Polysomnography entails recording of physiologic signals during sleep that includes: electroencephalogram (EEG), electro-oculogram (EOG), electromyogram (EMG), nasal/oral airflow, respiratory effort, pulse oximetry, and electrocardiogram (EKG). The studies are scored using 30-second epochs to determine sleep/wake stages, apneas, hypopneas, and oxygen desaturation1. The apnea- hypopnea index, a measure of the severity of sleep apnea, represents the number of apneas and hypopneas divided by the total sleep time. For future multi-center collaborative research studies, it would be important to determine the inter-rater scoring reliability among sleep centers to assure uniform scoring of sleep studies2.
We aim to determine the inter-rater reliability of polysomnography (PSG) scoring among six sleep centers. Polysomnography will be scored using the definitions developed by the American Academy of Sleep Medicine (AASM) in 15 previously recorded sleep studies that have been de-identified. The AASM definitions1 are currently used among sleep centers world-wide. The participants of this study are the individuals who score the de-identified sleep recordings rather than the patients involved in the sleep studies.
Copies of 15 previously recorded PSGs will be de-identified using the same software used for the recording. This process is automated because all data during the sleep study is in digital format. After de-identification, the studies will then be converted to EDF (European Data Format) format to assure that these will be compatible with other types of sleep study scoring software used by the scorers.
The de-identified studies in EDF format will then be transferred to DVD and provided to the following 6 participating sleep centers:
- The Ohio State University Sleep Disorders Center, Columbus, OH, USA.
- Penn Sleep Centers (University of Pennsylvania), Philadelphia, PA, USA
- The University of Sydney, Sydney, Australia.
- Chang Gung Memorial Hospital, Taipei, Taiwan.
- University Hospital Berlin, Berlin, Germany.
- Landspitali University Hospital, Reykjavik, Iceland.
Each center will assign the de-identified studies to one scorer. The studies will be scored using 30-second epochs. Each epoch will be examined for sleep/wake stages, apneas, hypopneas, EEG arousals, and oxygen desaturation.
The individuals performing the scoring of the PSGs are designated sleep center personnel who normally perform this function within the context of a normal clinical operation. The scorers will be anonymous to the investigators since the data collected in excel format will not contain any personal information, but rather only the name of the center. In future studies involving the participating centers, these individuals will be the ones performing the scoring of the sleep studies.
1. Iber C, Ancoli-Israekl S, Chesson A, Quan S, authors; for the American Academy of Sleep Medicine. The AASM manual for the scoring of sleep and associate events: rules, terminology and technical specifications.2007.1st ed. Westchester, IL: American Academy of Sleep Medicine.
2.Quan SF, Howard, BV, Iber C, Kiley JP, Nieto FJ, O'Connor GT, Rapoport DM, Redline S, Robbins J, Samet JM, Wahl PW, 1997. The Sleep Heart Health Study: design, rationale, and methods. Sleep 20(12):1077-85.
Standardization of Sleep Questionnaire
Obstructive sleep apnea (OSA) is a common, complex disorder characterized by sleep-induced partial obstruction (hypopnea) and/or complete obstruction (apnea) of the upper airway (pharynx)1,2. OSA is one of the most common sleep disorders in developed nations, and has a higher incidence and prevalence in adults compared to children3,4. Typical signs and symptoms of OSA include disruptive snoring, witnessed apneas or gasping and unrefreshing sleep5.
The most cited prevalence statistics for OSA are those from the Wisconsin Sleep Cohort Study6,7 which indicate that 24% of middle-aged men and 9% of middle-aged women are affected8. Obstructive sleep apnea-hypopnea syndrome (OSAHS), with its additional criterion of daytime sleepiness, affects 4% of men and 2% of women in the general population and > 1% of preschool children. In selected populations the prevalence of OSA is significantly higher9. It appears that both the prevalence and clinical recognition of OSA have risen over the past two decades in developed nations7,10-12. This may reflect increasing population obesity and age, though differences in sampling methods, the techniques used for monitoring sleep, and in the definitions used to diagnose OSA all influence the estimated disease prevalence.
Obtaining information through questionnaires about specific disease, such as OSA, and its risk factors can often provide the most efficient data collection method, allowing a greater sample size and greater statistical power than would be possible with other more accurate measurement techniques. However, there are many sleep questionnaires in use by the epidemiological community which have been utilised for genetic studies of sleep apnea. Many have used different wording which have made comparisons between different populations difficult, thus illustrating that there is a need for a standardized instrument which would not only capture relevant sleep information but to also allow greater comparability of results across research being conducted.
This project is focussed on comparing the questions and wording commonly collected via sleep questionnaires in epidemiological and population-based studies today. This will be valuable for better defining the most relevant questions (and the best wording to use) when collecting phenotype information for investigation of sleep apnea.
1. Gastaut H, Tassinari C, Duron B. Polygraphic study of the episodic diurnal and nocturnal (hypnic and respiratory manifestations of the Pickwick syndrome. Brain Res 1966;1:167-186.
2. Remmers J, deGroot W, Sauerland E, Anch A. Pathogenesis of upper airway occlusion during sleep. J Appl Physiol. 1978;44:931-938.
3. American Thoracic Society. Standards for the diagnosis and care of patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 1995;152(5 Pt 2):S77-121.
5. Somers V, White D, Amin R, et al. Sleep apnea and cardiovascular disease: an American Heart Association/american College Of Cardiology Foundation Scientific Statement from the American Heart Association Council for High Blood Pressure Research Professional Education Committee, Council on Clinical Cardiology, Stroke Council, and Council On Cardiovascular Nursing. In collaboration with the National Heart, Lung, and Blood Institute National Center on Sleep Disorders Research (National Institutes of Health). Circulation. 2008;118:1080-1111.
6. Peppard PE, Young T, Palta M, Dempsey J, Skatrud J. Longitudinal study of moderate weight change and sleep-disordered breathing. Jama. 2000;284(23):3015-3021.
7. Peppard PE, Young T, Palta M, Skatrud J. Prospective study of the association between sleep-disordered breathing and hypertension. New England Journal of Medicine. May 11 2000;342(19):1378-1384.
8. Young T, Peppard PE, Gottlieb DJ. Epidemiology of obstructive sleep apnea: a population health perspective. Am J Respir Crit Care Med. 2002;165:1217-1239.
9. Flemons WW, McNicolas WT. Clinical prediction of the sleep apnea syndrome. Sleep Medicine Reviews. 1997;1(1):19-32.
10. Redline S, Young T. Epidemiology and natural history of obstructive sleep apnea. Ear Nose Throat J. Jan 1993;72(1):20-21, 24-26.
11. Visscher TL, Seidell JC. The public health impact of obesity. Annu Rev Public Health. 2001;22:355-375.
12. Yaggi H, Concato J, Kernan W, Lichtman J, Brass L, Mohsenin V. Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med. 2005;353:2034–2041.
Comparison of cephalometric and digital photography measures
Inventory - Standardized DNA collection and extraction
Content coming soon.