SLEEP 2011 Abstract Supplement

B. Clinical Sleep Science III. Sleep Disorders – Insomnia
nia. In this study, we assessed relationship of polysomnographic determined
sleep, especially SWS amount, and body mass index (BMI) in
patients with insomnia.
Methods: One hundred forty one insomnia sufferers and 55 health volunteers
completed overnight polysomnographic recording, and data of
height and body weight were also collected. The measures of total sleep
time, sleep efficiency, sleep latency, percentage of N1, 2 and 3 (SWS),
rapid eye movement sleep (REMS), and apnea/hypopnea index (AHI)
were analyzed.
Results: No significant correlation was obtained between total sleep
time and BMI among insomniacs and among volunteer individuals.
Compared to volunteers, insomnia patients exhibited significant increases
in sleep latency and N1 percentage, and decreases in total sleep
time, SWS and REMS percentage, but no difference in BMI. Based on
values of SWS percentage, we divided insomnia into three groups of
short (7.2±3.2%), intermediate (14.7±1.8%) and long (26.6±5.9%) SWS
groups, and each group had 47 subjects. We found that short SWS group
had significantly greater BMI (23.3±3.0) than long SWS (21.4±2.4), no
difference to intermediate SWS group (22.9±2.6). Further analysis with
linear multiple regression showed that reduction of SWS was significantly
related to increase of BMI in insomnia patients, not in volunteers
after control confounders (e.g, age, sex and AHI).
Conclusion: The finding may suggest that poor quality of sleep in terms
of reduction in SWS percentage may associate with higher BMI in insomnia
patients.
Support (If Any): Chinese National Science Foundation 30870891/
C090302 and 30801528/C190701.
0547
SLEEP ARCHITECTURE PREDICTS THE MISMATCH
BETWEEN SUBJECTIVE AND OBJECTIVE SLEEP
DURATION
Bianchi MT, Williams KL, McKinney S, Ellenbogen JM
Neurology, Massachusetts General Hospital, Boston, MA, USA
Introduction: Patient self-report of sleep duration may not reflect objective
measurement. Improved understanding of the relation between
sleep architecture (stages, fragmentation, etc) and subjective-objective
mismatch might yield important diagnostic and prognostic information.
We hypothesized that the degree of mismatch among insomnia patients
would correlate with metrics of sleep fragmentation.
Methods: We performed a retrospective analysis of ~1000 patients undergoing
diagnostic polysomnography at our center. Patients completed
a post-study estimate of sleep latency, total sleep time, and certainty regarding
each answer. We excluded those with neurological or psychiatric
diseases, or those taking any medication influencing sleep (final n=312).
Insomnia category was defined by self-reported on intake questionnaire,
yielding 3 groups: insomnia alone, sleep apnea alone (AHI >5), or both.
Results: While a mismatch between subjective report of sleep (latency
and total sleep time) was evident in all groups, it was most pronounced
in insomnia patients who more substantially underestimated their
sleep. We found significant correlations between subjective-objective
mismatch of total sleep time, and fragmentation indices (such as EEG
arousals, brief awakenings, sleep efficiency, periodic leg movements,
and respiratory events) (0.2 to 0.35, Spearman’s R). The extent of sleep
underestimation was inversely related to certainty, suggesting a tendency
toward pessimism when guessing. However, errors in latency showed
only small correlation with errors in total sleep, arguing against a general
“exaggerator” phenotype. We also observed that subjective sleep duration
(across a range of accuracy) correlated best with the duration of
REM sleep and of N2. We present different weighting schemes applied
to sleep stage metrics to use architecture to predict self-reported sleep
duration.
Conclusion: Subjective-objective mismatch, which was common in
patients reporting insomnia, correlated with several fragmentation metrics.
Additionally, the prediction of self-reported sleep duration based on
sleep stages suggests possible mechanistic links between sleep architecture
and subjective estimation of sleep duration.
Support (If Any): Department of Neurology, MGH, and the Clinical
Investigator Training Program: Harvard/MIT Health Sciences and Technology
- Beth Israel Deaconess Medical Center, in collaboration with
Pfizer, Inc. and Merck &Co (MTB)
0548
THE FIRST REM SLEEP PERIOD: LATENCY AND
DURATION AS INDICATORS OF FIRST NIGHT EFFECTS
IN GOOD SLEEPERS AND OF REVERSE FIRST NIGHT
EFFECTS IN INSOMNIA SUFFERERS
D. Pérusse A 1 , Ouellet D 1 , Turcotte I 1,2 , Bastien CH 1,2
1
École de psychologie, Université Laval, Québec, QC, Canada, 2 Centre
de Recherche Université Laval Robert-Giffard, Québec, QC, Canada
Introduction: While first night effects (FNE) are often observed in good
sleepers (GS), individuals with insomnia (INS) are more susceptible to
reverse FNE (RFNE). Sleep efficacy, sleep onset latency and total REM
time are habitually used to quantify these effects. The present study is
aimed at evaluating if the first night spent in the sleep laboratory could
affect REM onset latency (REML) and duration of the first REM sleep
period (REMD). GS and INS will be compared on these measures and
INS subdivided in paradoxical (IPA) and psychophysiological insomnia
(IPS).
Methods: 33 IPS (Mean age=39.5), 21 IPA (Mean age=39.0) and 43 GS
(Mean age=35.3) completed four consecutive PSG nights in the laboratory.
The first three nights (N1, N2 and N3) were used in this study.
REML was defined as the duration between the first epoch of Stage 2
and the first epoch of REM sleep. REMD was computed by subtracting
the start time from the end time of this period.
Results: Repeated measures ANOVAs (3x3; Groups x Nights) were performed.
A main effect of night was found for REML (p ≤ .001), results
showing a night to night decrease in REML. Mean and (SD) were respectively
for IPS: [N1=112.4 (76.2), N2=95.7 (55.6), N3=78.0 (33.7)];
for IPA: [N1=97.7 (37.7), N2=92.4 (47.1), N3=71.5 (35.7)] and for GS:
[N1=87.8 (36.2), N2=86.5 (46.4), N3=79.1 (35.7)]. No other significant
main effects or interactions were found for REML or REMD.
Conclusion: Results showed that experience of sleeping in the laboratory
had an effect on REML. However, nightly changes in latency of the
first REM period may not be an adequate indicator of FNE and RFNE
since status (being good sleepers or suffering from insomnia) was not
related to observed changes. The clinical relevance of these changes remains
to be investigated.
Support (If Any): Supported by the Canadian Institute of Health Research.
0549
THE ASSOCIATION BETWEEN PRE-SLEEP SUBJECTIVE
AROUSAL AND PHYSIOLOGICAL MEASURES OF AROUSAL
DURING SLEEP-ONSET PERIOD IN PATIENTS WITH
PRIMARY INSOMNIA AND NORMAL SLEEPERS
Huang Y 1 , Yang C 1,2 , Jan Y 1,3 , Tsai M 1
1
Psychology, NCCU, Taipei, Taiwan, 2 The Research Center for Mind
Brain and Learning, NCCU, Taipei, Taiwan, 3 Sleep Center, Taipei
Medical University Hospital, Taipei, Taiwan
Introduction: Hyperarousal has been recognized to be a major factor
for insomnia. However, the term “arousal” was measured differently
for different studies. The present study is to explore the associations of
subjective ratings of somatic and cognitive arousal with physiologically
arousal as measured by EEG and heart rate variability (HRV) prior and
after sleep onset.
Methods: 15 patients with primary insomnia (10F; mean age=36.6) and
15 normal sleepers (8F; mean age=34.2) underwent one night of PSG
recording in a sleep laboratory. They completed the Pre-sleep Arousal
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SLEEP, Volume 34, Abstract Supplement, 2011