Supine sleep patterns as a part of phenotyping patients with sleep apnea—a pilot study

Purpose Polysomnography (PSG) is considered the best objective study to diagnose and quantify sleep disorders. However, PSG involves multiple electrodes and is usually performed in a sleep laboratory that in itself may change the physiology of sleep. One of the parameters that can change during PSG is the sleep position, leading to more supine sleep. The aim of this study was to quantify the amount of supine sleep during PSG and compare it to consecutive nights of a home sleep apnea test (HSAT) in the same patients. Methods This prospective study evaluated 22 consecutive patients undergoing PSG followed by HSAT. Sleep position was analyzed during PSG and subsequently on 2 to 6 nights (mean 3.7 nights) at home, and the amount of supine sleep was recorded during each night. Results Of 22 patients, there were 12 men (55%). The median age was 60.0 years for women and 45.5 years for men. Median proportion of supine sleep during PSG and HSAT was 61% and 26% (p < 0.001), respectively. Four “phenotypes” were identified according to their sleep position during PSG and HSAT, with 5 patients sleeping mainly supine during all nights, 7 patients sleeping mainly non-supine during all nights, 3 patients sleeping in different positions during each night, and 7 patients sleeping supine during PSG but non-supine at home, during HSAT. Conclusions There is a higher proportion of supine sleep during PSG compared to home sleep. We identified a subgroup of patients who slept mainly supine during PSG and mainly non-supine during HSAT. PSG may overestimate OSA severity in a specific phenotype of patients.

Insomnia with physiological hyperarousal is associated with lower weight: a novel finding and its clinical implications

Previous studies on the association of insomnia with body mass index (BMI) have been controversial. Physiological hyperarousal, the key pathological mechanism of insomnia, may be an important reason for different findings. We explored whether insomnia with physiological hyperarousal measured by the multiple sleep latency test (MSLT) is associated with body-weight differences. A total of 185 normal sleepers and 440 insomniacs were included in this study. Insomnia was defined by standard diagnostic criteria with symptoms lasting ≥6 months. All subjects underwent one night of laboratory polysomnography followed by a standard MSLT. We used the median MSLT value (i.e., ≥14 min) to define physiological hyperarousal. BMI was based on measured height (cm) and weight (kg) during the subjects’ sleep laboratory visit. BMI > 25 kg/m2 was defined as overweight, while BMI < 18.5 kg/m2 was defined as underweight. After controlling for confounders, the odds of lower weight rather than overweight were significantly increased among insomnia patients with increased MSLT: insomnia with MSLT 14–17 min and MSLT > 17 min increased the odds of lower weight by approximately 89% (OR = 1.89, 95% CI 1.00–4.85) and 273% (OR = 3.73, 95% CI 1.51–9.22) compared with normal sleepers, respectively. In contrast, insomnia in patients with MSLT 11–14 min and 8–11 min was not different from normal sleepers in terms of body weight. Insomnia associated with physiological hyperarousal, the most severe phenotype of chronic insomnia, is associated with higher odds of lower weight and underweight compared with normal sleepers. This is a novel finding consistent with previous physiologic data and has significant clinical implications.

P056 Using Polysomnography in Young People with Borderline Personality Disorder: A Pilot and Feasibility Study

Introduction Few studies have assessed sleep in young people (aged 15–25 years) with BPD using polysomnography. The feasibility of using polysomnography in this population might be questioned due to polysomnography’s invasiveness, anxiety and sensory sensitivities in BPD, and misconceptions that individuals with BPD are uncooperative and non-compliant. This study aimed to provide pilot sleep quality and architecture data and assess polysomnography feasibility. Method Participants were 13 females aged 15–25, 7 (Mage = 19.97, SD = 3.15) with BPD and 6 age-matched healthy controls (Mage = 20.13, SD = 3.31). Participants completed two non-consecutive nights of polysomnography monitoring (second night’s data were used in analyses). Participants were given the option of completing polysomnography monitoring at home or in a sleep laboratory. Results Young people with BPD displayed less arousals across the night and specifically during NREM sleep compared with healthy young people. All other sleep parameters were comparable across groups. There was considerable heterogeneity among participant preferences for in-home vs. sleep laboratory-based monitoring, due to comfort, safety, convenience, interest in seeing a sleep laboratory, or their living situation (eg. presence of bed partner at home). Anxiety was identified as a potential barrier to polysomnography research in this population. Discussion There were some indications of more consolidated sleep in BPD, which might reflect a greater sleep need in this population. The feasibility and tolerability of in-home and sleep laboratory-based polysomnography were demonstrated. Future protocols should incorporate ways to minimise anxiety, for example through providing a choice of monitoring location.

P123 Accuracy and Reliability of the Transcutaneous Carbon Dioxide (TcCO2) Signal in the Sleep Laboratory

Carbon Dioxide (CO2) monitoring is an essential part of assessing and treating disorders of hypoventilation in the sleep laboratory. While reliablity issues have been previously reported with the Transcutaneous Carbon Dioxide (TcCO2) signal, there is limited data assessing the validity of this signal or its trend in the sleep laboratory context. Therefore, this study aimed to investigate the change in TcCO2 accuracy from the beginning to the end of the sleep study in real world conditions across two different Victorian public hospital sleep laboratories that used two different TcCO2 monitors. The sample included 13 consecutive patients from Monash Health and 44 consecutive patients from Alfred Health with an average age of 64 and 56 years respectively. Arterial Blood Gas (ABG) measurements were taken prior to and following each sleep study and compared concurrently with the TcCO2 value. Bland-Altman analysis revealed an average difference between TcCO2 and PaCO2 of 3.29mmHg with agreement between -11.44 and 16.64mmHg for the TCM4 device and 1.31mmHg with agreement between -7.64 and 9.05mmHg for the TCM5 device. When accuracy was compared across time points for each patient, 46% of patients had an overnight accuracy change of ≥ 8mmHg when using the TCM4 compared with 20% when using the TCM5. It was concluded that the TcCO2 signal was un-reliable across the different monitors and that the TcCO2 trend may be difficult to interpret with confidence without blood gas calibration at the commencement and conclusion of the sleep study.

Sleep in the Intensive Care Unit through the Lens of Breathing and Heart Rate Variability: A Cross-Sectional Study

Background. Full polysomnography, the gold standard of sleep measurement, is impractical for widespread use in the intensive care unit (ICU). Wrist-worn actigraphy and subjective sleep assessments do not measure sleep physiology adequately. Here, we explore the feasibility of estimating conventional sleep indices in the ICU with heart rate variability (HRV) and respiration signals using artificial intelligence methods. Methods. We used deep learning models to stage sleep with HRV (through electrocardiogram) and respiratory effort (through a wearable belt) signals in critically ill adult patients admitted to surgical and medical ICUs, and in covariate-matched sleep laboratory patients. We analyzed the agreement of the determined sleep stages between the HRV- and breathing-based models, computed sleep indices, and quantified breathing variables during sleep. Results. We studied 102 adult patients in the ICU across multiple days and nights, and 220 patients in a clinical sleep laboratory. We found that sleep stages predicted by HRV- and breathing-based models showed agreement in 60% of the ICU data and in 81% of the sleep laboratory data. In the ICU, deep NREM (N2 + N3) proportion of total sleep duration was reduced (ICU 39%, sleep laboratory 57%, p<0.01), REM proportion showed heavy-tailed distribution, and the number of wake transitions per hour of sleep (median = 3.6) was comparable to sleep laboratory patients with sleep-disordered breathing (median = 3.9). Sleep in the ICU was also fragmented, with 38% of sleep occurring during daytime hours. Finally, patients in the ICU showed faster and less variable breathing patterns compared to sleep laboratory patients. Conclusions. Cardiovascular and respiratory signals encode sleep state information, which can be utilized to measure sleep state in the ICU. Using these easily measurable variables can provide automated information about sleep in the ICU.

Olfaction-Related Factors Affecting Chemosensory Dream Content in a Sleep Laboratory

Mental activity in sleep often involves visual and auditory content. Chemosensory (olfactory and gustatory) experiences are less common and underexplored. The aim of the study was to identify olfaction-related factors that may affect the occurrence of chemosensory dream content. Specifically, we investigated the effects of all-night exposure to an ambient odour, participants’ appraisal of their current olfactory environment, their general propensity to notice odours and act on them (i.e., odour awareness), and their olfactory acuity. Sixty pre-screened healthy young adults underwent olfactory assessment, completed a measure of odour awareness, and spent three nights in weekly intervals in a sleep laboratory. The purpose of the first visit was to adapt to the experimental setting. On the second visit, half of them were exposed to the smell of vanillin or thioglycolic acid and the other half to an odourless control condition. On the third visit, they received control or stimulation in a balanced order. On each visit, data were collected twice: once from the first rapid eye movement (REM) stage that occurred after 3 a.m., and then shortly before getting up, usually from a non-REM stage. Participants were asked to report the presence of sensory dream content and to assess their current olfactory environment. Neither exposure, nor participants’ assessments of the ambient odour, or olfactory acuity affected reports of chemosensory dream content but they were more frequent in individuals with greater odour awareness. This finding may have implications for treatment when such experiences become unwanted or bothersome.

Dreams and Trauma Changes in the Manifest Dreams in Psychoanalytic Treatments – A Psychoanalytic Outcome Measure

Although psychoanalysts are interested in symptom reduction as an outcome, they are looking for instruments to measure sustaining changes in the unconscious mental functioning. In this article it is discussed that conceptually well-founded transformation of manifest dreams analyzed with precise empirical methods could be considered as a promising indicator for such therapeutic changes. We are summarizing a dream generation model by Moser and von Zeppelin which has integrated a large interdisciplinary knowledge base of contemporary dream and sleep research. Based on this model the authors have developed a valid and reliable coding system for analyzing manifest dreams, the Zurich Dream Process Coding System (ZDPCS). One exemplary dream from the beginning and one from the third year of a severely traumatized, chronic depressed patient from the LAC Depression Study collected in psychoanalytic sessions as well as in the sleep laboratory have been analyzed applying the ZDPCS. Authors hypothesize that transformation in dreams as measured with the ZDPCS is the result of memory processes of traumatic embodied memories in the state of dreaming.