Contribution of Fatigue to Cognitive Dysfunction in Childhood Acute Lymphoblastic Leukemia Survivors
Bibliographic record
Abstract
Late effects such as neurocognitive issues and fatigue have been reported in childhood acute lymphoblastic leukemia (cALL) survivors. Yet, their association is often poorly understood. In this study, we wished to (1) describe neurocognitive difficulties and fatigue in a well-characterized cohort of long-term cALL survivors and (2) explore the risk of having neurocognitive deficits as a function of fatigue. Childhood ALL survivors (N = 285) from three Canadian treatment centers completed the DIVERGT battery of cognitive tests and the PedsQL Multidimensional Fatigue Scale. We performed logistic regressions to assess the risk of a survivor to show cognitive deficits (<2.0 SD) depending on their fatigue levels. At least one cognitive deficit on the DIVERGT was present in 31% of participants. Domains primarily affected were working memory, fine motor skills, and verbal fluency. Sleep/rest fatigue in youths was higher than norms (d = 0.35). The risk for cognitive deficits increased independently with levels of fatigue in the domains of cognitive speed and flexibility, working memory, and verbal fluency. For every 10-point increase on general or sleep/rest fatigue on the 0-100 scale, there was a median +23–35% risk of showing a deficit among the 7 tasks significantly associated with fatigue. Fatigue may constitute a complementary target when searching to mitigate cognitive issues in this population.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".