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      Validation of overnight oximetry to diagnose patients with moderate to severe obstructive sleep apnea

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          Abstract

          Background

          Polysomnography (PSG) is treated as the gold standard for diagnosing obstructive sleep apnea (OSA). However, it is labor-intensive, time-consuming, and expensive. This study evaluates validity of overnight pulse oximetry as a diagnostic tool for moderate to severe OSA patients.

          Methods

          A total of 699 patients with possible OSA were recruited for overnight oximetry and PSG examination at the Sleep Center of a University Hospital from Jan. 2004 to Dec. 2005. By excluding 23 patients with poor oximetry recording, poor EEG signals, or respiratory artifacts resulting in a total recording time less than 3 hours; 12 patients with total sleeping time (TST) less than 1 hour, possibly because of insomnia; and 48 patients whose ages less than 20 or more than 85 years old, data of 616 patients were used for further study. By further considering 76 patients with TST < 4 h, a group of 540 patients with TST ≥ 4 h was used to study the effect of insufficient sleeping time. Alice 4 PSG recorder (Respironics Inc., USA) was used to monitor patients with suspected OSA and to record their PSG data. After statistical analysis and feature selection, models built based on support vector machine (SVM) were then used to diagnose moderate and moderate to severe OSA patients with a threshold of AHI = 30 and AHI = 15, respectively.

          Results

          The SVM models designed based on the oxyhemoglobin desaturation index (ODI) derived from oximetry measurements provided an accuracy of 90.42-90.55%, a sensitivity of 89.36-89.87%, a specificity of 91.08-93.05%, and an area under ROC curve (AUC) of 0.953-0.957 for the diagnosis of severe OSA patients; as well as achieved an accuracy of 87.33-87.77%, a sensitivity of 87.71-88.53%, a specificity of 86.38-86.56%, and an AUC of 0.921-0.924 for the diagnosis of moderate to severe OSA patients. The predictive outcome of ODI to diagnose severe OSA patients is better than to diagnose moderate to severe OSA patients.

          Conclusions

          Overnight pulse oximetry provides satisfactory diagnostic performance in detecting severe OSA patients. Home-styled oximetry may be a tool for severe OSA diagnosis.

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          Most cited references31

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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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            Nocturnal pulse oximetry as an abbreviated testing modality for pediatric obstructive sleep apnea.

            To determine the utility of pulse oximetry for diagnosis of obstructive sleep apnea (OSA) in children. We performed a cross-sectional study of 349 patients referred to a pediatric sleep laboratory for possible OSA. A mixed/obstructive apnea/hypopnea index (MOAHI) greater than or equal to 1 on nocturnal polysomnography (PSG) defined OSA. A sleep laboratory physician read nocturnal oximetry trend and event graphs, blinded to clinical and polysomnographic results. Likelihood ratios were used to determine the change in probability of having OSA before and after oximetry results were known. Of 349 patients, 210 (60%) had OSA as defined polysomnographically. Oximetry trend graphs were classified as positive for OSA in 93 and negative or inconclusive in 256 patients. Of the 93 oximetry results read as positive, PSG confirmed OSA in 90 patients. A positive oximetry trend graph had a likelihood ratio of 19.4, increasing the probability of having OSA from 60% to 97%. The median MOAHI of children with a positive oximetry result was 16.4 (7.5, 30.2). The 3 false-positive oximetry results were all in the subgroup of 92 children who had diagnoses other than adenotonsillar hypertrophy that might have affected breathing during sleep. A negative or inconclusive oximetry result had a likelihood ratio of.58, decreasing the probability of having OSA from 60% to 47%. Interobserver reliability for oximetry readings was very good to excellent (kappa =.80). In the setting of a child suspected of having OSA, a positive nocturnal oximetry trend graph has at least a 97% positive predictive value. Oximetry could: 1) be the definitive diagnostic test for straightforward OSA attributable to adenotonsillar hypertrophy in children older than 12 months of age, or 2) quickly and inexpensively identify children with a history suggesting sleep-disordered breathing who would require PSG to elucidate the type and severity. A negative oximetry result cannot be used to rule out OSA.
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              An electrocardiogram-based technique to assess cardiopulmonary coupling during sleep.

              To evaluate a new automated measure of cardiopulmonary coupling during sleep using a single-lead electrocardiographic signal. Using training and test datasets of 35 polysomnograms each, we assessed the correlations of an electrocardiogram-based measure of cardiopulmonary interactions with respect to standard sleep staging, as well as to the cyclic alternating pattern classification. The pattern of coupling in 15 healthy individuals was also assessed. American Academy of Sleep Medicine Accredited Sleep Disorders Center. None. From a continuous, single-lead electrocardiogram, we extracted both the normal-to-normal sinus interbeat interval series and a corresponding electrocardiogram-derived respiration signal. Employing Fourier-based techniques, the product of the coherence and cross-power of these 2 simultaneous signals was used to generate a spectrographic representation of cardiopulmonary coupling dynamics during sleep. This technique shows that non-rapid eye movement sleep in adults demonstrates spontaneous abrupt transitions between high- and low-frequency cardiopulmonary coupling regimes, which have characteristic electroencephalogram, respiratory, and heart-rate variability signatures in both health and disease. Using the kappa statistic, agreement with standard sleep staging was poor (training set 62.7%, test set 43.9%) but higher with cyclic alternating pattern scoring (training set 74%, test set 77.3%). A sleep spectrogram derived from information in a single-lead electrocardiogram can be used to dynamically track cardiopulmonary interactions. The 2 distinct (bimodal) regimes demonstrate a closer relationship with visual cyclic alternating pattern and non-cyclic alternating pattern states than with standard sleep stages. This technique may provide a complementary approach to the conventional characterization of graded non-rapid eye movement sleep stages.
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                Author and article information

                Contributors
                lungwen.hang@gmail.com
                charmaine@nutc.edu.tw
                jen801019@yahoo.com.tw
                jinchyr.hsu@msa.hinet.net
                shlin@ctust.edu.tw
                chung.w53@msa.hinet.net
                yfchen@ctust.edu.tw
                Journal
                BMC Pulm Med
                BMC Pulm Med
                BMC Pulmonary Medicine
                BioMed Central (London )
                1471-2466
                20 March 2015
                20 March 2015
                2015
                : 15
                : 24
                Affiliations
                [ ]Sleep Medicine Center, Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan
                [ ]Department of Respiratory Therapy, College of Health Care, China Medical University, Taichung, Taiwan
                [ ]Department of Beauty Science, National Taichung University of Science and Technology, Taichung, Taiwan
                [ ]Department of Health Services Administration, China Medical University, Taichung, Taiwan
                [ ]Department of Internal Medicine, Taipei Hospital, Ministry of Health and Welfare, New Taipei City, Taiwan
                [ ]Department of Management Information System, Central Taiwan University of Science and Technology, Taichung, Taiwan
                [ ]Department of Internal Medicine, Taichung Hospital, Ministry of Health and Welfare, Taichung, Taiwan
                [ ]Department of Healthcare Administration, Central Taiwan University of Science and Technology, Taichung, Taiwan
                [ ]Department of Dental Technology and Materials Science, Central Taiwan University of Science and Technology, Taichung, Taiwan
                Article
                17
                10.1186/s12890-015-0017-z
                4407425
                25880649
                1f3dec1e-ef81-45b0-949b-9117165abf32
                © Hang et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 21 September 2013
                : 4 March 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Respiratory medicine
                obstructive sleep apnea (osa),oximetry,support vector machine (svm),polysomnography (psg)

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