Sleep Technologists Research Articles

Sleep medicine guidelines, recommendations for clinical practice: the role of the European Sleep Research Society.

The European Sleep Research Society (ESRS) has a strong focus on sleep research in Europe. In addition, the ESRS supports sleep medicine in Europe by providing a platform of exchange and communication for the national sleep societies of all European countries and by providing committees that support co-ordination for important clinical activities. These committees help on clinical guidelines, certification of sleep centres, certification of sleep physicians, psychologists, sleep scientists, sleep technologists, and medical education in sleep medicine. For education in sleep medicine, a "Catalogue on knowledge and skills" has been developed based on a consensus process. This catalogue serves as the backbone for a European textbook on sleep medicine and as the basis for courses, qualifications, and examinations of somnologists in Europe. These activities are devoted to improving and maintain a high quality of care in Europe for sleep medicine services.

Behavioral validation of the University of Michigan REM behavior disorder questionnaire in the synucleinopathies

Many questionnaires have been proposed to collect data related to dream enactment. These are typically validated by reference to objective measurements of polysomnography, which incorporate physiologic recording of muscle activity during sleep. Another approach to such questionnaire validation would be the direct behavioral observations of patients' sleep. In the course of an ongoing study, we examined the association between sleep technologists' observations of dream enactment on two consecutive sleep laboratory nights and patients' and bedpartners' responses on the University of Michigan REM Behavior Disorder Questionnaire (UMRBDQ). Results suggested good correspondence between laboratory-based observations and questionnaire responses that did not appear to be impacted by whether the patient or the bedpartner completed the questionnaire. These results suggest utility of the UMRBDQ to identify individuals who have dream enactment during sleep.

Effects of head rotation on upper airway morphology and respiratory events: perspectives from polysomnographic technologists

Effects of head rotation on upper airway morphology and respiratory events: perspectives from polysomnographic technologists

P042 Five-year review of a tertiary paediatric sleep service for complex patients

Abstract Introduction Our paediatric sleep unit commenced service for children with complex medical problems in July 2015. Service capacity includes 12 inpatient level 1 studies (two neonates) and one home study per week. FTE includes senior scientists 2.6, sleep technologists 1.7, administration 1.0, nursing 0.7 and medical 1.2. The primary aim of this study was to evaluate activity during the first 5-years. The secondary aim was to document the impact of the COVID-19 pandemic. Methods Sleep unit operational & diagnostic data were collected from sleep booking sheets, sleep study reports, electronic medical records. Descriptive statistics are presented. Results A total of 2186 sleep studies were performed (July 2015 to June 2020) with a range of 368–472 studies per annum. Overall, 61.7% were diagnostic studies, 20.8% titration studies (CPAP, oxygen, bi-level or invasive ventilation), 10% neonatal and 7.5% home studies. Between 2016–2020, the average waiting time (days) for a neonatal study was 16, a titration study was 106, a diagnostic study was 110 and a home study was 76. Further delays were caused by the COVID19 pandemic. Mean waiting time rose 229% from 108 days (Feb 2020) to 355 days (Feb 2021). Referrals for sleep studies have exceeded bed capacity since the beginning of the pandemic. Discussion This audit describes activity in a tertiary complex paediatric sleep service during the first 5 years. The service has struggled on current FTE and bed capacity to manage waiting times, exacerbated further by the COVID-19 pandemic. A new business and clinical model are warranted.

Variable negative external pressure-an alternative to continuous positive airway pressure for the treatment of obstructive sleep apnea: a pilot study.

To assess variable negative external pressure (vNEP) therapy using a range of pressures and varying collar sizes and shapes to identify combinations that improve the efficacy and comfort of this emerging therapy for obstructive sleep apnea (OSA). This prospective, open-label pilot study included 28 eligible patients (71% men) having documented moderate OSA (apnea-hypopnea index [AHI] 15 events/h ≤ AHI ≤ 30 events/h) at 1 sleep clinic for an overnight, in-lab sleep trial. Each participant tested at least 2 of 6 available vNEP devices during sleep periods ≥ 2 hours. During the assessment of AHI by polysomnography, negative pressures of -20 cm H2O to -35 cm H2O were adjusted to improve each patient's response. Participants' therapeutic preferences were assessed by a questionnaire and interviews. Twenty (71%) of the participants responded to vNEP therapy: excellent response (AHI ≤ 5 events/h) was observed in 14 (50%); 6 (21%) achieved a partial response (AHI ≤ 50% baseline). For the 20 responders, the therapy reduced the fraction of total sleep time when peripheral oxygen saturation < 90% and improved minimum pulse oximetry oxygen saturation. Six patients experienced a minor, self-limited adverse event. Twenty-six participants (93%) stated that they would use vNEP nightly. In this pilot study, vNEP therapy markedly improved AHI and oxygenation in most patients with moderate OSA. The majority of participants found vNEP comfortable and preferable to prevailing OSA therapies. Further development and studies of vNEP are warranted. Registry: ClinicalTrials.gov; Name: Study of Variable Negative External Pressure (vNEP) in Reducing Respiratory Event in Individuals With OSA; URL: https://clinicaltrials.gov/ct2/show/NCT04718142; Identifier: NCT04718142. Kram JA, Pelayo R. Variable negative external pressure-An alternative to continuous positive airway pressure for the treatment of obstructive sleep apnea: A pilot study. J Clin Sleep Med. 2022;18(1):305-314.

Sleep Medicine Health-Care Worker Concerns About COVID-19: An Early Pandemic Survey.

The coronavirus disease 2019 (COVID-19) pandemic has produced numerous safety concerns for sleep medicine patients and health-care workers, especially related to the use of aerosol-generating positive airway pressure devices. Differences between physician and sleep technologist concerns with regard to viral exposure and mitigation strategies may inform protocols to ensure safety and promote patient and health-care worker resilience and retention. An anonymous online survey aimed at sleep medicine practitioners was active from April 29, 2020 to May 8, 2020. We obtained 379 responses, including from 75 physicians and 283 technologists. The proportion of all the respondents who were extremely/very concerned about the following: exposing patients (70.8%), exposing technologists (81.7%), and droplet (82.7%) and airborne (81.6%) transmission from CPAP. The proportion of respondents who felt that aerosol precautions were extremely/very important varied by scenario: always needed (45.6%); only with CPAP (25.9%); and needed, despite negative viral testing (67.0%). More technologists versus physicians rated the following as extremely/very important: testing parents for COVID-19 (71.2 vs 47.5%; P = .01), high-efficiency particulate air filters (75.1 vs 61.8%; P = .02), and extremely/very concerned about shared-ventilation systems (65.9 vs 51.5%; shared ventilation P = .041). The respondents in northeastern and western United States were more concerned about the availability of COVID-19 testing than were those in other regions of the United States. Among the total number of respondents, 68.0% expected a ≥ 50% drop in patients willing to have in-laboratory testing, with greatest drops anticipated in northeastern United States. Sleep health-care workers reported high levels of concern about exposure to COVID-19. Physicians and technologists generally showed high concordance with regard to the need for mitigation strategies, but the respondents differed widely with regard to which strategies were necessary.

Comparison of home ambulatory type 2 polysomnography with a portable monitoring device and in-laboratory type 1 polysomnography for the diagnosis of obstructive sleep apnea in children.

To compare type 2 polysomnography (T2PSG) to the gold standard type 1 in-laboratory polysomnography (T1PSG) for diagnosing obstructive sleep apnea (OSA) in children; validate home T2PSG in children with suspected OSA. Eighty-one participants (ages 6-18) with suspected OSA had simultaneous T1PSG and T2PSG in the sleep laboratory, 47 participants (ages 5-16) had T1PSG in the sleep laboratory and T2PSG performed at home. Sleep scientists staged and scored polysomnography data, and pediatric sleep physicians assigned a diagnosis of normal or OSA. Participant demographics, polysomnography variables, and diagnoses were compared using chi-square and Fisher's exact tests for nominal variables, t test for continuous variables and Cohen's kappa to assess concordance. Acceptable recordings were obtained for every home T2PSG. When T1PSG and T2PSG were simultaneous, correlation between the number of arousals, respiratory disturbance index, and sleep stages was excellent. T2PSG at home demonstrated less stage 2 sleep, more rapid eye movement sleep, and higher sleep efficiency. Comparison of home T2PSG to T1PSG for diagnosing OSA showed a false-positive rate of 6.6% and false-negative rate of 3% for those performed at home. T2PSG in the home is feasible with excellent concordance with T1PSG for the purposes of diagnosing OSA in children aged 5-18 years. Home T2PSG may be more representative of a "normal" night for children and could benefit those suspected of having OSA by reducing waiting times for laboratory PSG, improving access to PSG and possibly reducing costs of investigating and treating OSA. Withers A, Maul J, Rosenheim E, O'Donnell A, Wilson A, Stick S. Comparison of home ambulatory type 2 polysomnography with a portable monitoring device and in-laboratory type 1 polysomnography for the diagnosis of obstructive sleep apnea in children. J Clin Sleep Med. 2022;18(2):393-402.

O-EG004. Comparing the accuracy of sleep staging data from a new wearable sleep electroencephalography device versus the Fitbit Charge 3 with polysomnography as reference

Introduction . Although sleep disorders are a common social problem, polysomnography (PSG), the gold standard in sleep diagnostics, can be burdensome and may interfere with natural sleep. We have developed a high-precision wearable electroencephalography (EEG) device for objectively measuring sleep at home. Actigraphy devices with the capability of measuring heart rate variability can also be used to evaluate sleep stages at home (e.g., Fitbit Charge 3). However, the accuracy of these inhome devices has not yet been compared. We hypothesized that the accuracy of our wearable sleep EEG device would be higher than that of the Fitbit Charge 3. Methods . We simultaneously recorded PSG, wearable sleep EEG, and data from the Fitbit Charge 3 in 42 (mean ± SD: 23.5 ± 7.8 years, 14 women) healthy participants. A registered polysomnographic technologist scored the PSG and wearable sleep EEG data, and we evaluated the sleep stages captured by the Fitbit Charge 3 using the Fitbit automatic sleep staging algorithm (stage W, N1+N2, N3, and R). We measured and compared the accuracy of the wearable EEG device and Fitbit Charge 3 data with respect to the PSG data. Results . The accuracy of the wearable sleep EEG device and Fitbit Charge 3 was 90.7 ± 2.8% and 69.5 ± 8.3 %, respectively (mean ± SD). The wearable sleep EEG device had significantly higher accuracy than the Fitbit (p < 0.001). Conclusion . Compared with the Fitbit Charge 3 data, data from the wearable sleep EEG device more closely mirrored the PSG data. Thus, the wearable sleep EEG device may be superior to the Fitbit Charge 3 as an alternative to PSG. Our wearable sleep EEG device has potential for use in sleep evaluations for multiple consecutive nights in an in-home setting.

Polysomnography parameters as predictors of respiratory adverse events following adenotonsillectomy in children

The first-line treatment of obstructive sleep apnea syndrome in children is adenotonsillectomy, but this may result in perioperative respiratory adverse events (PRAEs). The primary aim of this study is to examine whether the McGill oximetry score (MOS) and other polysomnography parameters can predict major PRAEs following adenotonsillectomy. We secondarily evaluated the MOS interrater reliability and correlation with other polysomnography parameters. This retrospective study included all children aged 0-18 years who underwent preoperative polysomnography between June 2010 and January 2016 prior to adenotonsillectomy at a tertiary pediatric institution. Oximetries from polysomnograms were assigned an MOS. Univariable and multivariable models for prediction of major PRAEs were constructed. MOS was correlated with polysomnography parameters and interrater reliability was evaluated. This study included 106 children; 15 had a major PRAE. A multivariable prediction model that combined MOS and age showed evidence for the ability to predict major PRAEs with an area under the receiver operating characteristic curve of 0.68 (95% confidence interval: 0.52, 0.84), whereby increased MOS and younger age were associated with PRAEs, but apnea-hypopnea index was not. MOS had excellent interrater reliability (κ = 0.95) and was highly correlated with oxygen saturation nadir and cumulative time percentage with oxygen saturation less than 90%. A prediction model including MOS and age may predict PRAEs following adenotonsillectomy. This suggests that nocturnal oximetry provides the most essential information of polysomnography measures to direct postoperative monitoring following adenotonsillectomy. Xiao L, Barrowman N, Momoli F, etal. Polysomnography parameters as predictors of respiratory adverse events following adenotonsillectomy in children. J Clin Sleep Med. 2021;17(11):2215-2223.

390 Risk of Obstructive Sleep Apnea: A Comparison Between Ischemic and Hemorrhagic Stroke

Abstract Introduction Obstructive Sleep Apnea (OSA) is common amongst stroke patients. Distinction between the prevalent types of stroke when evaluating sleep may prove useful to prevent recurrent strokes. There is a lack of information on how apnea prevalence following ischemic stroke compares to hemorrhagic stroke, particularly during the chronic period. Here we set out to retrospectively determine if apnea incidence was more marked in ischemic stroke patients compared to those that received a hemorrhagic stroke diagnose; while taking in account medications taken during the sleep evaluation. Methods Medical records were reviewed from 103 patients diagnosed with stroke that underwent a type I fully attended overnight polysomnography. Diagnosis of embolic, thromboembolic or hemorrhagic stroke was obtained from a neurological report that was typically confirmed by computed tomography or magnetic resonance imaging. Medications that the subject was taking at the time of the sleep study were documented by the sleep technologist. Results Arousals and microarousal index was higher in the ischemic group (p&amp;lt;0.005). Age adjusted assessment of apnea and hypopnea events, indicated that subjects with an ischemic stroke had a higher incidence of apnea and hypopnea compared to the hemorrhagic group (p&amp;lt;0.005). Ischemic subjects were also more likely to present severe apnea (AHI &amp;gt; 30) (p&amp;lt;0.005). In comparison, a higher percentage of hemorrhagic subjects had an AHI below 5 (p&amp;lt;0.005). Type of hemorrhagic stroke did not have an impact on apnea/hypopnea variables. Those with an ischemic stroke were taking significantly more lipid lowering agents (p&amp;lt;0.05). Logistic regression analysis indicated that the predictive probability of apnea (AHI &amp;gt; 5) increased from 0.55 to 0.81 (p &amp;lt; 0.05) when anti-hypertensive use was considered. An increase in predictive values for apnea was observed for indicators of diabetes such as use of anti-diabetics with or without consideration of diabetic history (p &amp;lt; 0.05). Conclusion Data suggests that ischemic patients present a higher artherosclerotic load that may contribute to the higher incidence of severe OSA. These data indicate that it is relevant to consider stroke type when determining the risk of OSA thus facilitating new strategies for stroke recurrence prevention. Support (if any):

475 Automatic detection of self-similarity and prediction of CPAP failure

Abstract Introduction Sleep disordered breathing is a significant risk factor for cardiometabolic and neurodegenerative diseases. Tolerance and efficacy of continuous positive airway pressure (CPAP), the primary form of therapy for sleep apnea, is often poor. High loop gain (HLG) is a driving mechanism of central sleep apnea or periodic breathing. The current study aimed to develop a computational approach to detect HLG based on self-similarity in respiratory oscillations during sleep solely using breathing patterns, measured via Respiratory Inductance Plethysmography (RIP). To quantify the potential utility of the developed similarity metric, the presented algorithm was used to predict acute CPAP failure. Methods We developed an algorithm for detecting apneas as periods with reduced breathing effort, manifested in the RIP signal as low signal amplitude. Our algorithm calculates self-similarity in breathing patterns between consecutive periods of apnea or hypopnea. Working under the assumption that high loop gain induces self-similar respiratory oscillations and increases the risk of failure during CPAP, the full night similarity, computed during diagnostic non-CPAP polysomnography (PSG), was used to predict failure of CPAP, which we defined as titration central apnea index (CAI)&amp;gt;10. Central apnea labels are obtained both from manual scoring by sleep technologists, and from an automated algorithm developed for this study. The Massachusetts General Hospital (MGH) sleep database was used, including 2466 PSG pairs of diagnostic and CPAP titration PSG recordings. Results Diagnostic CAI based on technologist labels predicted failure of CPAP with an AUC of 0.82 ±0.03. Based on automatically generated labels, the combination of full night similarity and automatically generated CAI resulted in an AUC of 0.85 ±0.02. A subanalysis was performed on a population with technologist labeled diagnostic CAI&amp;gt;5. Full night similarity predicted failure with an AUC of 0.57 ±0.07 for manual and 0.65 ±0.06 for automated labels. Conclusion This study showed that central apnea labels can be derived in an automated way. The proposed self-similarity feature, as a surrogate estimate of expressed respiratory high loop gain and computed from easily accessible effort signals, can detect periodic breathing regardless of admixed obstructive features such as flow-limitation, and can aid prediction of CPAP failure or success. Support (if any):

406 Clinical Validation of AI Scoring in Adult and Pediatric Clinical PSG Samples Compared to Prospective, Double-Blind Scoring Panel

Abstract Introduction Despite an appreciable rise in sleep wellness and sleep medicine A.I. research publications, public data corpuses, institutional support, and health A.I. research funding opportunities, the availability of controlled-retrospective, hybrid-retrospective-prospective, and prospective-RCT quality clinical validation study evidence is limited with respect to their potential clinical impact. Furthermore, only a few practical examples of A.I. technologies are validated, in use today clinically, and widely adopted, to assist in sleep diagnoses and treatment. In this study, we contribute to this growing body of clinical A.I. validation evidence and experimental design methodologies with an interoperable A.I. scoring engine in Adult and Pediatric populations. Methods Stratified random sampling with proportionate allocation was applied to a database of N&amp;gt;10,000 retrospective diagnostic clinical polysomnography (PSG), selected by evidence grading standards, with controls applied for OSA severity, diagnoses; sleep, psychiatric, neurologic, neurodevelopmental, cardiac, pulmonary, metabolic disorders, medications; benzodiazepines, antidepressants, stimulants, opiates, sleep aids, demographic groups of interest; sex, adult age, pediatric age, BMI, weight, height, and patient-reported sleepiness, to establish representative N=100 Adult and N=100 Pediatric samples. Double Blinded scoring was prospectively collected for each sample by 3 experienced RPSGT certified sleep technologists randomized from a pool of 9 scorers. Sensitivity (PA), Specificity (NA), Accuracy (OA), Kappa (K), and 95% Bootstrap CI’s are presented for sleep stages, OSA/CSA, hypopnea 3%/4%, arousals, limb movements, Cheyenne-Stokes respiration, periodic breathing, atrial fibrillation, and other events, and normative, mild, moderate, and severe OSA categories for global-AHI and REM-AHI. Results for Sleep Staging and OSA Severity Diagnostic Accuracy are summarized. Results A.I. scoring performance meet but in most cases exceeded initial clinical validation study (N=72 Adults, 2017) PA, NA, OA, K point-estimates and confidence-interval results for the 26 event types and 8 AHI-categories evaluated. The Adult sample showed 87%/94% Sensitivity/Specificity across all stages (Wake/N1/N2/N3/REM) and 94%/96% Sensitivity/Specificity for AHI&amp;gt;=15. The Pediatric sample showed 87%/93% Sensitivity/Specificity staging, 89%/98% Sensitivity/Specificity AHI&amp;gt;=15. Observed Accuracy was &amp;gt;90% for Adults and Pediatrics all 26 events and 7 AHI-categories analyzed, except REM-AHI&amp;gt;=5 (85%/82% Adults/Pediatrics). Conclusion We provide clinical validation evidence that demonstrates interoperable A.I. scoring performance in representative Adult and Pediatric patient clinical PSG samples when compared to prospective, double-blind scoring panel. Support (if any):

442 Feasibility of a Sleep Technologist Driven Intervention Protocol to Address CPAP Adherence in Hospitalized Patients

Abstract Introduction Obstructive sleep apnea (OSA) is associated with development of high blood pressure, diabetes, pulmonary hypertension, heart attack, stroke, atrial fibrillation, motor vehicle accidents, and death. These comorbidities may result in hospital admissions. Much of the therapy has been directed towards outpatient treatment with CPAP. Unfortunately, patient adherence to CPAP therapy is not optimal. We conducted a feasibility study to determine if a sleep technologist driven intervention protocol could address CPAP adherence in hospitalized patients. Methods Tampa General Hospital Sleep Center developed a quality improvement protocol that would address inadequate CPAP adherence. The components include: 1. Education on the cause and need for treatment of OSA based on comorbidities, 2. Choosing a patient preferred mask, 3. Mask desensitization while awake. These criteria were used to test the feasibility of implementing this protocol in hospitalized patients: 1. Completion of the protocol within 48 hours of receiving a consult, 2. Implementation of various components of the protocol, 3. Obtaining outcome measures to evaluate efficacy. Outcome measures include patient willingness to retry CPAP (on a scale from 0–10) and CPAP smartcard download. Additional outcome data included: patient reasoning for CPAP noncompliance and self-administered questionnaires (ESS, ISI, GAD-7, PHQ-9, SF-26). Results During November 2020, 31 inpatient consults were placed to the TGH Sleep Center. Within 48 hours of consult, the technologists implemented the protocol in 19 patients – 17 received mask fittings, 3 received education, and 3 had CPAP setting adjustments. 9 patients indicated their willingness to retry CPAP with an average rating of 9.1. 7 compliance downloads were obtained the following morning and usage ranged from 0:52 to 11:07 hours. 12 consults were not completed due to not meeting inclusion criteria (5), patient refusal (4), or other reasons (3). Conclusion This study demonstrates feasibility of a sleep technologist driven intervention protocol to address CPAP adherence in hospitalized patients. However, there were inconsistencies in protocol execution and obtaining outcome measures. We speculate that protocol improvement will require: 1. More consistent patient education, 2. Better correction of patient specific adherence issues, 3. Obtaining all smartcard downloads, 4. Compiling outcome measures using a convenient digital interface. Support (if any):

Deep Learning for Diagnosis and Classification of Obstructive Sleep Apnea: A Nasal Airflow-Based Multi-Resolution Residual Network.

PurposeThis study evaluated a novel approach for diagnosis and classification of obstructive sleep apnea (OSA), called Obstructive Sleep Apnea Smart System (OSASS), using residual networks and single-channel nasal pressure airflow signals.MethodsData were collected from the sleep center of the First Affiliated Hospital, Sun Yat-sen University, and the Integrative Department of Guangdong Province Traditional Chinese Medical Hospital. We developed a new model called the multi-resolution residual network (Mr-ResNet) based on a residual network to detect nasal pressure airflow signals recorded by polysomnography (PSG) automatically. The performance of the model was assessed by its sensitivity, specificity, accuracy, and F1-score. We built OSASS based on Mr-ResNet to estimate the apnea‒hypopnea index (AHI) and to classify the severity of OSA, and compared the agreement between OSASS output and the registered polysomnographic technologist (RPSGT) score, assessed by two technologists.ResultsIn the primary test set, the sensitivity, specificity, accuracy, and F1-score of Mr-ResNet were 90.8%, 90.5%, 91.2%, and 90.5%, respectively. In the independent test set, the Spearman correlation for AHI between OSASS and the RPSGT score determined by two technologists was 0.94 (p < 0.001) and 0.96 (p < 0.001), respectively. Cohen’s Kappa scores for classification between OSASS and the two technologists’ scores were 0.81 and 0.84, respectively.ConclusionOur results indicated that OSASS can automatically diagnose and classify OSA using signals from a single-channel nasal pressure airflow, which is consistent with polysomnographic technologists’ findings. Thus, OSASS holds promise for clinical application.

Asian accreditation of sleep medicine physicians and technologists: practice guidelines by the Asian Society of Sleep Medicine

Due to the rapid growth in sleep medicine's professional content, several countries have recognized sleep medicine as an independent specialty. The practice of sleep medicine and the demand for this service in Asian countries are expanding. At this point of growth, the accreditation of sleep medicine specialists is paramount to patient care and the training of physicians and technologists. The Asian Society of Sleep Medicine (ASSM) mandated a taskforce committee for the accreditation of sleep medicine practice. This taskforce developed Asian accreditation practice guidelines for sleep medicine physicians and technologists. This paper presents the newly approved Asian accreditation practice guidelines for sleep medicine physicians and technologists by the ASSM.

The new procedure for manual CPAP titration : the afternoon CPAP titration (aPT).

Study Objectives : Although the full-night continuous positive airway pressure (CPAP) titration (fnPT) has been recognized as the gold standard for determining an optimal therapeutic pressure for obstructive sleep apnea (OSA) treatment, it is labor-intensive, time-consuming because it requires overnight polysomnography attended by well-experienced sleep technologists. The aim of this study is to develop a practical and feasible alternative titration method. Methods : We assessed demographic data and diagnostic polysomnographic parameters, time spent in CPAP titration, CPAP efficacy and long-term adherence of the two groups of our OSA patients who had received CPAP titration either by fnPT (n = 46) or by afternoon CPAP titration (aPT, n = 22). Main results : Mean total recording time of aPT was significantly shorter than that by fnPT (p < 0.0001). There was no significant difference in mean residual apnea hypopnea index (AHI) on treatment, percent days with device usage, cumulative device usage hours during the 360 days, average device usage hours per day (360 days, days used), and percent of days with device usage ≥ 4 hours during the 360 days after starting CPAP treatment between the two groups. Conclusions : Our study demonstrated that aPT was feasible procedure as an alternative to fnPT. J. Med. Invest. 68 : 170-174, February, 2021.

Three-Stage Breathing Effort Quantification for Obstructive Sleep Apnea Detection Based on Thoracic and Abdominal Movement Signals

A level-IV home-based sleep apnea monitoring system that utilizes alternative sensors, such as dual respiratory inductance plethysmography (RIP) belts, is proposed to promote routine apnea monitoring. Notably, continued excursion may occur in RIP belt signals, owing to the imperfect relationship between thoracic and abdominal movements during obstructive events. Therefore, we propose a novel algorithm to detect obstructive apnea based on an obstructive reciprocal divergence (ORD) continued excursion model and to explore the possibility of a multistage breathing-effort evaluation model using only RIP signals. Using the developed approach, we detected obstructive sleep apnea with a high accuracy of 99.83 ± 0.71% and a slight reduction of 73.34 ± 28.35% in hypopnea performance with overall combined objective metrics of 89.38 ± 10.53%. We found that introducing many stages improves specificity (p $\text{R}^{2}=0.98$ ; p < 0.001). The proposed approach can assist sleep technologists in characterizing obstructive and nonobstructive apneic events. Moreover, ORD is competent for further quantitative and qualitative IFL analysis and will significantly benefit the automated IFL detection system studies.

Selective serotonin reuptake inhibitor use is associated with worse sleep-related breathing disturbances in individuals with depressive disorders and sleep complaints: a retrospective study.

The effects of serotonergic agents on respiration neuromodulation may vary according to differences in the serotonin system, such as those linked to depression. This study investigated how sleep-related respiratory disturbances relate to depression and the use of medications commonly prescribed for depression. Retrospective polysomnography was collated for all 363 individuals who met selection criteria out of 2,528 consecutive individuals referred to a specialized sleep clinic (Ottawa, Canada) between 2006 and 2016. The apnea-hypopnea index (AHI), oxygen saturation nadir, and oxygen desaturation index during REM and NREM sleep were analyzed using mixed analyses of covariance comparing 3 main groups: (1) medicated individuals with depressive disorders (antidepressant group; subdivided into the selective serotonin reuptake inhibitor and norepinephrine-dopamine reuptake inhibitor subgroups), (2) non-medicated individuals with depressive disorders (non-medicated group), and (3) mentally healthy control patients (control group). Individuals with depressive disorders (on antidepressants or not) had significantly higher AHIs compared to control patients (both P ≤ .007). The antidepressant group had a lower NREM sleep oxygen saturation nadir and a higher NREM sleep oxygen desaturation index than the control and non-medicated groups (all P ≤ .009). Within individuals with depressive disorders, independent of depression severity, the selective serotonin reuptake inhibitor group had a lower oxygen saturation nadir and a higher oxygen desaturation index during NREM sleep than the norepinephrine-dopamine reuptake inhibitor (both P ≤ .045) and non-medicated groups (both P < .001) and a higher NREM sleep AHI than the non-medicated group (P = .014). These findings suggest that the use of selective serotonin reuptake inhibitors may be associated with impaired breathing and worse nocturnal oxygen saturation in individuals with depressive disorders and sleep complaints, but this needs to be confirmed by prospective studies.

Algorithm for automatic detection of self-similarity and prediction of residual central respiratory events during continuous positive airway pressure.

Study ObjectivesSleep-disordered breathing is a significant risk factor for cardiometabolic and neurodegenerative diseases. High loop gain (HLG) is a driving mechanism of central sleep apnea or periodic breathing. This study presents a computational approach that identifies “expressed/manifest” HLG via a cyclical self-similarity feature in effort-based respiration signals.MethodsWorking under the assumption that HLG increases the risk of residual central respiratory events during continuous positive airway pressure (CPAP), the full night similarity, computed during diagnostic non-CPAP polysomnography (PSG), was used to predict residual central events during CPAP (REC), which we defined as central apnea index (CAI) higher than 10. Central apnea labels are obtained both from manual scoring by sleep technologists and from an automated algorithm developed for this study. The Massachusetts General Hospital sleep database was used, including 2466 PSG pairs of diagnostic and CPAP titration PSG recordings.ResultsDiagnostic CAI based on technologist labels predicted REC with an area under the curve (AUC) of 0.82 ± 0.03. Based on automatically generated labels, the combination of full night similarity and automatically generated CAI resulted in an AUC of 0.85 ± 0.02. A subanalysis was performed on a population with technologist-labeled diagnostic CAI higher than 5. Full night similarity predicted REC with an AUC of 0.57 ± 0.07 for manual and 0.65 ± 0.06 for automated labels.ConclusionsThe proposed self-similarity feature, as a surrogate estimate of expressed respiratory HLG and computed from easily accessible effort signals, can detect periodic breathing regardless of admixed obstructive features such as flow limitation and can aid the prediction of REC.

EL3-1 A way to research from the viewpoint of a sleep technologists

EL3-1 A way to research from the viewpoint of a sleep technologists