Bibliographic record
Abstract
PURPOSE OF REVIEW: Sleep is particularly important for critically ill patients. Here, we review the latest evidence on how sleep and circadian disruption in the intensive care unit (ICU) affects physiology and clinical outcomes, as well as the most recent advances in sleep and circadian rhythm promoting interventions including therapeutics. RECENT FINDINGS: On a molecular level, clock genes dysrhythmia and altered immunity are clearly linked, particularly in sepsis. Melatonin may also be associated with insulin sensitivity in ICU patients. Clinically, changes in sleep architecture are associated with delirium, and sleep-promoting interventions in the form of multifaceted care bundles may reduce its incidence. Regarding medications, one recent randomized controlled trial (RCT) on melatonin showed no difference in sleep quality or incidence of delirium. SUMMARY: Further investigation is needed to establish the clinical relevance of sleep and circadian disruption in the ICU. For interventions, standardized protocols of sleep promotion bundles require validation by larger multicenter trials. Administratively, such protocols should be individualized to both organizational and independent patient needs. Incorporating pharmacotherapy such as melatonin and nocturnal dexmedetomidine requires further evaluation in large RCTs.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".