ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2022
Obstructive sleep apnea predicts 10-year cardiovascular disease-related mortality in the Sleep Heart Health Study: a machine learning approach.
Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Obstructive sleep apnea and right ventricular function: A meta-analysis of speckle tracking echocardiographic studies.Journal of clinical hypertension (Greenwich, Conn.) · 2022Pooled it
- Benchmarking inflammation-nutrition and TyG-related indices for 5-year mortality risk in adults with questionnaire-defined obstructive sleep apnea: a survey-weighted NHANES derivation cohort with multicenter external validation.Journal of translational medicine · 2026Article
- Modified Sleep Apnea Severity Index and Cardiovascular Risk in CPAP-Intolerant OSA Patients.The Laryngoscope · 2026Article
- Sleep apnoea and its consequences: from animal models to precision medicine.Sleep medicine · 2026Review
- Identification of Comorbidities in Obstructive Sleep Apnea Using Diverse Data and a One-Dimensional Convolutional Neural Network.Sensors (Basel, Switzerland) · 2026Observational
- Comparative analysis of cardiac autonomic dysfunction between apnea-predominant and hypopnea-predominant obstructive sleep apnea: a study matched for age, sex, and apnea-hypopnea index : Short running title: cardiovascular risk of apnea vs. hypopnea in OSA.Sleep & breathing = Schlaf & Atmung · 2025Article
- Predicting All-Cause Mortality in Patients With Obstructive Sleep Apnea Using Sleep-Related Features: A Machine-Learning Approach.Journal of clinical neurology (Seoul, Korea) · 2025Article
- Article
- A foundational transformer leveraging full night, multichannel sleep study data accurately classifies sleep stages.medRxiv : the preprint server for health sciences · 2024Article
- Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management.Cell metabolism · 2024Review
- Achieving Better Understanding of Obstructive Sleep Apnea Treatment Effects on Cardiovascular Disease Outcomes through Machine Learning Approaches: A Narrative Review.Journal of clinical medicine · 2024Review
- Multiple Machine Learning Methods Reveal Key Biomarkers of Obstructive Sleep Apnea and Continuous Positive Airway Pressure Treatment.Frontiers in genetics · 2022Article
- The Weighted Combination of the Epworth Sleepiness Scale and the STOP-Bang Questionnaire Improved the Predictive Value of for OSAHS in Hypertensive Patients.International journal of general medicine · 2022Article
- Review
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Authors and funding
4 authors.
Funding
Abstract
STUDY
objectivesObstructive sleep apnea (OSA) is considered to be an important risk factor for the development of cardiovascular disease (CVD). This study aimed to develop and evaluate a machine learning approach with a set of features for assessing the 10-year CVD mortality risk of the OSA population.
methodsThis study included 2,464 patients with OSA who met study inclusion criteria and were selected from the Sleep Heart Health Study. We evaluated the importance of potential features by mutual information. The top 9 features were selected to develop a random forest model.
resultsWe evaluated the model performance on a test set (n = 493) using the area under the receiver operating curve with 95% confidence interval and confusion matrix. A random forest model awarded the highest area under the receiver operating curve of 0.84 (95% confidence interval: 0.78-0.89). The specificity and sensitivity were 73.94% and 81.82%, respectively. Sixty-three years old was a threshold for increased risk of 10-year CVD mortality. Persons with severe OSA had higher risk than those with mild OSA.
conclusionsThis study demonstrated that a random forest model can provide a quick assessment of the risk of 10-year CVD mortality. Our model may be more informative for patients with OSA in determining their future CVD mortality risk. CITATION: Li A, Roveda JM, Powers LS, Quan SF. Obstructive sleep apnea predicts 10-year cardiovascular disease-related mortality in the Sleep Heart Health Study: a machine learning approach.
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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.