ArticlePloS one2021
Risk factors and clinical prediction formula for the evaluation of obstructive sleep apnea in Asian adults.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 4 of them syntheses that pooled it.
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Who cites it
15 citing papers in PubMed, 4 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Clinical prediction models for the early diagnosis of obstructive sleep apnea in stroke patients: a systematic review.Systematic reviews · 2024Pooled it
- Clinical Practice Guideline: Clinical Efficacy of Nasal Surgery in the Treatment of Obstructive Sleep Apnea.Clinical and experimental otorhinolaryngology · 2023Guideline
- Discovery of genomic loci associated with sleep apnea risk through multi-trait GWAS analysis with snoring.Sleep · 2023Pooled it
- Enabling Early Obstructive Sleep Apnea Diagnosis With Machine Learning: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Factors influencing the prediction of obstructive sleep apnea: an observational study from a developing country.Future science OA · 2026Article
- Changes in Prescription Patterns and Diagnostic Outcomes of Polysomnography After Insurance Coverage: A Multicenter Retrospective Study.Journal of rhinology : official journal of the Korean Rhinologic Society · 2025Article
- The Obstructive Sleep Apnea Physical Exam: A Systematic Review and Meta-Analysis.Laryngoscope investigative otolaryngology · 2025Review
- Advancements in Obstructive Sleep Apnea Diagnosis and Screening Through Artificial Intelligence: A Systematic Review.Healthcare (Basel, Switzerland) · 2025Review
- Oxytocin Receptor Polymorphism Is Associated With Sleep Apnea Symptoms.Journal of the Endocrine Society · 2024Article
- Inclusion of blood pressure parameter increases predictive capability of severe obstructive sleep apnea: A decision tree approach.Journal of clinical hypertension (Greenwich, Conn.) · 2024Article
- OSApredictor: A tool for prediction of moderate to severe obstructive sleep apnea-hypopnea using readily available patient characteristics.Computers in biology and medicine · 2024Article
- Assessing the health and economic burden of obesity-related complications in East-Asian populations: implementation of risk equations in the Core Obesity Model for Japan and model validation.BMJ public health · 2024Article
- Predicting the Risk of Sleep Disorders Using a Machine Learning-Based Simple Questionnaire: Development and Validation Study.Journal of medical Internet research · 2023Article
- Therapeutic effect of laparoscopic sleeve gastrectomy on obstructive sleep apnea and relationship of type 2 diabetes in Japanese patients with severe obesity.Journal of diabetes investigation · 2022Article
- Obstructive Sleep Apnea in a Clinical Population: Prevalence, Predictive Factors, and Clinical Characteristics of Patients Referred to a Sleep Center in Mongolia.International journal of environmental research and public health · 2021Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obstructive sleep apnea is a highly prevalent cyclic repetitive hypoxia-normoxia respiratory sleep disorder characterized by intermittent upper-airway collapse. It is mainly diagnosed using in-laboratory polysomnography. However, the time-spatial constraints of this procedure limit its application. To overcome these limitations, there have been studies aiming to develop clinical prediction formulas for screening of obstructive sleep apnea using the risk factors for this disorder. However, the applicability of the formula is restricted by the group specific factors included in it. Therefore, we aimed to assess the risk factors for obstructive sleep apnea and develop clinical prediction formulas, which can be used in different situations, for screening and assessing this disorder. We enrolled 3,432 Asian adult participants with suspected obstructive sleep apnea who had successfully undergone in-laboratory polysomnography. All parameters were evaluated using correlation analysis and logistic regression. Among them, age, sex, hypertension, diabetes mellitus, anthropometric factors, Berlin questionnaire and Epworth Sleepiness Scale scores, and anatomical tonsil and tongue position were significantly associated with obstructive sleep apnea. To develop the clinical formulas for obstructive sleep apnea, the participants were divided into the development (n = 2,516) and validation cohorts (n = 916) based on the sleep laboratory visiting date. We developed and selected 13 formulas and divided them into those with and without physical examination based on the ease of application; subsequently, we selected suitable formulas based on the statistical analysis and clinical applicability (formula including physical exam: sensitivity, 0.776; specificity, 0.757; and AUC, 0.835; formula without physical exam: sensitivity, 0.749; specificity, 0.770; and AUC, 0.839). Analysis of the validation cohort with developed formulas showed that these models and formula had sufficient performance and goodness of fit of model. These tools can effectively utilize medical resources for obstructive sleep apnea screening in various situations.
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