The impact of poor sleep on cognition and activities of daily living after traumatic brain injury: A review
Bibliographic record
Abstract
BACKGROUND/AIM: Patients frequently report sleep disruptions or insomnia during their hospital stay, particularly after a traumatic brain injury (TBI). The consequences of these sleep disturbances on everyday activities are not well documented and are therefore not considered in the evaluation of independence in activities of daily living (ADLs). The goal of this narrative review is to explore the consequences of poor sleep quality on cognition and ADLs in the acute and subacute stages of a moderate and severe TBI, when patients are in acute care or inpatient rehabilitation. METHODS: We will present an overview of normal sleep and its role in cognitive functioning, and then present the findings of studies that have investigated sleep characteristics in hospital settings and the consequences of sleep disturbances on ADLs. RESULTS: During hospitalisation, TBI patients present severe sleep disturbances such as insomnia and sleep fragmentation, which are probably influenced by both the medical condition and the hospital or rehabilitation environment. Sleep disruption is associated with several cognitive deficits, including attention, memory and executive function impairments. Poor quality and/or insufficient quantity of sleep in acute TBI probably affect general functioning and ADLs calling for these cognitive functions. CONCLUSIONS AND SIGNIFICANCE: The cognitive impairments present following TBI are probably exacerbated by poor sleep quality and sleep deprivation during hospitalisation, which in turn impact ADLs among this population. Health-care personnel should further consider sleep disturbances among people with TBI and a sleep protocol should be established.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| 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".