ArticleBMC pulmonary medicine2019
Development and validation of a simple-to-use clinical nomogram for predicting obstructive sleep apnea.
Article in BMC pulmonary medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 citations in OpenAlex.
- Enabling Early Obstructive Sleep Apnea Diagnosis With Machine Learning: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Cardiovascular Disease, Sleep-Disordered Breathing, and Artificial Intelligence: From Neutral Trials to Precision Sleep Cardiology.Reviews in cardiovascular medicine · 2026Review
- Development and Validation of Prediction Models for Severe Obstructive Sleep Apnea Based on Periodic Health Examinations.The clinical respiratory journal · 2026Article
- Development and validation of a diagnostic model for obstructive sleep apnea.Sleep & breathing = Schlaf & Atmung · 2026Article
- Understanding Factors Influencing HIV pre-exposure prophylaxis adherence among men who have sex with men in Western China: a data-driven exploration using bayesian networks.BMC public health · 2025Article
- Construction and validation of a predictive model for sleep disorders among pregnant women.BMC pregnancy and childbirth · 2025Article
- Article
- Advancements in Obstructive Sleep Apnea Diagnosis and Screening Through Artificial Intelligence: A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Advances in Machine Learning Prediction Models for the Screening of Obstructive Sleep Apnea in Adults.Nature and science of sleep · 2025Review
- Improving OSA screening efficiency with subjective questionnaires: integrating STOP-Bang, ESS, and Berlin.Frontiers in medicine · 2025Article
- Development and validation of a nomogram model for predicting the risk of hypertension in Bangladesh.Heliyon · 2024Article
- Development and application of a machine learning-based predictive model for obstructive sleep apnea screening.Frontiers in big data · 2024Article
- Obstructive sleep apnea remains a risk factor for major adverse cardiovascular and cerebrovascular events even in hypertensive patients under treatment: the Urumqi Research on Sleep Apnea and Hypertension (UROSAH) data.Cardiovascular diagnosis and therapy · 2023Article
- Association between glycolipids and risk of obstructive sleep apnea: A population-based study.Frontiers in nutrition · 2023Article
- Two effective clinical prediction models to screen for obstructive sleep apnoea based on body mass index and other parameters.Sleep & breathing = Schlaf & Atmung · 2022Article
- Development and assessment of a risk prediction model for moderate-to-severe obstructive sleep apnea.Frontiers in neuroscience · 2022Article
- Development of a nomogram for predicting the risk of left ventricular diastolic function in subjects with type-2 diabetes mellitus.The international journal of cardiovascular imaging · 2022Article
- Development and validation of a clinical model to predict hypertension in consecutive patients with obstructive sleep apnea hypopnea syndrome: a hospital-based study and nomogram analysis.American journal of translational research · 2022Article
- Development and Validation of a Nomogram for Predicting Obstructive Sleep Apnea in Patients with Pulmonary Arterial Hypertension.Nature and science of sleep · 2022Article
- A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with Hypertension.International journal of hypertension · 2022Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe high cost and low availability of polysomnography (PSG) limits the timely diagnosis of OSA. Herein, we developed and validated a simple-to-use nomogram for predicting OSA.
methodsWe collected and analyzed the cross-sectional data of 4162 participants with suspected OSA, seen at our sleep center between 2007 and 2016. Demographic, biochemical and anthropometric data, as well as sleep parameters were obtained. A least absolute shrinkage and selection operator (LASSO) regression model was used to reduce data dimensionality, select factors, and construct the nomogram. The performance of the nomogram was assessed using calibration and discrimination. Internal validation was also performed.
resultsThe LASSO regression analysis identified age, sex, body mass index, neck circumference, waist circumference, glucose, insulin, and apolipoprotein B as significant predictive factors of OSA. Our nomogram model showed good discrimination and calibration in terms of predicting OSA, and had a C-index value of 0.839 according to the internal validation. Discrimination and calibration in the validation group was also good (C-index = 0.820). The nomogram identified individuals at risk for OSA with an area under the curve (AUC) of 0.84 [95% confidence interval (CI), 0.83-0.86].
conclusionsOur simple-to-use nomogram is not intended to replace standard PSG, but will help physicians better make decisions on PSG arrangement for the patients referred to sleep center.
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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.