Sleep Clinic Research Articles

Fascia Ecosystem: A Step Forward in Sleep Engineering and Research.

Millions suffer from sleep disorders, and sleep clinics and research institutions seek improved sleep study methods. This paper proposes the Fascia Ecosystem for Sleep Engineering to improve traditional sleep studies. The Fascia Sleep Mask is more comfortable and accessible than overnight stays at a sleep center, and the Fascia Portal and Fascia Hub allow for home-based sleep studies with real-time intervention and data analysis capabilities.A study of 10 sleep experts found that the Fascia Portal is easy to access, navigate, and use, with 44.4% finding it very easy to access, 33.3% very easy to navigate, and 60% very easy to get used to. Most experts found the Fascia Portal reliable and easy to use.Moreover, the study analyzed physiological signals during various states of sleep and wakefulness in two subjects. The results demonstrated that the Fascia dataset captured higher amplitude spindles in N2 sleep (72.20 V and 109.87 V in frontal and parietal regions, respectively) and higher peak-to-peak amplitude slow waves in N3 sleep (93.51 V) compared to benchmark datasets. Fascia produced stronger and more consistent EOG signals during REM sleep, indicating its potential to improve sleep disorder diagnosis and treatment by providing a deeper understanding of sleep patterns.

Fully Automated Detection of Isolated Rapid-Eye-Movement Sleep Behavior Disorder Using Actigraphy.

Isolated rapid-eye-movement (REM) sleep behavior disorder (iRBD) is caused by motor disinhibition during REM sleep and is a strong early predictor of Parkinson's disease. However, screening questionnaires for iRBD lack specificity due to other sleep disorders that mimic the symptoms. Nocturnal wrist actigraphy has shown promise in detecting iRBD by measuring sleep-related motor activity, but it relies on sleep diary-defined sleep periods, which are not always available. Our aim was to precisely detect iRBD using actigraphy alone by combining two actigraphy-based markers of iRBD - abnormal nighttime activity and 24-hour rhythm disruption. In a sample of 42 iRBD patients and 42 controls (21 clinical controls with other sleep disorders and 21 community controls) from the Stanford Sleep Clinic, the nighttime actigraphy model was optimized using automated detection of sleep periods. Using a subset of 38 iRBD patients with daytime data and 110 age-, sex-, and body-mass-index-matched controls from the UK Biobank, the 24-hour rhythm actigraphy model was optimized. Both nighttime and 24-hour rhythm features were found to distinguish iRBD from controls. To improve the accuracy of iRBD detection, we fused the nighttime and 24-hour rhythm disruption classifiers using logistic regression, which achieved a sensitivity of 78.9%, a specificity of 96.4%, and an AUC of 0.954. This study preliminarily validates a fully automated method for detecting iRBD using actigraphy in a general population.Clinical relevance- Actigraphy-based iRBD detection has potential for large-scale screening of iRBD in the general population.

Automatic Detection of Chronic Insomnia from Polysomnographic and Clinical Variables Using Machine Learning.

Insomnia is defined subjectively by the presence and frequency of specific clinical symptoms and an association with distress. Although sleep study data has shown some weak associations, no objective test can currently be used to predict insomnia. The purpose of this study was to use previously reported and relatively crafted insomnia-related polysomnographic variables in machine learning models to classify groups with and without insomnia. Demographics, diagnosed depression, Epworth Sleepiness Scale (ESS), and features derived from electroencephalography (EEG), arousals, and sleep stages from 3,407 sleep clinic patients (2,617 without insomnia and 790 insomnia patients based on responses to a set of questions) were included in this analysis. The number of features were reduced using pair-wise correlation and recursive feature elimination. Predictive value of three machine learning models (logistic regression, neural network, and support vector machine) was investigated, and the best performance was achieved with logistic regression, yielding a balanced accuracy of 71%. The most important features in predicting insomnia were depression, age, sex, duration of longest arousal, ESS score, and EEG power in theta and sigma bands across all sleep stages. Results indicate potential of machine learning-based screening for insomnia using clinical variables and EEG.

Phrenic nerve stimulation for treatment of central sleep apnea

The prevalence of central sleep apnea (CSA) is rare in general population. However, CSA is prevalent in those with cardiovascular and cerebrovascular disorders. CSA may persist or even worsen with positive airway pressure therapy in some patients and phrenic nerve stimulation (PNS) offers an alternative treatment for patients with CSA. The device is implanted similar to a cardiac pacemaker and typically followed in the sleep clinic. Multiple studies have described the efficacy and safety of PNS. Improvements were seen in apnea hypopnea events, central events, arousals, and daytime sleepiness and maintained through 5 years. Safety demonstrated a 91% freedom from serious adverse events through 1 year. The physiologic approach and improvement in sleep metrics and quality of life with a strong safety profile make this therapy a good option for many patients with central sleep apnea.

Periodic Limb Movements of Sleep: A Survey on Polysomnographic Characteristics of Patients with Obstructive Sleep Apnea

Background and Objective: Periodic limb movements of sleep (PLMS) and obstructive sleep apnea (OSA) are two common sleep disorders that frequently co-occur in one subject. In this study, we evaluated the polysomnographic (PSG) features of patients with OSA with and without PLMS.
 Materials and Methods: Patients with OSA diagnosed by PSG who referred to our sleep clinic over 2 years were studied for PLMS during a standard diagnostic sleep study. PSG features including apnea-hypopnea index (AHI), oxygen desaturation index (ODI), and sleep quality were evaluated and compared between patients with OSA with and without PLMS.
 Results: We evaluated 122 patients with OSA, of whom 17 had comorbid PLMS. Mean sleep quality was significantly lower in patients with PLMS compared to those without PLMS (P < 0.05). There was no significant difference in terms of mean age, gender, arousal index (AI), ODI, and apnea/hypopnea between the two groups.
 Conclusion: Patients with OSA with PLMS comorbidity have remarkably lower sleep quality and this finding is independent of the severity of arousals or respiratory events. Proper evaluation, diagnosis, and treatment of PLMS comorbidity in patients with OSA might improve treatment response.

How reliable is a simplified MSLT nap termination protocol?

ObjectiveAccording to current practical guidelines, naps of the Mean Sleep Latency Test (MSLT) must be terminated 15 min after sleep onset, which requires ad hoc scoring. For clinical convenience, some sleep clinics use a simplified protocol with fixed nap lengths of 20min. Its diagnostic accuracy remains unknown. MethodsA subset of MSLT naps of 56 narcolepsy type 1 (NT1), 98 Parkinson's disease (PD), 117 sleep disordered breathing (SDB), 22 insufficient sleep syndrome (ISS) patients, and 24 patients with idiopathic hypersomnia (IH), originally performed according to the simplified protocol, were retrospectively adjusted to standard protocol (nap termination 15min after sleep onset or after 20min when no sleep occurs). This was feasible in 60% of MSLT naps; in this subset, we compared sensitivity and specificity of both MSLT protocols for identification of patients with and without NT1. ResultsSensitivity of classical MSLT criteria for NT1, i.e. mean sleep latency ≤8.0min and ≥2 sleep onset rapid eye movement periods (SOREMPs), did not differ between protocols (95%). Specificity, however, was slightly lower (88.1% vs. 89.7%) in the simplified nap termination protocol, with 3 SDB patients and 1 ISS patient having false-positive MSLT findings in the simplified but not in the standard protocol. ConclusionsThe use of a simplified MSLT protocol with fixed nap duration had no impact on MSLT sensitivity for NT1, but the longer sleep periods in the simplified protocol increased the likelihood of REM sleep occurrence particularly in non-NT1 conditions, resulting in a slightly lower MSLT specificity compared to the standard protocol.

Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine.

Bandyopadhyay A, Bae C, Cheng H, etal. Smart sleep: what to consider when adopting AI-enabled solutions in clinical practice of sleep medicine. J Clin Sleep Med. 2023;19(10):1823-1833.

Screening and treatment of pre-bariatric surgical patients with obesity related sleep disordered breathing.

There is a significant burden of sleep disordered breathing (SDB) in patients living with severe and complex obesity undergoing pre-bariatric surgery assessment. This longitudinal observational study evaluated the burden of obesity hypoventilation syndrome (OHS) in this cohort of patients and the therapeutic compliance of patients commenced on positive airway pressure treatment. All pre-bariatric surgery patients referred to the sleep clinic for review after an abnormal screening study between 2018 and 2022 were included. We collected data on their sleep study results, anthropometrics, co-morbid medical conditions, clinical observations, spirometry and arterial blood gas (ABG). Patients commenced on therapy were followed-up longitudinally and compliance data collected via remote monitoring. A total of 116 patients were included [age: mean ± standard deviation (SD) 48.8±10.8 years; body mass index (BMI) 49.2±8.5 kg/m2; Epworth Sleepiness Scale (ESS) 8.7±5.1 points]. Fifteen patients (12.9% of cohort) were diagnosed with hypercapnic respiratory failure (pH 7.40±0.02; pO2 11.00±1.04 kPa; pCO2 6.15±0.08 kPa). Compared to eucapnic obstructive sleep apnoea (OSA) patients, they were older (51.1 vs. 48.5 years; P=0.311), had a higher BMI (51.5 vs. 48.9 kg/m2; P=0.266), more likely to be female (66.7% vs. 53.5%; P=0.275) and had a higher ESS score (10.4 vs. 8.5 points; P=0.177). On binomial regression analysis insulin dependent diabetes was the only patient characteristic of significance with prevalence increased in patients with OHS (26.7% vs. 8.9%; P=0.042). Forced vital capacity (FVC) and oxygen saturation (SpO2) cut-offs demonstrated high specificity (96.8%) but low sensitivity (13.3%) to diagnosed hypercapnia. Fifty percent of the patients with hypercapnia required bi-level ventilation. On follow-up 44.9% of patients were compliant with therapy (>4 hours usage/night). In minimally symptomatic patients living with severe and complex obesity who have an abnormal overnight oximetry, over 1 in 10 demonstrated chronic respiratory failure. Clinic spirometry and daytime SpO2 excluded those with hypercapnia. Overall adherence to prescribed therapy is low. Screening, appropriate pre-operative optimisation and peri-operative planning are important in preventing complications in this patient cohort.

Automatic sleep-stage classification of heart rate and actigraphy data using deep and transfer learning approaches

Manual sleep-stage scoring based on full-night polysomnography data recorded in a sleep lab has been the gold standard of clinical sleep medicine. This costly and time-consuming approach is unfit for long-term studies as well as assessment of sleep on a population level. With the vast amount of physiological data becoming available from wrist-worn devices, deep learning techniques provide an opportunity for fast and reliable automatic sleep-stage classification tasks. However, training a deep neural network requires large annotated sleep databases, which are not available for long-term epidemiological studies. In this paper, we introduce an end-to-end temporal convolutional neural network able to automatically score sleep stages from raw heartbeat RR interval (RRI) and wrist actigraphy data. Moreover, a transfer learning approach enables the training of the network on a large public database (Sleep Heart Health Study, SHHS) and its subsequent application to a much smaller database recorded by a wristband device. The transfer learning significantly shortens training time and improves sleep-scoring accuracy from 68.9% to 73.8% and inter-rater reliability (Cohen’s kappa) from 0.51 to 0.59. We also found that for the SHHS database, automatic sleep-scoring accuracy using deep learning shows a logarithmic relationship with the training size. Although deep learning approaches for automatic sleep scoring are not yet comparable to the inter-rater reliability among sleep technicians, performance is expected to significantly improve in the near future when more large public databases become available. We anticipate those deep learning techniques, when combined with our transfer learning approach, will leverage automatic sleep scoring of physiological data from wearable devices and enable the investigation of sleep in large cohort studies.

Vestibular symptoms are related to the proportion of REM sleep in people with sleep complaints: A preliminary report.

Though sleep problems (apnea, insomnia) and related daytime symptoms (fatigue, anxiety, depression) have been associated with vestibular problems (falls, dizziness), it is not well known which particular sleep features relate to vestibular problems. We thus assessed symptoms of vestibular problems in patients visiting a sleep clinic and evaluated how they were associated with objective sleep parameters derived from polysomnography and relevant daytime symptoms. The polysomnography data of thirty-one patients (61% female, between 20 and 79 years of age) who were referred for clinical sleep assessment was collated with subjective measures of symptoms linked to vestibular problems (rated on the Situational Characteristics Questionnaire), as well as fatigue, anxiety and depression symptoms. Multiple linear regression was used to identify factors associated with vestibular symptoms, including analyses adjusted for age, sex, medication use and total sleep time. A higher percentage of REM sleep and more severe anxiety symptoms were independently associated with more severe vestibular symptoms, which survived adjusted analyses. Other sleep stages, as well as as sleep efficiency, apnea-hypopnea index and oxygen saturation were not significantly related to vestibular symptoms. These results point at vestibular symptoms as possible important and overlooked correlates of variations in sleep architecture in individuals with sleep complaints. Though replication is needed to confirm findings from this limited sample, the results highlight the importance of assessing vestibular symptoms in people with sleep complaints. In particular, further investigations will need to address the potential implication of REM sleep for vestibular functions and the directionality of this relation.

Identification of Parkinson's Disease Subtypes from Resting-State Electroencephalography.

Parkinson's disease (PD) patients present with a heterogeneous clinical phenotype, including motor, cognitive, sleep, and affective disruptions. However, this heterogeneity is often either ignored or assessed using only clinical assessments. We aimed to identify different PD sub-phenotypes in a longitudinal follow-up analysis and their electrophysiological profile based on resting-state electroencephalography (RS-EEG) and to assess their clinical significance over the course of the disease. Using electrophysiological features obtained from RS-EEG recordings and data-driven methods (similarity network fusion and source-space spectral analysis), we have performed a clustering analysis to identify disease sub-phenotypes and we examined whether their different patterns of disruption are predictive of disease outcome. We showed that PD patients (n = 44) can be sub-grouped into three phenotypes with distinct electrophysiological profiles. These clusters are characterized by different levels of disruptions in the somatomotor network (Δ and β band), the frontotemporal network (α2 band) and the default mode network (α1 band), which consistently correlate with clinical profiles and disease courses. These clusters are classified into either moderate (only-motor) or mild-to-severe (diffuse) disease. We showed that EEG features can predict cognitive evolution of PD patients from baseline, when the cognitive clinical scores were overlapped. The identification of novel PD subtypes based on electrical brain activity signatures may provide a more accurate prognosis in individual patients in clinical practice and help to stratify subgroups in clinical trials. Innovative profiling in PD can also support new therapeutic strategies that are brain-based and designed to modulate brain activity disruption. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Treating Senile Chronic Insomnia with Spirit-Calming and Blood-Nourishing Decoction Combined with Guasha (Scraping) and Acupuncture

Abstract Objective To observe the efficacy of treating senile chronic insomnia with spirit-calming and blood-nourishing decoction combined with Guasha (scraping) and acupuncture therapy. Methods Seventy elderly patients with chronic insomnia were included and numbered by their visiting sequence. They were randomly divided into the control group and the observation group, 35 patients for each. Spirit-calming and blood-nourishing decoction was given to the control group, whereas Guasha (scraping) and acupuncture were applied together with the spirit-calming and blood-nourishing decoction to the observation group. Both groups were treated for 4 weeks before comparing their Pittsburgh Sleep Quality Index (PSQI) score and clinic efficacy. Results PSQI scores of both groups were significantly lowered. Compared with the control group, the differences are statistically significant (p < 0.01). After treatment, the PSQI score of the observation group is (6.80 ± 1.37), whereas that of the control group is (10.83 ± 2.51). PSQI score of the observation group is lower (p < 0.01). The effective rate was 85.7% in the observation group and 62.9% in the control group. Difference of the effective rates of both groups is statistically significant (p < 0.01). Conclusion Spirit-calming and blood-nourishing decoction combined with Guasha (scraping) and acupuncture is significantly effective in treating senile chronic insomnia. The combined therapy can effectively relieve the symptoms.

Profile of sleep disturbances in patients with recurrent depressive disorder or bipolar affective disorder in a tertiary sleep disorders service

Bidirectional relationship between sleep disturbances and affective disorders is increasingly recognised, but its underlying mechanisms are far from clear, and there is a scarcity of studies that report on sleep disturbances in recurrent depressive disorder (RDD) and bipolar affective disorder (BPAD). To address this, we conducted a retrospective study of polysomnographic and clinical records of patients presenting to a tertiary sleep disorders clinic with affective disorders. Sixty-three BPAD patients (32 female; mean age ± S.D.: 41.8 ± 12.4 years) and 126 age- and gender-matched RDD patients (62 female; 41.5 ± 12.8) were studied. Whilst no significant differences were observed in sleep macrostructure parameters between BPAD and RDD patients, major differences were observed in comorbid sleep and physical disorders, both of which were higher in BPAD patients. Two most prevalent sleep disorders, namely obstructive sleep apnoea (OSA) (BPAD 50.8.0% vs RDD 29.3%, P = 0.006) and insomnia (BPAD 34.9% vs RDD 15.0%, P = 0.005) were found to be strongly linked with BPAD. In summary, in our tertiary sleep clinic cohort, no overt differences in the sleep macrostructure between BPAD and RDD patients were demonstrated. However, OSA and insomnia, two most prevalent sleep disorders, were found significantly more prevalent in patients with BPAD, by comparison to RDD patients. Also, BPAD patients presented with significantly more severe OSA, and with higher overall physical co-morbidity. Thus, our findings suggest an unmet/hidden need for earlier diagnosis of those with BPAD.

0851 Evaluation of a new sleep focused nasal obstruction symptom evaluation (NOSE) tool

Abstract Introduction Nasal obstruction is a common patient complaint in the sleep clinic. The nasal obstruction symptom evaluation (NOSE) scale is a validated questionnaire to assess symptoms and quality of life. However, it has weaknesses when evaluating patients in the sleep clinic because it does not differentiate awake and sleep related nasal obstruction. Our primary goal was to compare the old NOSE scale to a new sleep NOSE scale that separates awake and sleep related nasal obstruction. Methods A retrospective study was completed to compare the known NOSE scale (old NOSE) with a revised clinical scale more relevant to the sleep clinic (new sleep NOSE and new awake NOSE). 169 adult participants completed the 3 scales in a sleep clinic specializing in otolaryngologic interventions. The collected data compared median scores (Wilcoxon’s signed rank test), agreement (Cohen’s kappa), and correlation (Spearman correlation). Wald’s test was also used to compare the scores between subgroups of insomnia and obstructive sleep apnea (OSA). Results The old NOSE scale scores were not significantly different from the sleep NOSE score (p=0.4) but was significantly different from the awake NOSE scale (p< 0.001). The new sleep NOSE scores were also significantly higher than then awake NOSE scores (p<.001). Patients with insomnia tended to score higher on the sleep NOSE scale than the awake NOSE scale. Conclusion This study suggests that in the sleep clinic setting, patients score the NOSE scale according to sleep related obstruction. In addition, insomnia patients relate more nighttime than daytime nasal obstruction. Further studies are needed to determine if the NOSE scale needs to be revised to better encompass nasal complaints related to sleep. Support (if any)

0504 STOP BANG FAN, A Novel Screening Tool of OSA in Sleep Clinic

Abstract Introduction We noticed that patients with OSA when admitted to hospital requested a fan even in winter. We explored the literature and did not find any reports about fan use in OSA. STOP-Bang questionnaire has been widely used in preoperative clinics [4-6], sleep clinics [7-8] to detect patients at high-risk of OSA. STOP Bang score 5 or more has high risk of OSA. We did a pilot study to explore if adding the use of FAN, especially in winter, would increase the sensitivity of STOP Bang questionnaire in the sleep clinic. Methods We screened 350 consecutive patients referred to our sleep clinic for suspected OSA in the period of March 2021 to April 2022, with STOP Bang FAN questionnaire. The questionnaire added if they use FAN during sleep in addition to the air condition and if they still use it in winter. Results 255 (73%) used FAN during sleep and 210 (60%) used the fan in winter. 247 patients had PSG, the others did not for variable reasons, including refusing COVID test before the study, insurance issues or no insurance. In the 247 patients who had the PSG the sensitivity of STOP Bang score 5 or more, STOP Bang score 5 or more + Sleeping with FAN and STOP Bang score 5 or more + sleeping with Fan in winter for OSA AHI 5 or more were 78%, 83% and 89%. The sensitivity of STOP Bang score 5 or more, STOP Bang score 5 or more + Sleeping with FAN and STOP Bang score 5 or more + sleeping with Fan in winter for moderate and severe OSA AHI 15 or more were 65%, 74% and 79%. The sensitivity of STOP Bang score 5 or more, STOP Bang score 5 or more + Sleeping with FAN and STOP Bang score 5 or more + sleeping with Fan in winter for severe OSA AHI 30 or more were 55%, 64% and 71%. Conclusion Adding the use of the FAN and especially FAN in winter during sleep to STOP Bang would increase the sensitivity of the questionnaire for suspected OSA in sleep clinic. Support (if any)

0342 Are Clinical Trials for Insomnia Recruiting Real World Patients?

Abstract Introduction Studies that have resulted in recent approval of hypnotics for chronic insomnia disorder (CID) have extremely restrictive inclusion criteria. We sought to determine how many patients seen in a sleep medicine clinic would be eligible to participate in these trials in order to assess the generalizability of these findings to clinical populations. Methods Six-hundred and twenty-eight patients were screened to identify 100 patients who were ≥18 years old, had a diagnosis of CID, and were prescribed a hypnotic medication at a sleep medicine clinic in a quaternary level healthcare center. Information regarding age, sex, body mass index, comorbid diagnoses, sleep schedule, medications, alcohol/tobacco/illicit drug use, caffeine intake, as well as Epworth Sleepiness Scale, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and Insomnia Severity Index scores were abstracted. These data were compared against the inclusion and exclusion criteria for recent regulatory Phase III trials of orexin receptor antagonists (suvorexant, lemborexant, daridorexant). Results Of the 100 patients with CID (mean age=56.2 years; 57% female), only 3 patients met eligibility criteria for inclusion. A majority of patients (80%) would have been excluded due to a prior/concurrent trial of cognitive behavioral therapy for insomnia. If this criterion was set aside, only 11 patients would have been eligible to participate. The remaining top reasons for potential exclusion from the regulatory trials were: presence of medical comorbidities (36%), daytime napping (33%), and sleep apnea (30%). Conclusion A very small number of patients with CID seen in a clinical setting met eligibility criteria for clinical trials of hypnotic medications resulting in regulatory approval. This substantially limits the generalizability of findings from these trials and restricts our ability to determine the efficacy of these drugs in clinical populations. Future trials should enroll patients with less restrictive criteria to help determine the effectiveness of these medications in real world settings. Support (if any)

1029 Inspire Confidence In CPAP

Abstract Introduction Obstructive sleep apnea (OSA) is defined as the repetitive episodes of complete or partial occlusion of the airway occurring during sleep. OSA is thought to play a role in many different diseases including anxiety, depression, excessive day time sleepiness, and GERD. Treatment of OSA can often be difficult as many patients cannot tolerate CPAP. Report of case(s) The patient is a 76-year-old male who was diagnosed with OSA in 1991. He had undergone Uvulopalatopharyngoplasty in 1997 and maxillomandibular advancement in 1999 but continued to have snoring and witnessed apneas and excessive daytime sleepiness (EDS). A repeat PSG in 2019 showed severe sleep apnea with an AHI of 37.3. The patient had been unable to tolerate his CPAP at home due to discomfort from the pressure. He was then referred for evaluation and subsequent placement of a hypoglossal nerve stimulator known as inspire by ENT. On follow-up at the sleep clinic, the patient complained that he was still having daytime sleepiness and snoring despite compliance with INSPIRE. A home study was done to evaluate the effectiveness of INSPIRE and his AHI was found to be 46. INSPIRE was reconfigured and a repeat sleep study was done which showed similar results. A decision was made to try combination therapy with INSPIRE and CPAP at a lower pressure than previously. His original CPAP settings were 12cmH20 and with combo therapy we were able to change this to autoPAP 7-10, which the patient tolerated well and showed good control of his sleep apnea with an AHI of 4.6. Conclusion For those with moderate to severe OSA, the gold standard therapy is CPAP, but not every patient can tolerate CPAP therapy. One of the reasons is the CPAP pressure being too high. In 2014 the FDA approved a new treatment option for those with moderate to severe sleep apnea with the hypoglossal nerve stimulator. In our patient, multiple different INSPIRE configurations were attempted but he still had uncontrolled OSA and EDS. We were able to use combination therapy with INSPIRE and CPAP to adequately control his OSA without needing the high pressure that he could not tolerate previously. Support (if any)

0482 Sleep Apnea Diagnosis Disparities from Serious Mental Illness in a Veteran Cohort

Abstract Introduction Sleep apnea (SA) diagnosis requires multiple steps including an office visit and testing. People with serious mental illness (SMI) may require a longer time from referral to diagnosis and be less likely to complete the full diagnostic pathway because of functional limitations. Methods A retrospective cohort of VA Northeast Ohio Healthcare System Veterans referred for sleep medicine consultation (1/1/2010-12/31/2020). Dates of consultation, sleep clinic visits, and testing was collected in addition to demographics, past medical history, and medications at the time of initial consultation. SMI was defined as a composite of schizophrenia, schizoaffective disorder, and bipolar diagnosed disorder before the initial consultation. The outcome was defined as the time until fulfilling minimal SA diagnostic pathway defined as completing both a sleep clinic appointment and at last one sleep test. Relationships between SMI and pathway completion were tested using survival analyses. Analyses were adjusted for age, sex, race, insurance status, service connection percent, Medicare eligibility, marital status, alcohol use, and drug use to account for other potential sources of health disparities. Sensitivity analyses evaluated differences in time to pathway completion via the Wilcoxon-Mann-Whitney test. Results The cohort (n=11,030) was primarily male (91.1%), with mean age of 55.8 ±14.4 yrs, with mean body mass index of 32.9 ± 6.4 kg/m2, and a mean pathway completion in 71 days, interquartile range (IQR): [33, 135]. Those with SMI had similar pathway completion rates (89.9% in SMI vs. 90.2% without), but a longer time to completion (83 days, IQR = [35.5, 185.5] in SMI vs. 70 days IQR: [32, 132]). Pathway completion time was significantly higher in those with SMI (Wilcoxon rank sum test difference = 9.0 days, 95%CI: [4.0, 14.0]. ]SMI was associated with a lower hazard of time to pathway completion (HR = 0.87, 95% confidence interval (CI): [0.91, 0.94] in unadjusted and HR = 0.87, 95%CI:[0.81, 0.94]. Conclusion Although pathway completion rates were similar, Veterans with SMI were more likely to take longer before pathway completion. Additional investigation of factors that delay pathway completion may offer tailored avenues to improve the time to diagnosis. Support (if any) VA CSR&D IK2CX001882

1025 Schizophrenic Patient with Large REM Rebound Following Treatment of Severe Obstructive Sleep Apnea

Abstract Introduction We present a case of uncontrolled schizophrenia with severe obstructive sleep apnea (OSA) and significant REM rebound after bilevel positive airway pressure (BPAP) therapy. Report of case(s) A 74-year-old female, with Schizophrenia on anti-psychotic therapy, presented to the sleep clinic due to excessive daytime sleepiness (EDS) and an Epworth score of 21/24. Diagnostic polysomnogram (PSG) reported an AHI of 162.1 events/hour with SaO2 nadir of 71% with sleep efficiency of 31.6% and no REM-sleep, consistent with severe OSA. The next morning, multiple sleep latency testing (MSLT) demonstrated mean sleep latency (MSL) of 3.6 minutes with 0 REM-onset sleep periods (SOREMPs). Patient underwent CPAP/BPAP titration which improved sleep efficiency to 88.6% and severe REM rebound at 61.7%. MSLT after the titration study demonstrated MSL of 4.0 minutes and 3 SOREMPs and was initiated on BPAP therapy at 20/13 cmH2O. A repeat PSG, 4 weeks later showed normalization of sleep architecture. After starting PAP therapy, the patient had a significant improvement in EDS but also energy and interest levels and denied feelings of sadness, racing or paranoid thoughts. Her social life improved and started exercising regularly and volunteering in the community. There was also improved blood pressure and blood sugar levels. She was followed up in the sleep clinic regularly and remained compliant with and benefiting from BPAP therapy and was continued on anti-psychotic therapy. Conclusion Untreated OSA often requires repetitive arousals to reopen the obstructed upper-airway that results in increased non-REM sleep at the expense of slow wave sleep and REM sleep. PAP therapy can cause a rebound increase in REM and SWS. OSA is under recognized in schizophrenic patients and other psychiatric disorders which results in development of significant comorbidities with greater severity of psychiatric symptoms. Elevated rates of OSA have been seen in the schizophrenic population. Treatment of OSA helps with not only physical but also psychotic symptoms. Many anti-psychotics, due to causing weight gain, may contribute to OSA. Studies also indicated that CPAP response to OSA, was as favorable in people with severe mental illness, compared to other patient groups. Support (if any) REM rebound and CPAP compliance; B. Koo, R. Wiggins, C. Molina

0402 Factors associated with subjective sleep problem and treatment willingness in sleep clinic patients

Abstract Introduction Insomnia clinic physicians often encounter patients with discrepancy between subjective and objective sleep problem. This study aimed to investigate factors that attributed to patients’ perception of sleep disturbances and treatment willingness, which were practical in determining diagnostic and treatment direction. Methods This study was a cross-sectional study, data collected from November 2018 to October 2022 in sleep clinic of tertiary university-affiliated hospital. Adults older than 19 who underwent sleep questionnaires and polysomnography (PSG) were included (n=3,239). Demographic data and sleep-related factors (alcohol, caffeine, exercise, education, job, marital status, comorbidity) were collected. Subjects were categorized into four groups by questionnaire answers (Do you think you have sleep problem? Do you want treatment for sleep problem? -group 1, neither; group 2, no sleep problem but want treatment; group 3, yes sleep problem without treatment willing; group 4, both yes.) and compared. Results Group 2 had higher percentage of job, snoring, witnessed apnea, worry about sleep, sleep maintenance problem than group 1. Group 3 had less job, sleep maintenance problem, daytime dysfunction, worry about sleep than group 4 (p< 0.05). Majority of no sleep problem groups were revealed to be normal (group 1: 28.0%, 2: 28.5%) or OSA (group 1: 63,7%, 2: 63.1%), while yes sleep problem groups were relatively higher combined insomnia and OSA (COMISA) (group 3: 20.0%, 4: 23.8%) or insomnia (group 3: 11.1%, 4: 15.3%) by PSG. OSA patients in group 2 showed more witnessed apnea and worry about sleep than group 1. COMISA patients in group 3 had less daytime dysfunction than group 4. However, PSG parameters were not significantly different among groups. Conclusion This study found that social need and subjective sleep maintenance problem are key factors that lead patients to regard their sleep as problematic or seek for treatment. In particular, patients with suspected OSA need to be instructed to get sleep study since sleep apnea severity do not affect treatment willingness and they had the lowest insight of their sleep problem. For those complaining of no or mild problem yet seeks for treatment, focusing on relieving misperceived worries about sleep is needed. Support (if any)