furthermore, stepwise discriminant analysis allowed classifying successfully 88.4% of children in the correct group (ALL or Control). The normal development of GMS among children affected by ALL appears to have been compromised. The UQAC-UQAM test battery seems to be sensitive enough to quantify with precision the extent of the motor impairment in these children. CONCLUSION: The UQAC-UQAM test battery appears to be a useful tool to evaluate the extent to which ALL survivors are affected. Early motor intervention should be considered for those patients even during the treatment periods.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".