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

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      1 , 2 , 3 , 3 , 4 , 1 , 2 , *

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          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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          Most cited references 48

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          The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research

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            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.

            The American Academy of Sleep Medicine (AASM) Sleep Apnea Definitions Task Force reviewed the current rules for scoring respiratory events in the 2007 AASM Manual for the Scoring and Sleep and Associated Events to determine if revision was indicated. The goals of the task force were (1) to clarify and simplify the current scoring rules, (2) to review evidence for new monitoring technologies relevant to the scoring rules, and (3) to strive for greater concordance between adult and pediatric rules. The task force reviewed the evidence cited by the AASM systematic review of the reliability and validity of scoring respiratory events published in 2007 and relevant studies that have appeared in the literature since that publication. Given the limitations of the published evidence, a consensus process was used to formulate the majority of the task force recommendations concerning revisions.The task force made recommendations concerning recommended and alternative sensors for the detection of apnea and hypopnea to be used during diagnostic and positive airway pressure (PAP) titration polysomnography. An alternative sensor is used if the recommended sensor fails or the signal is inaccurate. The PAP device flow signal is the recommended sensor for the detection of apnea, hypopnea, and respiratory effort related arousals (RERAs) during PAP titration studies. Appropriate filter settings for recording (display) of the nasal pressure signal to facilitate visualization of inspiratory flattening are also specified. The respiratory inductance plethysmography (RIP) signals to be used as alternative sensors for apnea and hypopnea detection are specified. The task force reached consensus on use of the same sensors for adult and pediatric patients except for the following: (1) the end-tidal PCO(2) signal can be used as an alternative sensor for apnea detection in children only, and (2) polyvinylidene fluoride (PVDF) belts can be used to monitor respiratory effort (thoracoabdominal belts) and as an alternative sensor for detection of apnea and hypopnea (PVDFsum) only in adults.The task force recommends the following changes to the 2007 respiratory scoring rules. Apnea in adults is scored when there is a drop in the peak signal excursion by ≥ 90% of pre-event baseline using an oronasal thermal sensor (diagnostic study), PAP device flow (titration study), or an alternative apnea sensor, for ≥ 10 seconds. Hypopnea in adults is scored when the peak signal excursions drop by ≥ 30% of pre-event baseline using nasal pressure (diagnostic study), PAP device flow (titration study), or an alternative sensor, for ≥ 10 seconds in association with either ≥ 3% arterial oxygen desaturation or an arousal. Scoring a hypopnea as either obstructive or central is now listed as optional, and the recommended scoring rules are presented. In children an apnea is scored when peak signal excursions drop by ≥ 90% of pre-event baseline using an oronasal thermal sensor (diagnostic study), PAP device flow (titration study), or an alternative sensor; and the event meets duration and respiratory effort criteria for an obstructive, mixed, or central apnea. A central apnea is scored in children when the event meets criteria for an apnea, there is an absence of inspiratory effort throughout the event, and at least one of the following is met: (1) the event is ≥ 20 seconds in duration, (2) the event is associated with an arousal or ≥ 3% oxygen desaturation, (3) (infants under 1 year of age only) the event is associated with a decrease in heart rate to less than 50 beats per minute for at least 5 seconds or less than 60 beats per minute for 15 seconds. A hypopnea is scored in children when the peak signal excursions drop is ≥ 30% of pre-event baseline using nasal pressure (diagnostic study), PAP device flow (titration study), or an alternative sensor, for ≥ the duration of 2 breaths in association with either ≥ 3% oxygen desaturation or an arousal. In children and adults, surrogates of the arterial PCO(2) are the end-tidal PCO(2) or transcutaneous PCO(2) (diagnostic study) or transcutaneous PCO(2) (titration study). For adults, sleep hypoventilation is scored when the arterial PCO(2) (or surrogate) is > 55 mm Hg for ≥ 10 minutes or there is an increase in the arterial PCO(2) (or surrogate) ≥ 10 mm Hg (in comparison to an awake supine value) to a value exceeding 50 mm Hg for ≥ 10 minutes. For pediatric patients hypoventilation is scored when the arterial PCO(2) (or surrogate) is > 50 mm Hg for > 25% of total sleep time. In adults Cheyne-Stokes breathing is scored when both of the following are met: (1) there are episodes of ≥ 3 consecutive central apneas and/or central hypopneas separated by a crescendo and decrescendo change in breathing amplitude with a cycle length of at least 40 seconds (typically 45 to 90 seconds), and (2) there are five or more central apneas and/or central hypopneas per hour associated with the crescendo/decrescendo breathing pattern recorded over a minimum of 2 hours of monitoring.
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              Estimation of the clinically diagnosed proportion of sleep apnea syndrome in middle-aged men and women.

              The proportion of sleep apnea syndrome (SAS) in the general adult population that goes undiagnosed was estimated from a sample of 4,925 employed adults. Questionnaire data on doctor-diagnosed sleep apnea were followed up to ascertain the prevalence of diagnosed sleep apnea. In-laboratory polysomnography on a subset of 1,090 participants was used to estimate screen-detected sleep apnea. In this population, without obvious barriers to health care for sleep disorders, we estimate that 93% of women and 82% of men with moderate to severe SAS have not been clinically diagnosed. These findings provide a baseline for assessing health care resource needs for sleep apnea.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysis
                Role: Data curationRole: Formal analysisRole: Methodology
                Role: ConceptualizationRole: Funding acquisitionRole: Supervision
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2 February 2021
                2021
                : 16
                : 2
                Affiliations
                [1 ] Department of Otolaryngology, Ajou University School of Medicine, Suwon, Republic of Korea
                [2 ] Sleep Center, Ajou University Hospital, Suwon, Republic of Korea
                [3 ] Office of Biostatistics, Ajou Research Institute for Innovative Medicine, Ajou University Medical Center, Suwon, Republic of Korea
                [4 ] Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea
                University of Catania, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Article
                PONE-D-20-23427
                10.1371/journal.pone.0246399
                7853448
                33529265
                © 2021 Park et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 2, Tables: 5, Pages: 15
                Product
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003725, National Research Foundation of Korea;
                Award ID: 2017R1E1A1A01074543
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003625, Ministry of Health and Welfare;
                Award ID: HC15C3415
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003725, National Research Foundation of Korea;
                Award ID: 2017R1C1B1007454
                Award Recipient :
                This research was supported by a National Research Foundation of Korea grant funded by the Korean Government (2017R1E1A1A01074543) and the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (HC15C3415) to HJ Kim. This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF- 2017R1C1B1007454) to DY Park.The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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