Respiratory event index underestimates severity of sleep apnea compared to apnea-hypopnea index.

Polygraphy (PG) is often used to diagnose obstructive sleep apnea (OSA). However, it does not use electroencephalography, and therefore cannot estimate sleep time or score arousals and related hypopneas. Consequently, the PG-derived respiratory event index (REI) differs from the polysomnography (PSG)-derived apnea-hypopnea index (AHI). In this study, we comprehensively analyzed the differences between AHI and REI. Conventional AHI and REI were calculated based on total sleep time (TST) and total analyzed time (TAT), respectively, from two different PSG datasets (n = 1561). Moreover, TAT-based AHI (AHITAT) and TST-based REI (REITST) were calculated. These indices were compared keeping AHI as the gold standard. The REI, AHITAT, and REITST were significantly lower than AHI (p < 0.0001, p ≤ 0.002, and p ≤ 0.01, respectively). The total classification accuracy of OSA severity based on REI was 42.1% and 72.8% for two datasets. Based on AHITAT, the accuracies were 68.4% and 85.9%, and based on REITST, they were 65.9% and 88.5% compared to AHI. AHI was most correlated with REITST (r = 0.98 and r = 0.99 for the datasets) and least with REI (r = 0.92 and r = 0.97). Compared to AHI, REI had the largest mean absolute errors (13.9 and 6.7) and REITST the lowest (5.9 and 1.9). REI had the lowest sensitivities (42.1% and 72.8%) and specificities (80.7% and 90.9%) in both datasets. Based on these present results, REI underestimates AHI. Furthermore, these results indicate that arousal-related hypopneas are an important measure for accurately classifying OSA severity.

Morbid obesity influences the nocturnal electrocardiogram wave and interval durations among suspected sleep apnea patients.

BACKGROUND: Obesity is a global issue with a major impact on cardiovascular health. This study explores how obesity influences nocturnal cardiac electrophysiology in suspected obstructive sleep apnea (OSA) patients. METHODS: We randomly selected 12 patients from each of the five World Health Organization body mass index (BMI) classifications groups (ntotal = 60) while keeping the group's age and sex matched. We evaluated 1965 nocturnal electrocardiography (ECG) samples (10 s) using modified lead II recorded during normal saturation conditions. R-wave peaks were detected and confirmed using dedicated software, with the exclusion of ventricular extrasystoles and artifacts. The duration of waves and intervals was manually marked. The average electric potential graphs were computed for each segment. Thresholds for abnormal ECG waveforms were P-wave > 120 ms, PQ interval > 200 ms, QRS complex > 120 ms for, and QTc > 440 ms. RESULTS: Obesity was significantly (p < .05) associated with prolonged conduction times. Compared to the normal weight (18.5 ≤ BMI < 25) group, the morbidly obese patients (BMI ≥ 40) had a significantly longer P-wave duration (101.7 vs. 117.2 ms), PQ interval (175.8 vs. 198.0 ms), QRS interval (89.9 vs. 97.7 ms), and QTc interval (402.8 vs. 421.2 ms). We further examined ECG waveform prolongations related to BMI. Compared to other patient groups, the morbidly obese patients had the highest number of ECG segments with PQ interval (44% of the ECG samples), QRS duration (14%), and QTc duration (20%) above the normal limits. CONCLUSIONS: Morbid obesity predisposes patients to prolongation of cardiac conduction times. This might increase the risk of arrhythmias, stroke, and even sudden cardiac death.

Increased Flow Limitation During Sleep Is Associated With Increased Psychomotor Vigilance Task Lapses in Individuals With Suspected OSA.

BACKGROUND: Impaired daytime vigilance is an important consequence of OSA, but several studies have reported no association between objective measurements of vigilance and the apnea-hypopnea index (AHI). Notably, the AHI does not quantify the degree of flow limitation, that is, the extent to which ventilation fails to meet intended ventilation (ventilatory drive). RESEARCH QUESTION: Is flow limitation during sleep associated with daytime vigilance in OSA? STUDY DESIGN AND METHODS: Nine hundred ninety-eight participants with suspected OSA completed a 10-min psychomotor vigilance task (PVT) before same-night in-laboratory polysomnography. Flow limitation frequency (percent of flow-limited breaths) during sleep was quantified using airflow shapes (eg, fluttering and scooping) from nasal pressure airflow. Multivariable regression assessed the association between flow limitation frequency and the number of lapses (response times > 500 ms, primary outcome), adjusting for age, sex, BMI, total sleep time, depression, and smoking status. RESULTS: Increased flow limitation frequency was associated with decreased vigilance: a 1-SD (35.3%) increase was associated with 2.1 additional PVT lapses (95% CI, 0.7-3.7; P = .003). This magnitude was similar to that for age, where a 1-SD increase (13.5 years) was associated with 1.9 additional lapses. Results were similar after adjusting for AHI, hypoxemia severity, and arousal severity. The AHI was not associated with PVT lapses (P = .20). In secondary exploratory analysis, flow limitation frequency was associated with mean response speed (P = .012), median response time (P = .029), fastest 10% response time (P = .041), slowest 10% response time (P = .018), and slowest 10% response speed (P = .005). INTERPRETATION: Increased flow limitation during sleep was associated with decreased daytime vigilance in individuals with suspected OSA, independent of the AHI. Flow limitation may complement standard clinical metrics in identifying individuals whose vigilance impairment most likely is explained by OSA.

Nasal Pressure Derived Airflow Limitation and Ventilation Measurements are Resilient to Reduced Signal Quality.

Obstructive sleep apnea is a disorder characterized by partial or complete airway obstructions during sleep. Our previously published algorithms use the minimally invasive nasal pressure signal routinely collected during diagnostic polysomnography (PSG) to segment breaths and estimate airflow limitation (using flow:drive) and minute ventilation for each breath. The first aim of this study was to investigate the effect of airflow signal quality on these algorithms, which can be influenced by oronasal breathing and signal-to-noise ratio (SNR). It was hypothesized that these algorithms would make inaccurate estimates when the expiratory portion of breaths is attenuated to simulate oronasal breathing, and pink noise is added to the airflow signal to reduce SNR. At maximum SNR and 0% expiratory amplitude, the average error was 2.7% for flow:drive, -0.5% eupnea for ventilation, and 19.7 milliseconds for breath duration (n = 257,131 breaths). At 20 dB and 0% expiratory amplitude, the average error was -15.1% for flow:drive, 0.1% eupnea for ventilation, and 28.4 milliseconds for breath duration (n = 247,160 breaths). Unexpectedly, simulated oronasal breathing had a negligible effect on flow:drive, ventilation, and breath segmentation algorithms across all SNRs. Airflow SNR ≥ 20 dB had a negligible effect on ventilation and breath segmentation, whereas airflow SNR ≥ 30 dB had a negligible effect on flow:drive. The second aim of this study was to explore the possibility of correcting these algorithms to compensate for airflow signal asymmetry and low SNR. An offset based on estimated SNR applied to individual breath flow:drive estimates reduced the average error to ≤ 1.3% across all SNRs at patient and breath levels, thereby facilitating for flow:drive to be more accurately estimated from PSGs with low airflow SNR.Clinical Relevance- This study demonstrates that our airflow limitation, ventilation, and breath segmentation algorithms are robust to reduced airflow signal quality.

Obstructive Sleep Apnea Patients With Atrial Arrhythmias Suffer From Prolonged Recovery From Desaturations.

OBJECTIVE: We aimed to investigate how acute and long-term effects of atrial arrhythmias affect the desaturation severity and characteristics determined from the oxygen saturation signal in obstructive sleep apnea (OSA) patients. METHODS: 520 suspected OSA patients were included in retrospective analyses. Eight desaturation area and slope parameters were calculated from blood oxygen saturation signals recorded during polysomnographic recordings. Patients were grouped based on whether they had previously diagnosed atrial arrhythmia (i.e., atrial fibrillation (AFib) or atrial flutter) or not. Furthermore, patients with a previous atrial arrhythmia diagnosis were sub-grouped based on whether they had continuous AFib or sinus rhythm during the polysomnographic recordings. Empirical cumulative distribution functions and linear mixed models were utilized to investigate the connection between diagnosed atrial arrhythmia and the desaturation characteristics. RESULTS: Patients with previous atrial arrhythmia diagnosis had greater desaturation recovery area when the 100% oxygen saturation baseline reference was considered (ß = 0.150--0.127, p ≤ 0.039) and more gradual recovery slopes (ß = -0.181 to -0.199, p < 0.004) than patients without a previous atrial arrhythmia diagnosis. Furthermore, patients with AFib had more gradual oxygen saturation fall and recovery slopes than patients with sinus rhythm. CONCLUSION: Desaturation recovery characteristics in the oxygen saturation signal contains essential information about the cardiovascular response to hypoxemic periods. SIGNIFICANCE: More comprehensive consideration of the desaturation recovery section could provide more detailed information about OSA severity, for example when developing new diagnostic parameters.

Power spectral analysis of the sleep electroencephalogram in positional obstructive sleep apnea.

OBJECTIVE/BACKGROUND: Previous studies have shown that obstructive sleep apnoea (OSA) is associated with reduced delta EEG and increased beta EEG power and increased EEG slowing ratio. There are however no studies that explore differences in sleep EEG between positional obstructive sleep apnoea (pOSA) and non-positional obstructive sleep apnoea (non-pOSA) patients. PATIENTS/METHODS: 556 of 1036 consecutive patients (246 of 556 were female) undertaking polysomnography (PSG) for the suspicion of OSA met the inclusion criteria for this study. We calculated power spectra of each sleep epoch using Welch's method with ten, 4-s overlapping windows. Outcome measures such as Epworth Sleepiness Scale, SF-36 Quality of Life, Functional Outcomes of Sleep Questionnaire and Pyschomotor Vigilance Task were compared between the groups. RESULTS: Patients with pOSA had greater delta EEG power in NREM and greater N3 proportions compared to their non-pOSA counterparts. There were no differences in theta (4-8Hz), alpha (8-12Hz), sigma (12-15Hz) or beta (15-25Hz) EEG power or EEG slowing ratio between the two groups. There were also no differences in the outcome measures between these two groups. The division of pOSA into spOSA and siOSA groups showed better sleep parameters in siOSA but with no difference in sleep power spectra. CONCLUSIONS: This study partially supports our hypothesis in showing that pOSA, compared to non-pOSA, is associated with increased delta EEG power but did not show any variation to beta EEG power or EEG slowing ratio. This limited improvement in sleep quality did not translate to measurable changes to outcomes, suggesting beta EEG power or EEG slowing ratio may be key factors.

A Comparison of Signal Combinations for Deep Learning-Based Simultaneous Sleep Staging and Respiratory Event Detection.

OBJECTIVE: Obstructive sleep apnea (OSA) is diagnosed using the apnea-hypopnea index (AHI), which is the average number of respiratory events per hour of sleep. Recently, machine learning algorithms for automatic AHI assessment have been developed, but many of them do not consider the individual sleep stages or events. In this study, we aimed to develop a deep learning model to simultaneously score both sleep stages and respiratory events. The hypothesis was that the scoring and subsequent AHI calculation could be performed utilizing pulse oximetry data only. METHODS: Polysomnography recordings of 877 individuals with suspected OSA were used to train the deep learning models. The same architecture was trained with three different input signal combinations (model 1: photoplethysmogram (PPG) and oxygen saturation (SpO 2); model 2: PPG, SpO 2, and nasal pressure; model 3: SpO 2, nasal pressure, electroencephalogram (EEG), oronasal thermocouple, and respiratory belts). RESULTS: Model 1 reached comparative performance with models 2 and 3 for estimating the AHI (model 1 intraclass correlation coefficient (ICC) = 0.946; model 2 ICC = 0.931; model 3 ICC = 0.945), and REM-AHI (model 1 ICC = 0.912; model 2 ICC = 0.921; model 3 ICC = 0.883). The automatic sleep staging accuracies (wake/N1/N2/N3/REM) were 69%, 70%, and 79% with models 1, 2, and 3, respectively. CONCLUSION: AHI can be estimated using pulse oximetry-based automatic scoring. Explicit scoring of sleep stages and respiratory events allows visual validation of the automatic analysis, and provides information on OSA phenotypes. SIGNIFICANCE: Automatic scoring of sleep stages and respiratory events with a simple pulse oximetry setup could allow cost-effective, large-scale screening of OSA.

Obstructive sleep apnea-related intermittent hypoxaemia is associated with impaired vigilance.

Obstructive sleep apnea (OSA)-related intermittent hypoxaemia is a potential risk factor for different OSA comorbidities, for example cardiovascular disease. However, conflicting results are found as to whether intermittent hypoxaemia is associated with impaired vigilance. Therefore, we aimed to investigate how desaturation characteristics differ between the non-impaired vigilance and impaired vigilance patient groups formed based on psychomotor vigilance task (PVT) performance and compared with traditional OSA severity parameters. The study population comprised 863 patients with suspected OSA who underwent a PVT test before polysomnography. The conventional OSA parameters, for example, the apnea-hypopnea index, oxygen desaturation index, and arousal index were computed. Furthermore, the median desaturation area, fall area, recovery area, and desaturation depth were computed with the pre-event baseline reference and with reference to the 100% oxygen saturation level. Patients were grouped into best- and worst-performing quartiles based on the number of lapses in PVT (Q1: PVT lapses <5 and Q4: PVT lapses >36). The association between parameters and impaired vigilance was evaluated by cumulative distribution functions (CDFs) and binomial logistic regression. Based on the CDFs, patients in Q4 had larger desaturation areas, recovery areas, and deeper desaturations when these were referenced to 100% saturation compared with Q1. The odds ratio (OR) of the median desaturation area (OR = 1.56), recovery area (OR = 1.71), and depth (OR = 1.65) were significantly elevated in Q4 in regression models. However, conventional OSA parameters were not significantly associated with impaired vigilance (ORs: 0.79-1.09). Considering desaturation parameters with a 100% SpO2 reference in the diagnosis of OSA could provide additional information on the severity of OSA and related daytime vigilance impairment.

Inter-sleep stage variations in corrected QT interval differ between obstructive sleep apnea patients with and without stroke history.

Obstructive sleep apnea (OSA) is related to the progression of cardiovascular diseases (CVD); it is an independent risk factor for stroke and is also prevalent post-stroke. Furthermore, heart rate corrected QT (QTc) is an important predictor of the risk of arrhythmia and CVD. Thus, we aimed to investigate QTc interval variations in different sleep stages in OSA patients and whether nocturnal QTc intervals differ between OSA patients with and without stroke history. 18 OSA patients (apnea-hypopnea index (AHI)≥15) with previously diagnosed stroke and 18 OSA patients (AHI≥15) without stroke history were studied. Subjects underwent full polysomnography including an electrocardiogram measured by modified lead II configuration. RR, QT, and QTc intervals were calculated in all sleep stages. Regression analysis was utilized to investigate possible confounding effects of sleep stages and stroke history on QTc intervals. Compared to patients without previous stroke history, QTc intervals were significantly higher (ß = 34, p<0.01) in patients with stroke history independent of age, sex, body mass index, and OSA severity. N3 sleep (ß = 5.8, p<0.01) and REM sleep (ß = 2.8, p<0.01) increased QTc intervals in both patient groups. In addition, QTc intervals increased progressively (p<0.05) towards deeper sleep in both groups; however, the magnitude of changes compared to the wake stage was significantly higher (p<0.05) in patients with stroke history. The findings of this study indicate that especially in deeper sleep, OSA patients with a previous stroke have an elevated risk for QTc prolongation further increasing the risk for ventricular arrhythmogenicity and sudden cardiac death.

Desaturation event scoring criteria affect the perceived severity of nocturnal hypoxic load.

OBJECTIVES/BACKGROUND: Interest in using blood oxygen desaturations in the diagnostics of sleep apnea has risen in recent years. However, no standardized criteria for desaturation scoring exist which complicates the drawing of solid conclusions from literature. PATIENTS/METHODS: We investigated how different desaturation scoring criteria affect the severity of nocturnal hypoxic load and the prediction of impaired daytime vigilance in 845 patients. Desaturations were scored based on three features: 1) minimum oxygen saturation drop during the event (2-20%, 1% interval), 2) minimum duration of the event (2-20s, 1s interval), and 3) maximum plateau duration within the event (5-60s, 5s interval), resulting in 4332 different scoring criteria. The hypoxic load was described with oxygen desaturation index (ODI), desaturation severity (DesSev), and desaturation duration (DesDur) parameters. Association between hypoxic load and impaired vigilance was investigated with covariate-adjusted area under curve (AUC) analyses by dividing patients into normal (≤5 lapses) and impaired (≥36 lapses) vigilance groups based on psychomotor vigilance task performance. RESULTS: The severity of hypoxic load varied greatly between different scoring criteria. For example, median ODI ranged between 0.4 and 12.9 events/h, DesSev 0.01-0.23 %-point, and DesDur 0.3-9.6 %-point when the minimum transient drop criterion of 3% was used and other two features were altered. Overall, the minimum transient drop criterion had the largest effect on parameter values. All models with differently determined parameters predicted impaired vigilance moderately (AUC = 0.722-0.734). CONCLUSIONS: Desaturation scoring criteria greatly affected the severity of hypoxic load. However, the difference in the prediction of impaired vigilance between different criteria was rather small.

Randomized controlled trial on the efficacy of audio-visual health educational materials on CPAP adherence: the AHEAD trial.

STUDY OBJECTIVES: Educational interventions have been proposed to improve continuous positive airway pressure (CPAP) adherence; however, studies to date have not demonstrated robust effectiveness, due to methodological issues. Furthermore, these educational interventions have not specifically targeted low health literacy communication techniques, which have been demonstrated to improve outcomes in numerous other chronic diseases. We hypothesized that the addition of low-cost audio-visual educational videos (EVs) to usual standard-of-care (SC) education would improve CPAP adherence in adults with obstructive sleep apnea (OSA) syndrome. METHODS: At CPAP initiation, treatment-naïve adults with OSA syndrome were randomized to (1) usual SC or (2) SC + 5 EVs showing a patient's journey, designed with low health literacy communication techniques to teach patients about OSA and CPAP therapy. The primary endpoint was CPAP usage at 2 months (hours/night) and secondary endpoints were CPAP usage at 12 months and percentage of patients with ≥ 4 hours/night use at 2 months and 12 months. RESULTS: One hundred and ninety-five patients were randomized (SC 99, EV 96), with a mean age of 57 years (interquartile range [IQR] 44.1-64.8 years). There were no statistically significant differences in patient characteristics at baseline between the SC vs EV groups, with the diagnostic apnea-hypopnea index of 34 events/h (IQR 21-59 events/h) vs 30 events/h (IQR 20-50 events/h) and Epworth Sleepiness Scale score of 12.8 ± 6 vs 11.7 ± 5. At 2 months, there was no significant difference in hours of CPAP usage (SC: 3.45 hours/night [95% confidence interval (CI): 2.76 to 4.13] vs EV: 3.75 hours/night [95% CI: 3.14 to 4.37]) nor in proportion with adequate usage or overall commencement rate. However, at 12 months, there was a significant difference in hours of CPAP usage (SC: 2.50 hours/night [95% CI: 1.94 to 3.06] vs EV: 3.66 hours/night [95% CI: 2.92 to 4.40]). The probability of adequate CPAP usage at 12 months was higher in the intervention arm (odds ratio: 1.33; 95% CI: 1.04 to 1.7; P = .013). Patients with low education backgrounds benefitted substantially from the EV intervention compared with SC (mean difference at 12 months = 2.47 hours/night usage; 95% CI: 1.01 to 2.93; P < .01). CONCLUSIONS: Low health literacy-designed EVs improve CPAP adherence at 12 months compared with SC, with the greatest impact in patients with a low educational background. CLINICAL TRIAL REGISTRATION: Registry: Australian New Zealand Clinical Trials Registry; Name: Randomised controlled trial on the efficacy of audio-visual health educational materials on sleep health literacy and continuous positive airway pressure (CPAP) adherence in Sleep Clinic patients; URL: https://www.australianclinicaltrials.gov.au/anzctr/trial/ACTRN12619000523101; Identifier: ACTRN12619000523101. CITATION: Ellender CM, Samaranayake C, Reid N, et al. Randomized controlled trial on the efficacy of audio-visual health educational materials on CPAP adherence: the AHEAD trial. J Clin Sleep Med. 2022;18(11):2617-2625.

Association between early stage N2 sleep spindle burst characteristics and vigilance groups: an observational study on patients from a tertiary sleep centre.

Objective.Obstructive sleep apnoea (OSA) is associated with impaired vigilance. This paper examines the hypothesis that sleep spindle (Sp) characteristics during nocturnal sleep can be mapped to vigilance deficits measured by the psychomotor vigilance task (PVT) in patients with OSA.Approach.The PVT was performed prior to In-laboratory Polysomnography for 250 patients. PVT outcomes were clustered into three vigilance groups (VGs). Spindles were scored manually for a Training Cohort of 55 patients, (9491 Sps) across different blocks of NREM sleep (SBs) and validated in a Test Cohort (25 patients, 4867 Sps). We proposed a novel set of Sp features including a spindle burst index (SBI), which quantifies the burst characteristics of spindles and constructed models mapping them to VGs. We also explored the performance of conventional Sp features (such as Sp number and density) in our modelling approach.Main results.In the Training Cohort, we observed statistically significant differences in the SBI across VGs and SBs independent of OSA severity (1st stage N2 SBI;p= <0.001 across VGs). In the Test Cohort, a Model based on the proposed SBI predicted VG membership with 88% accuracy. A model based on conventional Sp features mapped to VGs with 80% accuracy, and a model using mixed burst and conventional features reached an accuracy of 88%.Significance.Spindle features measured during diagnostic In-laboratory polysomnography measurements can be mapped to PVT outcomes. The novel SBI proved useful for exploring the relationship between PVT outcomes and sleep. Further studies in larger populations are needed to verify these conclusions.

QTc prolongation is associated with severe desaturations in stroke patients with sleep apnea.

BACKGROUND: Obstructive sleep apnea (OSA) is associated with vascular diseases from which stroke and sudden cardiac death are the most significant ones. It is known that disturbances of the autonomic nervous system and electrocardiographic changes are seen in patients with a previous cerebrovascular event. However, the pathophysiological cascade between breathing cessations, autonomic regulation, and cardiovascular events is not fully understood. METHODS: We aimed to investigate the acute effect of desaturation on repolarisation in OSA patients with a previous stroke. We retrospectively analysed heart-rate corrected QT (QTc) intervals before, within, and after 975 desaturations in OSA patients with a stroke history and at least moderate sleep apnea (apnea-hypopnea index ≥ 15 events/h, n = 18). For the control population (n = 18), QTc intervals related to 1070 desaturation were analysed. Desaturations were assigned to groups according to their length and duration. Groupwise comparisons and regression analyses were further executed to investigate the influence of desaturation features on repolarization. RESULTS: In the stroke population the QTc prolonged at least 11 ms during 27.1% of desaturations, and over 20 ms during 12.2% of desaturations. QTc was significantly prolonged during longer (> 30 s, p < 0.04) and deeper (> 7%, p < 0.03) desaturations. Less severe desaturations didn't influence QTc. In median, QTc prolonged 7.5 ms during > 45 s desaturations and 7.4 ms during > 9% deep desaturations. In the control population, QTc prolongation was observed but to a significantly lesser extent than in stroke patients. In addition, desaturation duration was found to be an independent predictor of QTc prolongation (ß = 0.08, p < 0.001) among all study patients. CONCLUSIONS: We demonstrated that longer (> 30 s) and deeper (> 7%) desaturations prolong QTc in patients with stroke history. A significant proportion of desaturations produced clinically relevant QTc prolongation. As it is known that a long QTc interval is associated with lethal arrhythmias, this finding might in part explain the pathophysiological sequelae of cardiovascular mortality in OSA patients with a history of stroke.

Usefulness of self-administered questionnaires in screening for direct referral for polysomnography without sleep physician review.

STUDY OBJECTIVES: To evaluate self-administered screening questionnaires (Epworth Sleepiness Scale [ESS], Berlin, OSA50, and STOP-Bang questionnaires) in patients considered for polysomnography for probable obstructive sleep apnea suitable for direct polysomnography without sleep specialist review and to evaluate the usefulness of combining questionnaires in this population. METHODS: This was a retrospective review of tertiary sleep center referrals (November 2017 to April 2020) where ≥ 3 screening questionnaires were completed and type 1 polysomnography was performed. Sensitivity, specificity, positive and negative predictive values, and likelihood ratios to detect an apnea-hypopnea index (AHI) ≥ 15 or ≥ 30 events/h were calculated for each questionnaire (with or without ESS ≥ 8) or any positive questionnaire with ESS ≥ 8. RESULTS: We included 2,152 patients. The questionnaires were completed in the majority (ESS 96%, Berlin 77%, OSA50 84%, and STOP-Bang 90%) of referrals. Berlin was most sensitive (82.5% and 85% to detect AHI ≥ 15 and ≥ 30 events/h, respectively) but least specific (23% both thresholds). STOP-Bang was least sensitive (66% and 42%, respectively) but most specific (68% and 60%, respectively). Sensitivity declined for the Berlin, OSA50 and STOP-Bang questionnaires when combined with ESS ≥ 8. Combining any questionnaire with ESS ≥ 8 returned an intermediate sensitivity of 61% and 73% and a specificity of 49% and 47% for AHI ≥ 15 and ≥ 30 events/h, respectively. STOP-Bang alone was predictive of obstructive sleep apnea on multivariate analysis but was only associated with a clinically nonsignificant positive likelihood ratio. However, STOP-Bang is associated with unacceptable false-positive and -negative rates, which did not support its use. CONCLUSIONS: Self-administered questionnaires are inadequate in patients under consideration for polysomnography and should not be used as clinical support for suitability of direct polysomnography without sleep specialist review. Combining questionnaires causes deteriorated performance. CITATION: Hukins C, Duce B. Usefulness of self-administered questionnaires in screening for direct referral for polysomnography without sleep physician review. J Clin Sleep Med. 2022;18(5):1405-1412.

Gamma Power of Electroencephalogram Arousal Is Modulated by Respiratory Event Type and Severity in Obstructive Sleep Apnea.

OBJECTIVE: We aimed to investigate the differences in electroencephalogram (EEG) gamma power (30-40 Hz) of respiratory arousals between varying types and severities of respiratory events, and in different sleep stages. METHODS: Power spectral densities of EEG signals from diagnostic Type I polysomnograms of 869 patients with clinically suspected obstructive sleep apnea were investigated. Arousal gamma powers were compared between sleep stages, and between the type (obstructive apnea and hypopnea) and duration (10-20 s, 20-30 s, and >30 s) of the related respiratory event. Moreover, we investigated whether the presence of a ≥3% blood oxygen desaturation influenced the arousal gamma power. RESULTS: Gamma power of respiratory arousals was the lowest in Stage R sleep and increased from Stage N1 towards Stage N3. Gamma power was higher when the arousals were caused by obstructive apneas compared to hypopneas. Moreover, arousal gamma power increased when the duration of the related apnea increased, whereas an increase in the hypopnea duration did not have a similar effect. Furthermore, respiratory events associated with desaturations increased the arousal gamma power more than respiratory events not associated with desaturations. CONCLUSION: Gamma power of respiratory arousals increased towards deeper sleep and as the severity of the related respiratory event increased in terms of type and duration of obstruction, and presence of desaturation. SIGNIFICANCE: As increased gamma power might indicate a greater shift towards wakefulness, the present findings demonstrate that the respiratory arousal intensity and the magnitude of sleep disruption may vary depending on the event type and severity.

Assessment of obstructive sleep apnea-related sleep fragmentation utilizing deep learning-based sleep staging from photoplethysmography.

STUDY OBJECTIVES: To assess the relationship between obstructive sleep apnea (OSA) severity and sleep fragmentation, accurate differentiation between sleep and wakefulness is needed. Sleep staging is usually performed manually using electroencephalography (EEG). This is time-consuming due to complexity of EEG setup and the amount of work in manual scoring. In this study, we aimed to develop an automated deep learning-based solution to assess OSA-related sleep fragmentation based on photoplethysmography (PPG) signal. METHODS: A combination of convolutional and recurrent neural networks was used for PPG-based sleep staging. The models were trained using two large clinical datasets from Israel (n = 2149) and Australia (n = 877) and tested separately on three-class (wake/NREM/REM), four-class (wake/N1 + N2/N3/REM), and five-class (wake/N1/N2/N3/REM) classification. The relationship between OSA severity categories and sleep fragmentation was assessed using survival analysis of mean continuous sleep. Overlapping PPG epochs were applied to artificially obtain denser hypnograms for better identification of fragmented sleep. RESULTS: Automatic PPG-based sleep staging achieved an accuracy of 83.3% on three-class, 74.1% on four-class, and 68.7% on five-class models. The hazard ratios for decreased mean continuous sleep compared to the non-OSA group obtained with Cox proportional hazards models with 5-s epoch-to-epoch intervals were 1.70, 3.30, and 8.11 for mild, moderate, and severe OSA, respectively. With EEG-based hypnograms scored manually with conventional 30-s epoch-to-epoch intervals, the corresponding hazard ratios were 1.18, 1.78, and 2.90. CONCLUSIONS: PPG-based automatic sleep staging can be used to differentiate between OSA severity categories based on sleep continuity. The differences between the OSA severity categories become more apparent when a shorter epoch-to-epoch interval is used.

Automatic Respiratory Event Scoring in Obstructive Sleep Apnea Using a Long Short-Term Memory Neural Network.

The diagnosis of obstructive sleep apnea is based on daytime symptoms and the frequency of respiratory events during the night. The respiratory events are scored manually from polysomnographic recordings, which is time-consuming and expensive. Therefore, automatic scoring methods could considerably improve the efficiency of sleep apnea diagnostics and release the resources currently needed for manual scoring to other areas of sleep medicine. In this study, we trained a long short-term memory neural network for automatic scoring of respiratory events using input signals from peripheral blood oxygen saturation, thermistor-airflow, nasal pressure -airflow, and thorax respiratory effort. The signals were extracted from 887 in-lab polysomnography recordings. 787 patients with suspected sleep apnea were used to train the neural network and 100 patients were used as an independent test set. The epoch-wise agreement between manual and automatic neural network scoring was high (88.9%, κ = 0.728). In addition, the apnea-hypopnea index (AHI) calculated from the automated scoring was close to the manually determined AHI with a mean absolute error of 3.0 events/hour and an intraclass correlation coefficient of 0.985. The neural network approach for automatic scoring of respiratory events achieved high accuracy and good agreement with manual scoring. The presented neural network could be used for analysis of large research datasets that are unfeasible to score manually, and has potential for clinical use in the future In addition, since the neural network scores individual respiratory events, the automatic scoring can be easily reviewed manually if desired.

Adequate health literacy is associated with adherence to continuous positive airway pressure in adults with obstructive sleep apnea.

Study Objectives: Obstructive sleep apnea (OSA) is a chronic disease with significant health implications and adequate adherence to continuous positive airway pressure (CPAP) is essential for effective treatment. In many chronic diseases, health literacy has been found to predict treatment adherence and outcomes. In this study, the aim was to determine the health literacy of a sleep clinic population and evaluate the association between health literacy and CPAP adherence. Methods: A prospective cohort study was undertaken, recruiting 104 consecutive patients with a variety of sleep diagnoses. The Short Form Rapid Estimate of Adult Literacy in Medicine (REALM-SF), a validated questionnaire, was administered to measure health literacy. In a sub-group of 91 patients prescribed CPAP for OSA, CPAP usage was measured, with adequate usage defined as greater than 4 h/night CPAP therapy. Results: Seventy-one percent of the sleep clinic cohort was found to have adequate health literacy, as measured by the REALM-SF. In those prescribed CPAP for OSA, inadequate health literacy was associated with a twofold increased risk for inadequate CPAP usage (adjusted odds ratio [OR] 2.9, 95% CI: 1.1 to 8.22, p = 0.045). There was a 1.7 h/night difference in median CPAP usage comparing those with adequate to inadequate health literacy (4.6 h vs. 6.3 h/night). Conclusions: The majority of this sleep disorders cohort had adequate health literacy as measured by the REALM-SF questionnaire. However, inadequate health literacy appears to be an independent predictor of treatment adherence and may represent a modifiable risk factor of poor treatment outcomes in OSA.

Polysomnographic risk factors for vigilance-related cognitive decline and obstructive sleep apnea.

PURPOSE: Cognitive decline (CD) and obstructive sleep apnea (OSA) are often comorbid. Some modifiable risk factors (RF) for CD are also associated with OSA. Diagnostic polysomnography (PSG) measures these RF and may identify at risk patients prior to the onset of CD. We aim to determine whether there are severe RF associated with established CD and an increasing severity of OSA that could identify patients at risk for CD for medical intervention. METHODS: We gathered information from subjects having type 1 PSG for suspected OSA. The psychomotor vigilance task (PVT) measured established CD (group 0 and group1). We compared levels of severe RF in group 0 and group 1 with a larger group (group 2) without the PVT. We used severe standardized values of excessive daytime sleepiness (Epworth Sleepiness Score [ESS]), overnight change of systolic blood pressure (ΔSBP), change of oxygen desaturation (ΔSpO2), and sleep arousal (ArI) as RF. We compared the severe levels of ESS, ΔSBP, ΔSpO2, and ArI by group and OSA severity. RESULTS: A total of 136 patients underwent diagnostic PSG. PVT parameters were available for 43 subjects. The severity of the RF was consistent with risk for CD (ΔSBP 22.0 ± 5.6, ESS 18.2 ± 2.2, ArI 58.8 ± 18.7, ΔSpO2 61.7 ± 21.9). The levels of RF increased with increasing severity of OSA. There were significant between-group differences for severe ΔSpO2 (p = 0.004) and ΔSpO2 + ArI (p = 0.019). CONCLUSION: The levels of RF increase with increasing OSA severity. Subjects with severe RF ΔSpO2 and ΔSpO2 + ArI are likely to have PVT-determined CD. Risk factor analysis may screen for CD.