Polysomnography Versus Home Sleep Study: Overview and Clinical Application

Madani, Mansoor; Frank, Marcella; Lloyd, Ryan; Dimitrova, Dessislava I.; Madani, Farideh

doi:10.1016/j.cxom.2007.06.002

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…[1][2][3][4][5][6] PSG can be conducted using in-home settings or sleep laboratories considering the advantages afforded by variability in the closeness of monitoring, the ability to correct technical problems in a timely manner, and control temperature, noise and other environmental factors to minimize systematic bias. Use of PSG in the home or laboratory setting has substantial costs for data acquisition and the time required for data processing while potentially imposing physical and psychological burdens on the participant.…”

Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

Sources of Variability in Epidemiological Studies of Sleep Using Repeated Nights of In-Home Polysomnography: SWAN Sleep Study

Zheng

Sowers

Buysse

et al. 2012

Journal of Clinical Sleep Medicine

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Study Objective: To quantify sources of night-to-night variability. Methods: This project was conducted in 285 middle-aged African American, Caucasian, and Chinese women from the Study of Women's Health Across the Nation (SWAN) Sleep Study living in Chicago, the Detroit area, Oakland, and Pittsburgh. The study used 3 repeated nights of in-home polysomnography (PSG) measures. Night 1 data included assessment of sleep staging, sleep apnea, and periodic limb movements, while Nights 2 and 3 focused on sleep staging. Results: Mean total sleep time (TST) increased substantially from 365 minutes on Night 1 to 391 minutes and 380 minutes, respectively, on Nights 2 and 3. Mean percent sleep effi ciency (SE%) for the 3 nights were 83%, 85%, and 85%, respectively. Night 1 sleep values were signifi cantly different than Nights 2 and 3 measures except for S2 (%), S1 (min), and Delta (S3+4)%. Nights 2 and 3 differences in variability were negligible. Obesity, past smoking, and fi nancial strain measures were associated with greater Night 1 vs. Night 2 or Night 3 differences. We concluded that there was signifi cant Night 1 vs. Nights 2 and 3 variability and, though relatively modest, it was suffi cient to bias estimates of association. Additionally, personal characteristics including smoking, obesity, and fi nancial strain increased night-to-night variability. Conclusions: This reports adds new information about between and within person sources of variation with in-home PSG and identifi es elements that are essential in the design and planning of future sleep studies of multi-ethnic groups in social and physiological transition states such as the menopause. Keywords S C I E N T I F I C I N V E S T I G A T I O N SP olysomnography (PSG) is widely used in clinical and epidemiological research settings to provide objective sleep measures.1-6 PSG can be conducted using in-home settings or sleep laboratories considering the advantages afforded by variability in the closeness of monitoring, the ability to correct technical problems in a timely manner, and control temperature, noise and other environmental factors to minimize systematic bias. Use of PSG in the home or laboratory setting has substantial costs for data acquisition and the time required for data processing while potentially imposing physical and psychological burdens on the participant.7 Given these considerations, it is important to ascertain how much and what kind of data must be collected, determine if more than a single night's data collection is required to describe sleep behaviors; and, identify personal characteristics associated with substantially increased within-person variation in sleep behaviors.Considering the number of data collection nights that are needed to provide unbiased estimates of sleep characteristics is often made more complex because of the impact of the "fi rst night" effect (FNE), generated from changes in the sleep envi-BRIEF SUMMARY Current Knowledge/Study Rationale: Use of repeated polysomnography (PSG) in the home or laboratory to descr...

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Section: S C I E N T I F I C I N V E S T I G a T I O N Smentioning

confidence: 99%

Sources of Variability in Epidemiological Studies of Sleep Using Repeated Nights of In-Home Polysomnography: SWAN Sleep Study

Zheng

Sowers

Buysse

et al. 2012

Journal of Clinical Sleep Medicine

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“…In addition, the PSG setup requires many sensors attached to the patient and a night of sleep in an unfamiliar hospital bed. This leads to an uncomfortable analysis and an inaccurate representation of an actual night of sleep in the patients home [10], [11]. To allow a more comfortable and representative analysis, while also enabling more patients to be tested and diagnosed patients to be continuously monitored, home sleep apnea tests (HSAT) are being developed.…”

Section: Introductionmentioning

confidence: 99%

Portable Detection of Apnea and Hypopnea Events Using Bio-Impedance of the Chest and Deep Learning

Steenkiste

Groenendaal

Dreesen

et al. 2020

IEEE J. Biomed. Health Inform.

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“…It can be used as a diagnostic tool as well as to assess therapeutic efficacy of a given treatment modality including weight loss, CPAP, oral appliances and MMA. It is usually done in a sleep clinic, as the patient should sleep at least for 4 hours, and the electroencephalogram (EEG), electrooculogram (EOG), electromyogram (EMG), and electrocardiogram (ECG) will be monitored [9].…”

Section: Diagnosismentioning

confidence: 99%

Telegnathic Surgery for Obstructive Sleep Apnea

Ameen¹

2015

A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

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Polysomnography Versus Home Sleep Study: Overview and Clinical Application

Cited by 5 publications

References 28 publications

Sources of Variability in Epidemiological Studies of Sleep Using Repeated Nights of In-Home Polysomnography: SWAN Sleep Study

Sources of Variability in Epidemiological Studies of Sleep Using Repeated Nights of In-Home Polysomnography: SWAN Sleep Study

Portable Detection of Apnea and Hypopnea Events Using Bio-Impedance of the Chest and Deep Learning

Telegnathic Surgery for Obstructive Sleep Apnea

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