Guideline for the management of fatigue in children and adolescents with cancer or pediatric hematopoietic cell transplant recipients: 2023 update
Bibliographic record
Abstract
Objective was to update a clinical practice guideline (CPG) for the management of fatigue in children and adolescents with cancer or pediatric hematopoietic cell transplant recipients. We reconvened a multi-disciplinary and multi-national panel. While the previous 2018 CPG evaluated adult and pediatric randomized controlled trials (RCTs) to manage fatigue, this 2023 update revised previous recommendations based only on pediatric RCTs. Twenty RCTs were included in the updated systematic review. Physical activity significantly reduced fatigue (standardized mean difference -0.44, 95% confidence interval -0.64 to -0.24; n = 8 RCTs). Using the 2018 recommendations as a basis, the panel continued to make strong recommendations to use physical activity, and to offer relaxation, mindfulness or both, to manage fatigue in pediatric patients. Cognitive or cognitive behavioral therapies may be offered. Pharmacological approaches should not be routinely used. The panel made a new good practice statement to routinely assess for fatigue, ideally using a validated scale.
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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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".