Sleep on the ward in intensive care unit survivors: a case series of polysomnography
Bibliographic record
Abstract
BACKGROUND: Few studies have investigated sleep in patients after intensive care despite the possibility that inadequate sleep might further complicate an acute illness impeding recovery. AIMS: To assess the quality and quantity of a patient's sleep on the ward by polysomnography (PSG) within a week of intensive care unit (ICU) discharge and to explore the prevalence of key in-ICU risk factors for persistent sleep fragmentation. METHODS: We enrolled 20 patients after they have been mechanically ventilated for at least 3 days and survived to ICU discharge. We included all patients over the age of 16 years and excluded patients with advanced cognitive impairment or who were unable to follow simple commands before their acute illness, primary admission diagnosis of neurological injury, uncontrolled psychiatric illness or not fluent in English. RESULTS: Twenty patients underwent an overnight PSG recording on day 7 after ICU discharge (SD, 1 day). ICU survivors provided 292.8 h of PSG recording time with median recording times of 16.8 h (Interquartile range (IQR), 15.0-17.2 h). The median total sleep time per patient was 5.3 h (IQR, 2.6-6.3 h). In a multivariable regression model, postoperative admission diagnosis (P = 0.04) and patient report of poor ICU sleep (P = 0.001) were associated with less slow-wave (restorative) sleep on the wards after ICU discharge. CONCLUSIONS: Patients reported poor sleep while in the ICU, and a postoperative admission diagnosis may identify a high-risk subgroup of patients who may derive greater benefit from interventions to improve sleep hygiene.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".