Literature DB >> 33529265

Risk factors and clinical prediction formula for the evaluation of obstructive sleep apnea in Asian adults.

Do-Yang Park1,2, Ji-Su Kim3, Bumhee Park3,4, Hyun Jun Kim1,2.   

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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Year:  2021        PMID: 33529265      PMCID: PMC7853448          DOI: 10.1371/journal.pone.0246399

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  48 in total

Review 1.  Risk factors for obstructive sleep apnea in adults.

Authors:  Terry Young; James Skatrud; Paul E Peppard
Journal:  JAMA       Date:  2004-04-28       Impact factor: 56.272

2.  The reliability and validity of the Korean version of the Epworth sleepiness scale.

Authors:  Yong Won Cho; Joo Hwa Lee; Hyo Kyung Son; Seung Hoon Lee; Chol Shin; Murray W Johns
Journal:  Sleep Breath       Date:  2010-04-01       Impact factor: 2.816

3.  Sleep-disordered breathing and cancer mortality: results from the Wisconsin Sleep Cohort Study.

Authors:  F Javier Nieto; Paul E Peppard; Terry Young; Laurel Finn; Khin Mae Hla; Ramon Farré
Journal:  Am J Respir Crit Care Med       Date:  2012-05-20       Impact factor: 21.405

4.  Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline.

Authors:  Vishesh K Kapur; Dennis H Auckley; Susmita Chowdhuri; David C Kuhlmann; Reena Mehra; Kannan Ramar; Christopher G Harrod
Journal:  J Clin Sleep Med       Date:  2017-03-15       Impact factor: 4.062

5.  Formula for predicting OSA and the Apnea-Hypopnea Index in Koreans with suspected OSA using clinical, anthropometric, and cephalometric variables.

Authors:  Seon Tae Kim; Kee Hyung Park; Seung-Heon Shin; Ji-Eun Kim; Chi-Un Pae; Kwang-Pil Ko; Hee Young Hwang; Seung-Gul Kang
Journal:  Sleep Breath       Date:  2017-04-29       Impact factor: 2.816

6.  Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine.

Authors:  Richard B Berry; Rohit Budhiraja; Daniel J Gottlieb; David Gozal; Conrad Iber; Vishesh K Kapur; Carole L Marcus; Reena Mehra; Sairam Parthasarathy; Stuart F Quan; Susan Redline; Kingman P Strohl; Sally L Davidson Ward; Michelle M Tangredi
Journal:  J Clin Sleep Med       Date:  2012-10-15       Impact factor: 4.062

7.  Risk factors for obstructive sleep apnea-related hypertension in police officers in Southern China.

Authors:  Minxia Pan; Qiong Ou; Baixin Chen; Zuogeng Hong; Hui Liu
Journal:  J Thorac Dis       Date:  2019-10       Impact factor: 2.895

8.  A clinical prediction formula for apnea-hypopnea index.

Authors:  Mustafa Sahin; Cem Bilgen; M Sezai Tasbakan; Rasit Midilli; Ozen K Basoglu
Journal:  Int J Otolaryngol       Date:  2014-10-01

9.  The Relationship between Diabetes-Related Complications and Obstructive Sleep Apnea in Type 2 Diabetes.

Authors:  Nantaporn Siwasaranond; Hataikarn Nimitphong; Areesa Manodpitipong; Sunee Saetung; Naricha Chirakalwasan; Ammarin Thakkinstian; Sirimon Reutrakul
Journal:  J Diabetes Res       Date:  2018-03-07       Impact factor: 4.011

10.  Clinical implications of sleep disordered breathing in acute myocardial infarction.

Authors:  Doron Aronson; Morad Nakhleh; Tawfiq Zeidan-Shwiri; Michael Mutlak; Peretz Lavie; Lena Lavie
Journal:  PLoS One       Date:  2014-02-11       Impact factor: 3.240

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  3 in total

1.  Obstructive Sleep Apnea in a Clinical Population: Prevalence, Predictive Factors, and Clinical Characteristics of Patients Referred to a Sleep Center in Mongolia.

Authors:  Shuren Dashzeveg; Yasunori Oka; Munkhjin Purevtogtokh; Enkhnaran Tumurbaatar; Battuvshin Lkhagvasuren; Otgonbayar Luvsannorov; Damdindorj Boldbaatar
Journal:  Int J Environ Res Public Health       Date:  2021-11-16       Impact factor: 3.390

2.  Therapeutic effect of laparoscopic sleeve gastrectomy on obstructive sleep apnea and relationship of type 2 diabetes in Japanese patients with severe obesity.

Authors:  Shingo Yanari; Akira Sasaki; Akira Umemura; Yasushi Ishigaki; Haruka Nikai; Tsuguo Nishijima; Shigeru Sakurai
Journal:  J Diabetes Investig       Date:  2022-02-08       Impact factor: 3.681

Review 3.  Enabling Early Obstructive Sleep Apnea Diagnosis With Machine Learning: Systematic Review.

Authors:  Daniela Ferreira-Santos; Pedro Amorim; Tiago Silva Martins; Matilde Monteiro-Soares; Pedro Pereira Rodrigues
Journal:  J Med Internet Res       Date:  2022-09-30       Impact factor: 7.076

  3 in total

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