Sleep fragmentation in critically ill children: a review of contributing factors in the pediatric intensive care unit and neurodevelopmental outcomes
Bibliographic record
Abstract
Sleep is a critical neurobiological process essential for brain maturation, emotional regulation, cognitive development, and overall organ system homeostasis. In the pediatric intensive care unit (PICU), sleep architecture is frequently disrupted by environmental stimuli, sedation, and clinical interventions, resulting in sleep fragmentation. Unlike sleep deprivation, sleep fragmentation preserves sleep duration but impairs its continuity and depth, disproportionately affecting slow-wave sleep, that is essential for growth, healing, in addition to immune function and REM sleep, that is fundamental for synaptic plasticity, neurogenesis, and memory consolidation. These disruptions are particularly concerning in children, who require more sleep than adults due to ongoing neurogenesis and rapid somatic growth, rendering them uniquely vulnerable to adverse effects. Emerging evidence links fragmented sleep in the PICU to altered neurodevelopmental trajectories and increased risk of Pediatric Post-Intensive Care Syndrome (PICS-p), with delirium serving as a key mediator. Despite promising adult studies on sleep-promoting interventions and EEG-based monitoring, pediatric research remains limited. Future research should prioritize objective sleep monitoring, developmental tailoring of care protocols, and longitudinal studies to clarify the impact of sleep fragmentation on recovery and neurodevelopment. This narrative review highlights the urgent need to recognize and preserve sleep as a modifiable determinant of neurocognitive outcomes in critically ill children.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".