Disturbed Sleep in Pediatric Patients With Leukemia: The Potential Role of <i>Interleukin-6</i> (-174GC) and <i>Tumor Necrosis Factor</i> (-308GA) Polymorphism
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To explore an association between sleep quality in children and adolescents undergoing therapy for acute lymphoblastic leukemia (ALL) and polymorphisms in two proinflammatory cytokines, interleukin-6 (IL-6) and tumor necrosis factor (TNF). DESIGN: Retrospective exploratory analysis using data from a multi-institutional prospective study comparing objective sleep measures by actigraphy over 10 days with retrospective genotyping of IL-6 (-174GC) and TNF (-308GA). SETTING: Pediatric oncology centers in the southeastern and southwestern United States and in Canada. SAMPLE: 88 children or adolescents with ALL. METHODS: Secondary analysis of 88 patients (ages 5-18) with sleep quality measured by actigraphy over 10 days in their home environment and retrospective DNA genotyping. MAIN RESEARCH VARIABLES: Sleep variables and genotype. FINDINGS: IL-6 promoter (-174G>C) C allele was associated with fewer total daily sleep minutes (p = 0.028) and fewer daily nap minutes (p < 0.01). Patients with the TNF genotype AA had 28.2 more minutes of wake after sleep onset (p = 0.015), 3.4 more nocturnal wake episodes (p = 0.026), and a 5% lower sleep efficiency rate (p = 0.03) than their GA genotype counterparts. CONCLUSIONS: Patients with the TNF (-308G>A) or IL-6 (-174G>C) polymorphisms demonstrated disturbed sleep. This study is the first to find a relationship between these two cytokines and disturbed sleep in children and adolescents with cancer. IMPLICATIONS FOR NURSING: Disturbed sleep among pediatric patients with cancer is multifactoral and includes interactions among environment, medications, and genotype. Additional research should explore serum proinflammatory cytokine levels and the influence of mood and worry on sleep.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".