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Record W4295761011 · doi:10.1097/mcp.0000000000000912

Sleep in the intensive care unit

2022· review· en· W4295761011 on OpenAlexaff
Eugenia Y. Lee, M. Elizabeth Wilcox

Bibliographic record

VenueCurrent Opinion in Pulmonary Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsMedicineDeliriumMelatoninIntensive care medicineRandomized controlled trialIntensive care unitPsychological interventionCircadian rhythmIntensive careSleep (system call)ActigraphyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.174
GPT teacher head0.431
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations14
Published2022
Admission routes1
Has abstractyes

Explore more

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