@article {784, title = {Polysomnography performed in the unattended home versus the attended laboratory setting--Sleep Heart Health Study methodology.}, journal = {Sleep}, volume = {27}, year = {2004}, month = {2004 May 01}, pages = {536-40}, abstract = {

STUDY OBJECTIVE: To compare polysomnographic recordings obtained in the home and laboratory setting.

DESIGN AND SETTING: Multicenter study comparing unsupervised polysomnography performed in the participant{\textquoteright}s home with polysomnography supervised at an academic sleep disorders center, using a randomized sequence of study setting. Sleep Heart Health Study (SHHS) standardized polysomnographic recording and scoring techniques were used for both settings.

PARTICIPANTS: 64 of 76 non-SHHS participants recruited from 7 SHHS field sites who had both a laboratory and home polysomnogram meeting acceptable quality criteria.

MEASUREMENTS AND RESULTS: Median sleep duration was greater in the home than in the laboratory (375 vs 318 minutes, respectively, P < .0001) as was sleep efficiency (86\% vs 82\%, respectively, P < .0024). Very small, but significant increases in percentage of rapid eye movement sleep and decreases in stage 1 sleep were noted in the laboratory. Employing multiple definitions of respiratory disturbance index (RDI), median RDI was similar in both settings (for example, RDI with 3\% desaturation: home 12.4, range 0.6-67; laboratory 9.5, range 0.1-93.4, P = .41). Quartile analysis of laboratory RDI showed moderate agreement with home RDI measurements. Based on the mean of laboratory and home RDI and using a cutpoint of 20, there was a biphasic distribution, with the RDI 3\% above 20 being more common in the recordings performed in the laboratory than in the home and below 20 being more common in the recordings performed in the home than in the laboratory. These differences could not be attributed to quality of recording, age, sex, or body mass index.

CONCLUSIONS: Using SHHS methodology, median RDI was similar in the unattended home and attended laboratory setting with differences of small magnitude in some sleep parameters. Differences in RDI between settings resulted in a rate of disease misclassification that is similar to repeated studies in the same setting.

}, keywords = {Adult, Aged, Body Mass Index, Clinical Laboratory Techniques, Cohort Studies, Health Status, Home Care Services, Humans, Middle Aged, Polysomnography, Sleep Apnea Syndromes, Sleep, REM}, issn = {0161-8105}, doi = {10.1093/sleep/27.3.536}, author = {Iber, Conrad and Redline, Susan and Kaplan Gilpin, Adele M and Quan, Stuart F and Zhang, Lin and Gottlieb, Daniel J and Rapoport, David and Resnick, Helaine E and Sanders, Mark and Smith, Philip} } @article {993, title = {Power spectral analysis of EEG activity during sleep in cigarette smokers.}, journal = {Chest}, volume = {133}, year = {2008}, month = {2008 Feb}, pages = {427-32}, abstract = {

BACKGROUND: Research on the effects of cigarette smoking on sleep architecture is limited. The objective of this investigation was to examine differences in sleep EEG between smokers and nonsmokers.

METHODS: Smokers and nonsmokers who were free of all medical comorbidities were matched on different factors, including age, gender, race, body mass index, and anthropometric measures. Home polysomnography was conducted using a standard recording montage. Sleep architecture was assessed using visual sleep-stage scoring. The discrete fast Fourier transform was used to calculate the EEG power spectrum for the entire night within contiguous 30-s epochs of sleep for the following frequency bandwidths: delta (0.8 to 4.0 Hz); theta (4.1 to 8.0 Hz); alpha (8.1 to 13.0 Hz); and beta (13.1 to 20.0 Hz).

RESULTS: Conventional sleep stages were similar between the two groups. However, spectral analysis of the sleep EEG showed that, compared to nonsmokers, smokers had a lower percentage of EEG power in the delta-bandwidth (59.7\% vs 62.6\%, respectively; p < 0.04) and higher percentage of EEG power in alpha-bandwidth (15.6\% vs 12.5\%, respectively; p < 0.001). Differences in the EEG power spectrum between smokers and nonsmokers were greatest in the early part of the sleep period and decreased toward the end. Subjective complaints of lack of restful sleep were also more prevalent in smokers than in nonsmokers (22.5\% vs 5.0\%, respectively; p < 0.02) and were explained, in part, by the differences in EEG spectral power.

CONCLUSIONS: Cigarette smokers manifest disturbances in the sleep EEG that are not evident in conventional measures of sleep architecture. Nicotine in cigarette smoke and withdrawal from it during sleep may contribute to these changes and the subjective experience of nonrestorative sleep.

}, keywords = {Electroencephalography, Female, Humans, Logistic Models, Male, Middle Aged, Polysomnography, Sleep, Smoking, Spectroscopy, Fourier Transform Infrared}, issn = {0012-3692}, doi = {10.1378/chest.07-1190}, author = {Zhang, Lin and Samet, Jonathan and Caffo, Brian and Bankman, Isaac and Punjabi, Naresh M} }