ArticleFrontiers in neuroscience2021
Development and Validation of a Clinical Prediction Model for Sleep Disorders in the ICU: A Retrospective Cohort Study.
Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 7 citations in OpenAlex.
- AI digital-twin ecosystem translating gut-microbiome-neuroimmune signals into precision sleep-mood interventions.Frontiers in psychiatry · 2026Review
- Validation and the psychometric properties of the Persian version of the sleep quality scale for coronary care patients: a methodological survey.Scientific reports · 2025Article
- Review
- The use of nomogram for detecting mild cognitive impairment in patients with type 2 diabetes mellitus.Journal of diabetes · 2023Article
- Exploration of Perioperative Sleep Disturbance in 208 Patients Undergoing Non-Cardiac Surgery: Protocol for a Prospective Cohort Study.Medical science monitor : international medical journal of experimental and clinical research · 2023Article
- Development and validation of prediction models for neurocognitive disorders in adult patients admitted to the ICU with sleep disturbance.CNS neuroscience & therapeutics · 2022Article
- Risk factors and prediction model of sleep disturbance in patients with maintenance hemodialysis: A single center study.Frontiers in neurology · 2022Article
- Development and Validation of Nomogram Prediction Model for Postoperative Sleep Disturbance in Patients Undergoing Non-Cardiac Surgery: A Prospective Cohort Study.Nature and science of sleep · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSleep disorders, the serious challenges faced by the intensive care unit (ICU) patients are important issues that need urgent attention. Despite some efforts to reduce sleep disorders with common risk-factor controlling, unidentified risk factors remain.
objectivesThis study aimed to develop and validate a risk prediction model for sleep disorders in ICU adults.
methodsData were retrieved from the MIMIC-III database. Matching analysis was used to match the patients with and without sleep disorders. A nomogram was developed based on the logistic regression, which was used to identify risk factors for sleep disorders. The calibration and discrimination of the nomogram were evaluated with the 1000 bootstrap resampling and receiver operating characteristic curve (ROC). Besides, the decision curve analysis (DCA) was applied to evaluate the clinical utility of the prediction model.
results2,082 patients were included in the analysis, 80% of whom (
conclusionThe model showed high performance in predicting sleep disorders in ICU adults, the good clinical utility of which may be a useful tool for providing clinical decision support to improve sleep quality in the ICU.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.