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Psychotic-like experiences (PLEs) are prevalent occurrences deemed comparable with the symptoms of psychosis, but not sufficiently severe to warrant a diagnosis upon clinical presentation. Their presence is associated with several adverse clinical outcomes: the onset of various common mental health disorders (e.g. anxiety, mood, substance abuse), poorer functioning, non-remission and relapse. Sleep and circadian rhythm disruption (SCRD) is observed in 30-80% of patients with psychosis. The omnipotence of SCRD across all phases of the disorder (including the prodromal, acute, chronic and residual phases) raises the question as to whether SCRD may directly contribute to the development of psychosis. Assuming that PLEs are along the same continuum to developing psychosis, a logical next step to further disentangle the sleep-psychosis relationship is to examine whether SCRD relates to the experience of PLEs and whether this relationship is bi-directional. This thesis begins by examining the core predictions made by a continuum model of understanding psychosis and how specific parameters of sleep may influence PLEs. A smaller high-definition cross-sectional study follows, examining biological underpinnings (electroencephalography (EEG), electrocardiography (ECG), endogenous melatonin rhythms and actigraphy) of a complaint of poor sleep and their relation to the occurrence of PLEs. We then refocus on which parameters of sleep are most integral to the sleep-PLE relationship and close with an investigation of how Hypothalamic Pituitary Adrenal (HPA) axis activity may further our knowledge of this relationship. The findings of this thesis demonstrate specificity in the parameters of sleep shown to impact certain PLEs. The importance of objective sleep and biologically driven measures in this line of research are underscored, with group differences in EEG, ECG and melatonin. This thesis also highlights dissociative symptomatology as a candidate mediator for the sleep-psychosis relationship, and emphasises the ties between paranoia and negative affect. Finally, this thesis also illuminates the challenges of examining the relationship between sleep and PLEs in isolation, and suggests that they must be considered within the broader framework of co-existing mental health problems.

Fibromyalgia syndrome (FMS) is a disorder characterised by chronic widespread pain, non-restorative sleep, fatigue and daytime dysfunction. Occurring in 2-5% of the population, the aetiology is largely unknown. Sleep dysfunction occurs in over 90% of FMS patients. While research has shown that both the macrostructure and microstructure of sleep may be altered, there remain inconsistencies in the polysomnographic (PSG) findings, and wide variations in methodological approaches. Few studies have controlled for symptom duration or the time elapsed between diagnosis and PSG sleep assessments. In addition, while psychometric analyses have suggested a distinctive FMS psychological profile (which includes higher levels of depressive symptoms, anxiety and fatigue) few studies have simultaneously, and thoroughly examined sleep and psychological status in the same participants. A frequently reported alteration found in the sleep microstructure of FMS patients is the alpha-delta sleep anomaly, characterised by an increase in alpha wave activity during slow wave sleep. Originally considered a possible neurological contribution to FMS, whether the alpha-delta sleep anomaly is fundamental to the development of fibromyalgia syndrome, or results mainly from the pain experience of FMS patients remains unknown. No previous study has directly compared the sleep of FMS and other (non-FMS) patients experiencing similar levels of chronic pain and sleep dysfunction. The present study was designed to examine sleep macrostructure and microstructure in FMS patients, and evaluate the role of the alpha-delta sleep anomaly as either a possible contributor to fibromyalgia syndrome, or a likely consequence of pain experience. In order to explore these relationships, detailed sleep, activity and psychological profiles were compared in 3 groups: 1) FMS patients (n = 19); 2) osteoarthritis patients with sleep disturbance (n = 17); and non-clinical (normal healthy) adults (n = 10). In order to standardise diagnostic reliability and symptom chronicity, the FMS group was recruited from a single rheumatology facility immediately following diagnosis. Guided by a series of formal research questions, analyses compared sleep macrostructure (using American Academy of Sleep Medicine criteria), sleep microstructure (using spectral analysis), and a range of psychological variables (including pain experience, sleepiness, fatigue, depression, anxiety, perceived social support, health locus of control, pain catastrophizing and personality). The results indicated that the alpha-delta sleep anomaly is not unique to FMS, but appears to be a feature found in the sleep of normal healthy adults and (to a greater extent) those with FMS and osteoarthritis. The incidence of the anomaly was statistically similar in both clinical (FMS and osteoarthritis) groups, a pattern consistent of its being a secondary feature of pain, rather than a primary abnormality of FMS. Overall, the psychometric assessments of state and trait anxiety and depression better discriminated between the three groups than did the sleep variables. Nevertheless, on measures of sleep, perceived social support, health locus of control, and pain catastrophizing, FMS and osteoarthritis patients were not significantly different, though both clinical groups differed on these variables from healthy controls.

Obstructive Sleep Apnea (OSA) is a common pediatric breathing disorder which leads to complete or partial obstruction of the airway while sleeping. It occurs in pediatric patients due to enlarged tonsils (tonsillitis), obesity, cranio-facial abnormalities and facial muscle-related disorders that lead to hypotonia thereby resulting in obstruction of the airway. Polysomnography (PSG) is the gold standard overnight systemic study to diagnose sleep apnea. The quality of data obtained from various sensors in an overnight PSG is important for good diagnosis, but sometimes the data obtained from the thermistor sensor is usually corrupted by the use of a pacifier by pediatric patients that may use them during the study. Hence the corrupted data is discarded and not used for analysis. This causes a problem as the thermistor data captures apnea (complete reduction of airflow) and hypopnea (partial reduction of airflow) events and can lead to an incorrect Apnea Hypopnea Index (AHI) which is the total number of apnea and hypopnea events in an hour of the study. In the first objective, we set up a Bayesian framework to compute the probability of having an apnea and hypopnea event while taking into consideration the data from other sensors from the artifact-free part of the data and applied that probability to artifact part of the data. This determined the probability of the number of events that could be hidden behind those artifacts and in turn led to a revised AHI score which is usually higher than the actual score. This is of great value to the physician as the AHI score plays a major role in determining the standard of care or the diagnostic procedure that will be given to the patient after the PSG. As an example, for one particular patient a score of 4 was increased to greater than 5, and would have led to a different treatment plan.The second objective of the study was to use signal processing techniques to remove the artifacts from the thermistor data. This would prevent them from completely discarding the data while taking cues from other sensors on the possibility of any apnea/hypopnea events in that segment. The final objective of this dissertation was to develop a simple yet smart instrument to collect the airflow data without picking up any artifacts while the pacifier was being used by the patient. These three objectives seek to provide an immediate or near term solution to the problem without changing or compromising the legacy system or the gold standard PSG.

Abstract Background: Sleep disturbances and deprivation are known to exist in the critically ill patient. Over a 24-hour period, the critically ill can have 7-9 hours of sleep, but as much as 50% of that sleep can occur during daytime hours, signifying significant sleep fragmentation. Furthermore, some critically ill patients have been found to have abnormal brain waves that obliterate normal sleep architecture. These patients are without conventional sleep markers exhibiting no Stage II sleep spindles, minimal rapid eye movement sleep, and slow background brain wave reactivity. Disrupted sleep has been associated with delirium, weakened immune system, impaired wound healing, nitrogen imbalance, and negative cardiac, pulmonary, and neurological consequences which may all lead to negative patient outcomes. Objective: The objective of this dissertation was to explore factors and outcomes associated with sleep disturbances in critically ill patients. The state of knowledge related to sleep and delirium in critically ill patients were explored. The tools and challenges of measuring sleep in patients while in the intensive care unit (ICU) were also explored. Methods: Using a data base from retrospective chart review of 84 subjects, factors and outcomes related to the presence or absence of sleep in critically ill patients were explored. Literature reviews determined the state of knowledge related to sleep and delirium and the measurement of sleep in critically ill patients. Results. Severity of disease was significantly associated the absence of sleep architecture in both the continuous electroencephalogram (cEEG) 1 to 2- and 1 to 5-day groups. Propofol was significantly associated with the presence or absence of sleep architecture in the day 1-2 group. After adjusting for age and medications, serum creatinine and neurologic physiologic state during days 1 to 2 of cEEG are factors associated with no sleep architecture using bi-variate analysis. Multivariate logistic regression adjusting for age and medications during Days 1-2 cEEG found abnormal serum creatinine to be statically significant. After adjusting for age and medications, encephalopathy and developmental disability were factors significantly associated with no sleep architecture in the Day 1-5 group. . Multivariate logistic regression adjusting for age and medication during days 1-5 cEEG found the physiologic states of encephalopathy and developmental disability to be significantly associated with the absence of sleep architecture. The patient outcomes of increased mechanical ventilation days, ICU length of stay and hospital length of stay were associated significantly with no sleep architecture during Days 1-2 cEEG. In the 1-5 Days cEEG group, hospital length of stay was significantly associated with no sleep architecture. Post-hospitalization transfer location was associated with no sleep architecture for both cEEG groups. Discharge to home was associated with the presence of sleep architecture. Conclusions: Certain patient characteristics are associated with the presence or absence of sleep architecture. The presence or absence of sleep architecture may impact patient outcomes. The exploratory study indicates that future prospective research with larger sample sizes and sleep architecture specifics is needed to advance the state of knowledge. While delirium theoretically may be related to sleep disturbances, more research is needed to determine if a correlation exists. Measuring sleep architecture in ICU patients can be challenging. Critical illness can impact the reliability and accuracy of sleep measurement tools including the gold standard polysomnography. Researchers need to be clear in their research goals and know the challenges related to the various sleep measurement tools.

BACKGROUND: Sleep problems affect people of all ages, race, gender, and socioeconomic classifications. Undiagnosed sleep disorders significantly and adversely impact a person’s level of academic achievement, job performance, and subsequently, socioeconomic status. Undiagnosed sleep disorders also negatively impact both direct and indirect costs for employers, the national government, and the general public. Sleepiness has significant implications on quality of life by impacting occupational performance, driving ability, cognition, memory, and overall health. The purpose of this study is to describe the prevalence of daytime sleepiness, as well as other quantitative predictors of sleep continuity and quality. METHODS: Population data from the CDC program in fatigue surveillance were used for this secondary analysis seeking to characterize sleep quality and continuity variables. Each participant underwent a standard nocturnal polysomnography and a standard multiple sleep latency test (MSLT) on the subsequent day. Frequency and chi-square tests were used to describe the sample. One-Way Analysis of Variance (ANOVA) was used to compare sleep related variables of groups with sleep latencies of minutes, 5-10 minutes, and >10 minutes. Bivariate and multivariate logistic regression was used to examine the association of the sleep variables with sleep latency time. RESULTS: The mean (SD) sleep latency of the sample was 8.8 (4.9) minutes. Twenty-four individuals had ≥1 SOREM, and approximately 50% of participants (n = 100) met clinical criteria for a sleep disorder. Individuals with shorter sleep latencies, compared to those with longer latencies reported higher levels of subjective sleepiness, had higher sleep efficiency percentages, and longer sleep times. The Epworth Sleepiness Scale, sleep efficiency percentage, total sleep time, the presence of a sleep disorder, and limb movement index were positively associated with a mean sleep latency of minutes. CONCLUSIONS: The presence of a significant percentage of sleep disorders within our study sample validate prior suggestions that such disorders remain unrecognized, undiagnosed, and untreated. In addition, our findings confirm questionnaire-based surveys that suggest a significant number of the population is excessively sleepy, or hypersomnolent. Therefore, the high prevalence of sleep disorders and the negative public health effects of daytime sleepiness demand attention. Further studies are now required to better quantify levels daytime sleepiness, within a population based sample, to better understand their impact upon morbidity and mortality. This will not only expand on our current understanding of daytime sleepiness, but it will also raise awareness surrounding its significance and relation to public health.

Timely detection of signs and symptoms of congestion to allow for clinical intervention and prevent patient hospitalisation for cardiac failure has been a challenge. The breathing disorders which can manifest in congestive cardiac failure may provide an avenue for sourcing markers of congestion; however monitoring systems capable of long-term observation of patients are required. Practical, long-term monitoring systems were developed for sleep disordered breathing (SDB) in cardiac failure and for the detection of respiratory changes that may relate to impending decompensation of cardiac failure. A portable sleep monitoring device (ApneaLink, ResMed Ltd.) was evaluated against polysomnography (PSG) to characterise SDB in cardiac failure. In clinically unstable cardiac failure, the AHI of in-patients was found to vary by up to 10 events/hr over 3 sleep studies. Whilst it was challenging for patients to adopt the ApneaLink as a home monitoring tool, the severity of SDB was found to traverse multiple categories for SDB severity in out-patients. PSG was impractical to monitor cardiac failure patients on more than 1 night in-hospital. As an alternative to PSG, a test regimen for assessing Cheyne-Stokes respiration (CSR) in the wake state was developed and evaluated. Whilst the test could not differentiate patients with CSR, further modifications to the test may realise this objective. Respiratory monitoring and SDB treatment devices were investigated for the detection of respiratory changes that may relate to decompensation of cardiac failure. The parameters derived from actigraphy based sleep assessment and positive airway pressure therapy devices were found to be feasible and apparently clinically beneficial surrogate measurement methods for pulmonary fluid status in cardiac failure patients. Decompensation of cardiac failure appeared to increase the probability of CSR by 70 %, increase AHI by 30 events/hr or increase respiratory rate by 25 % in the days or weeks prior to hospitalisation. The results highlight the kinetics of SDB in cardiac failure and the limitations of conventional intermittent review of SDB and cardiac failure. Serial respiratory monitoring may be a mechanism by which patient clinical state can be assessed on an ongoing basis in cardiac failure.

Epilepsy is the second most common chronic neurological disorder, affecting over 50 million people worldwide. Nearly 40% of cases are drug resistant. The prevalence of obstructive sleep apnea (OSA) is reportedly higher in epilepsy patients than the general population. Treatment has been shown to reduce seizures in some cases. We performed a cross-sectional study to assess the prevalence and predictors of OSA in adults with epilepsy. We hypothesized an association between OSA and seizure control such that more drug resistant patients were more likely to be affected. The prevalence of OSA was found to be 41.7%, markedly exceeding general population estimates. Multivariate modeling found age and body mass index to be OSA predictors. Measures of epilepsy severity were not associated with presence of OSA or OSA severity. Despite limitations, these observations raise questions regarding the impact of OSA on seizure control, alertness and quality of life in people with epilepsy.

Heart Rate Variability (HRV) currently is utilized when assessing the risk of mortality in individuals suffering from coronary heart disease or diabetic neuropathy. Research has shown that patients with Obstructive Sleep Apnea (OSA) also show a decrease in HRV, as well as an increase in sympathetic drive characterized by an increase in the low-frequency component of HRV. HRV, in conjunction with other indicators, may represent a non-invasive, low cost method for the confirmation of severity of OSA in some patients and therefore may represent an additional tool for the assessment of risk in these individuals. This becomes especially true when urinary catecholamines, fitness level, and quality of life (QOL) assessment are included. The purpose of this study was to determine if a correlation exists between severity of OSA as assessed by respiratory distress index (RDI) and the selected measures HRV, fitness, QOL, and catecholamine output. Subjects were 6 men and 5 women who were recently diagnosed with OSA by polysomnographic (PSG) study. HRV and blood pressure was measured during two consecutive trials consisting of 512 heartbeats. Catecholamine levels were determined by HPLC following 24-hour urine collection. Fitness levels were established following cycle ergometer testing and QOL following questionnaire completion. Subjects with lower weight, BMI, and neck circumference had significantly higher parasympathetic influence as analyzed through the amount of high frequency component of HRV (r =.738, .726, .789, respectively; p

บทนำ: ดนตรีบำบัดสามารถลดความตึงเครียดและความวิตกกังวลได้และถูกนำมาใช้เพื่อให้การนอนหลับดีขึ้น วัตถุประสงค์: เพื่อประเมินประสิทธิผลของดนตรีบำบัดต่อคุณภาพการนอนหลับ ความเครียดและความวิตกกังวลในผู้ป่วยที่เข้ารับการตรวจการนอนหลับ วิธีการศึกษา: การวิจัยแบบสุ่มตัวอย่างในผู้ป่วยที่เข้ารับการตรวจการนอนหลับ ณ โรงพยาบาลรามาธิบดี จำนวน 140 คน แบ่งเป็น 2 กลุ่ม คือ กลุ่มดนตรีบำบัดที่ได้ฟังดนตรีบรรเลง จำนวน 70 คน และกลุ่มควบคุม จำนวน 70 คน ซึ่งได้รับการบริการตามปกติ การประเมินใช้แบบสอบถามระดับความเครียดและความวิตกกังวล (Spielberger’s stress and anxiety level) ร่วมกับผลตรวจการนอนหลับ คือ ระยะเวลาที่เริ่มหลับ (Sleep latency) และประสิทธิภาพของการนอน (Sleep efficiency) ผลการศึกษา: จากกลุ่มตัวอย่างพบว่า ผู้ป่วยกลุ่มดนตรีบำบัดมีระดับความเครียดและความวิตกกังวลลดลงเมื่อเทียบกับกลุ่มควบคุม (35.6 ± 10.8 เปรียบเทียบกับ 47.6 ± 6.1; P < 0.01) และมีระดับความเครียดและความวิตกกังวลก่อนและหลังการตรวจการนอนหลับน้อยกว่ากลุ่มควบคุม (-12.4 ± 12.8 เปรียบเทียบกับ 0.52 ± 7.7; P < 0.01) แต่ไม่พบความแตกต่างของระยะเวลาที่เริ่มหลับและประสิทธิภาพของการนอน สรุป: ดนตรีบำบัดสามารถลดระดับความเครียดและความวิตกกังวลที่เกี่ยวเนื่องกับการตรวจการนอนหลับได้ ดังนั้นอาจเสนอเป็นทางเลือกในการผ่อนคลายให้กับผู้ป่วยที่มาตรวจการนอนหลับได้ อย่างไรก็ตาม ไม่พบว่าดนตรีบำบัดสามารถเปลี่ยนแปลงโครงสร้างการนอนหลับในผู้ป่วยเหล่านี้ได้