Identifying Risk of Postoperative Cardiorespiratory Complications in OSA.

BACKGROUND: Patients with OSA are at increased risk of postoperative cardiorespiratory complications and death. Attempts to stratify this risk have been inadequate, and predictors from large, well-characterized cohort studies are needed. RESEARCH QUESTION: What is the relationship between OSA severity, defined by various polysomnography-derived metrics, and risk of postoperative cardiorespiratory complications or death, and which metrics best identify such risk? STUDY DESIGN AND METHODS: In this cohort study, 6,770 consecutive patients who underwent diagnostic polysomnography for possible OSA and a procedure involving general anesthesia within a period of 2 years before and at least 5 years after polysomnography. Participants were identified by linking polysomnography and health databases. Relationships between OSA severity measures and the composite primary outcome of cardiorespiratory complications or death within 30 days of hospital discharge were investigated using univariable and multivariable analyses. RESULTS: The primary outcome was observed in 5.3% (n = 361) of the cohort. Although univariable analysis showed strong dose-response relationships between this outcome and multiple OSA severity measures, multivariable analysis showed its independent predictors were: age older than 65 years (OR, 2.67 [95% CI, 2.03-3.52]; P < .0001), age 55.1 to 65 years (OR, 1.47 [95% CI, 1.09-1.98]; P = .0111), time between polysomnography and procedure of ≥ 5 years (OR, 1.32 [95% CI, 1.02-1.70]; P = .0331), BMI of ≥ 35 kg/m2 (OR, 1.43 [95% CI, 1.13-1.82]; P = .0032), presence of known cardiorespiratory risk factor (OR, 1.63 [95% CI, 1.29-2.06]; P < .0001), > 4.7% of sleep time at an oxygen saturation measured by pulse oximetry of < 90% (T90; OR, 1.91 [95% CI, 1.51-2.42]; P < .0001), and cardiothoracic procedures (OR, 7.95 [95% CI, 5.71-11.08]; P < .0001). For noncardiothoracic procedures, age, BMI, presence of known cardiorespiratory risk factor, and percentage of sleep time at an oxygen saturation of < 90% remained the significant predictors, and a risk score based on their ORs was predictive of outcome (area under receiver operating characteristic curve, 0.7 [95% CI, 0.64-0.75]). INTERPRETATION: These findings provide a basis for better identifying high-risk patients with OSA and determining appropriate postoperative care.

Polysomnographic characteristics of excessive daytime sleepiness phenotypes in obstructive sleep apnea: results from the international sleep apnea global interdisciplinary consortium.

STUDY OBJECTIVES: Excessive daytime sleepiness (EDS) is a major symptom of obstructive sleep apnea (OSA). Traditional polysomnographic (PSG) measures only partially explain EDS in OSA. This study analyzed traditional and novel PSG characteristics of two different measures of EDS among patients with OSA. METHODS: Sleepiness was assessed using the Epworth Sleepiness Scale (>10 points defined as "risk of dozing") and a measure of general sleepiness (feeling sleepy ≥ 3 times/week defined as "feeling sleepy"). Four sleepiness phenotypes were identified: "non-sleepy," "risk of dozing only," "feeling sleepy only," and "both at risk of dozing and feeling sleepy." RESULTS: Altogether, 2083 patients with OSA (69% male) with an apnea-hypopnea index (AHI) ≥ 5 events/hour were studied; 46% were "non-sleepy," 26% at "risk of dozing only," 7% were "feeling sleepy only," and 21% reported both. The two phenotypes at "risk of dozing" had higher AHI, more severe hypoxemia (as measured by oxygen desaturation index, minimum and average oxygen saturation [SpO2], time spent < 90% SpO2, and hypoxic impacts) and they spent less time awake, had shorter sleep latency, and higher heart rate response to arousals than "non-sleepy" and "feeling sleepy only" phenotypes. While statistically significant, effect sizes were small. Sleep stages, frequency of arousals, wake after sleep onset and limb movement did not differ between sleepiness phenotypes after adjusting for confounders. CONCLUSIONS: In a large international group of patients with OSA, PSG characteristics were weakly associated with EDS. The physiological measures differed among individuals characterized as "risk of dozing" or "non-sleepy," while "feeling sleepy only" did not differ from "non-sleepy" individuals.

The interrelationships between sleep regularity, obstructive sleep apnea, and hypertension in a middle-aged community population.

STUDY OBJECTIVES: Little is known about the interrelationships between sleep regularity, obstructive sleep apnea (OSA) and important health markers. This study examined whether irregular sleep is associated with OSA and hypertension, and if this modifies the known association between OSA and hypertension. METHODS: Six hundred and two adults (age mean(SD) = 56.96(5.51) years, female = 60%) from the Raine Study who were not evening or night shift workers were assessed for OSA (in-laboratory polysomnography; apnea-hypopnea index ≥ 15 events/hour), hypertension (doctor diagnosed, or systolic blood pressure ≥140 mmHg and/or diastolic ≥90 mmHg) and sleep (wrist actigraphy for ≥5 days). A sleep regularity index (SRI) was determined from actigraphy. Participants were categorized by tertiles as severely irregular, mildly irregular, or regular sleepers. Logistic regression models examined the interrelationships between SRI, OSA and hypertension. Covariates included age, sex, body mass index, actigraphy sleep duration, insomnia, depression, activity, alcohol, smoking, and antihypertensive medication. RESULTS: Compared to regular sleepers, participants with mildly irregular (OR 1.97, 95% confidence intervals [CI] 1.20 to 3.27) and severely irregular (OR 2.06, 95% CI: 1.25 to 3.42) sleep had greater odds of OSA. Compared to those with no OSA and regular sleep, OSA and severely irregular sleep combined had the highest odds of hypertension (OR 2.34 95% CI: 1.07 to 5.12; p for interaction = 0.02) while those with OSA and regular/mildly irregular sleep were not at increased risk (p for interaction = 0.20). CONCLUSIONS: Sleep irregularity may be an important modifiable target for hypertension among those with OSA.

Sleep apnea multi-level surgery trial: long-term observational outcomes.

STUDY OBJECTIVES: The sleep apnea multi-level surgery (SAMS) randomized clinical trial showed surgery improved outcomes at 6 months compared to ongoing medical management in patients with moderate or severe obstructive sleep apnea (OSA) who failed continuous positive airway pressure therapy. This study reports the long-term outcomes of the multi-level surgery as a case series. METHODS: Surgical participants were reassessed >2 years postoperatively with the same outcomes reported in the main SAMS trial. Primary outcomes were apnea-hypopnea index (AHI) and Epworth sleepiness scale (ESS), with secondary outcomes including other polysomnography measures, symptoms, quality of life, and adverse events. Long-term effectiveness (baseline to long-term follow-up [LTFU]) and interval changes (6 month to LTFU) were assessed using mixed effects regression models. Control participants were also reassessed for rate of subsequent surgery and outcomes. RESULTS: 36/48 (75%) of surgical participants were reevaluated (mean (standard deviation)) 3.5 (1.0) years following surgery, with 29 undergoing polysomnography. AHI was 41/h (23) at preoperative baseline and 21/h (18) at follow-up, representing persistent improvement of -24/h (95% CI -32, -17; p < 0.001). ESS was 12.3 (3.5) at baseline and 5.5 (3.9) at follow-up, representing persistent improvement of -6.8 (95% CI -8.3, -5.4; p < 0.001). Secondary outcomes were improved long term, and adverse events were minor. Interval change analysis suggests stability of outcomes. 36/43 (84%) of the control participants were reevaluated, with 25 (69%) reporting subsequent surgery, with symptom and quality of life improvements. CONCLUSION: Multi-level upper airway surgery improves OSA burden with long-term maintenance of treatment effect in adults with moderate or severe OSA in whom conventional therapy failed. CLINICAL TRIAL: Multi-level airway surgery in patients with moderate-severe obstructive sleep apnea (OSA) who have failed medical management to assess change in OSA events and daytime sleepiness; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366019&isReview=true; ACTRN12614000338662.

Early life predictors of obstructive sleep apnoea in young adults: Insights from a longitudinal community cohort (Raine study).

OBJECTIVE: Early-life obstructive sleep apnoea (OSA) predictors are unavailable for young adults. This study identifies early-life factors predisposing young adults to OSA. METHODS: This retrospective study included 923 young adults and their mothers from the Western Australian Pregnancy Raine Study Cohort. OSA at 22 years was determined from in-laboratory polysomnography. Logistic regression was used to identify maternal and neonatal factors associated with OSA in young adulthood. RESULTS: OSA was observed in 20.8% (192) participants. Maternal predictors of OSA included gestational diabetes mellitus (odds ratio (OR) 9.54, 95% confidence interval (CI) 1.7, 58.5, P = 0.011), preterm delivery (OR 3.18, 95%CI 1.1,10.5, P = 0.043), preeclampsia (OR 2.95, 95%CI 1.1,8.0, P = 0.034), premature rupture of membranes (OR 2.46, 95%CI 1.2, 5.2, P = 0.015), age ≥35 years (OR 2.28, 95%CI 1.2,4.4, P = 0.011), overweight and obesity (pregnancy BMI≥25 kg/m2) (OR 2.00, 95%CI 1.2,3.2, P = 0.004), pregnancy-induced hypertension (OR 1.89, 95%CI 1.1,3.2, P = 0.019), and Chinese ethnicity (OR 2.36,95%CI 1.01,5.5, P = 0.047). Neonatal predictors included male child (OR 2.10, 95%CI 1.5,3.0, P < 0.0001), presence of meconium-stained liquor during delivery (OR 1.60, 95%CI 1.0,2.5, P = 0.044) and admission to special care nursery (OR 1.51 95%CI 1.0,2.2, P = 0.040). Higher birth lengths reduced OSA odds by 7% for each centimetre (OR 0.93, 95%CI 0.87, 0.99, P = 0.033). CONCLUSIONS: A range of maternal and neonatal factors predict OSA in young adults, including those related to poor maternal metabolic health, high-risk pregnancy and stressful perinatal events. This information could assist in the early identification and management of at-risk individuals and indicates that better maternal health may reduce the likelihood of young adults developing OSA.

Estimating sleep duration: performance of open-source processing of actigraphy compared to in-laboratory polysomnography in the community.

Comparisons of actigraphy findings between studies are challenging given differences between brand-specific algorithms. This issue may be minimized by using open-source algorithms. However, the accuracy of actigraphy-derived sleep parameters processed in open-source software needs to be assessed against polysomnography (PSG). Middle-aged adults from the Raine Study (n = 835; F 58%; Age 56.7 ± 5.6 years) completed one night of in-laboratory PSG and concurrent actigraphy (GT3X+ ActiGraph). Actigraphic measures of total sleep time (TST) were analyzed and processed using the open-source R-package GENEActiv and GENEA data in R (GGIR) with and without a sleep diary and additionally processed using proprietary software, ActiLife, for comparison. Bias and agreement (intraclass correlation coefficient) between actigraphy and PSG were examined. Common PSG and sleep health variables associated with the discrepancy between actigraphy, and PSG TST were examined using linear regression. Actigraphy, assessed in GGIR, with and without a sleep diary overestimated PSG TST by (mean ± SD) 31.0 ± 50.0 and 26.4 ± 69.0 minutes, respectively. This overestimation was greater (46.8 ± 50.4 minutes) when actigraphy was analyzed in ActiLife. Agreement between actigraphy and PSG TST was poor (ICC = 0.27-0.44) across all three methods of actigraphy analysis. Longer sleep onset latency and longer wakefulness after sleep onset were associated with overestimation of PSG TST. Open-source processing of actigraphy in a middle-aged community population, agreed poorly with PSG and, on average, overestimated TST. TST overestimation increased with increasing wakefulness overnight. Processing of actigraphy without a diary in GGIR was comparable to when a sleep diary was used and comparable to actigraphy processed with proprietary algorithms in ActiLife.

Does OSA Increase Risk for Cancer?: A Large Historical Sleep Clinic Cohort Study.

BACKGROUND: The relationship between OSA and cancer is unclear. RESEARCH QUESTION: What is the association between OSA and cancer prevalence and incidence in a large Western Australian sleep clinic cohort (N = 20,289)? STUDY DESIGN AND METHODS: OSA severity was defined by apnea-hypopnea index (AHI) and nocturnal hypoxemia (duration and percentage at oxygen saturation < 90%) measured by in-laboratory polysomnogram. Measures of potential confounding included age, sex, BMI, smoking status, socioeconomic status, and BP. Outcomes were determined from the Western Australian cancer and death registries. Analyses were confined within periods using consistent AHI scoring criteria: January 1, 1989, to July 31, 2002 (American Sleep Disorders Association criteria), and August 1, 2002, to June 30, 2013 (Chicago criteria). We examined associations of AHI and nocturnal hypoxemia with cancer prevalence using logistic regression and cancer incidence using Cox regression analyses. RESULTS: Cancer prevalence at baseline was 329 of 10,561 in the American Sleep Disorders Association period and 633 of 9,728 in the Chicago period. Nocturnal hypoxemia but not AHI was independently associated with prevalent cancer following adjustment for participant age, sex, BMI, smoking status, socioeconomic status, and BP. Of those without prevalent cancer, cancer was diagnosed in 1,950 of 10,232 (American Sleep Disorders Association) and 623 of 9,095 (Chicago) participants over a median follow-up of 11.2 years. Compared with the reference category (no OSA, AHI < 5 events per hour), univariable models estimated higher hazard ratios for cancer incidence for mild (AHI 5-15 events per hour), moderate (AHI 15.1-30 events per hour), and severe (AHI > 30 events per hour) OSA. Multivariable analyses consistently revealed associations between age and, in some cases, sex, BMI, and smoking status, with cancer incidence. After adjusting for confounders, multivariable models showed no independent association between OSA severity and increased cancer incidence. INTERPRETATION: Nocturnal hypoxemia is independently associated with prevalent cancer. OSA severity is associated with incident cancer, although this association seems secondary to other risk factors for cancer development. OSA is not an independent risk factor for cancer incidence.

Facial and Intraoral Photographic Traits Related to Sleep Apnea in a Clinical Sample with Genetic Ancestry Analysis.

Rationale: Craniofacial and pharyngeal morphology influences risk for obstructive sleep apnea (OSA). Quantitative photography provides phenotypic information about these anatomical factors and is feasible in large samples. However, whether associations between morphology and OSA severity differ among populations is unknown. Objectives: The aim of this study was to examine this question in a large sample encompassing people from different ancestral backgrounds. Methods: Participants in SAGIC (Sleep Apnea Global Interdisciplinary Consortium) with genotyping data were included (N = 2,393). Associations between photography-based measures and OSA severity were assessed using linear regression, controlling for age, sex, body mass index, and genetic ancestry. Subgroups (on the basis of 1000 Genomes reference populations) were identified: European (EUR), East Asian, American, South Asian, and African (AFR). Interaction tests were used to assess if genetically determined ancestry group modified these relationships. Results: Cluster analysis of genetic ancestry proportions identified four ancestrally defined groups: East Asia (48.3%), EUR (33.6%), admixed (11.7%; 46% EUR, 27% Americas, and 22% AFR), and AFR (6.4%). Multiple anatomical traits were associated with more severe OSA independent of ancestry, including larger cervicomental angle (standardized ß [95% confidence interval (CI)] = 0.11 [0.06-0.16]; P < 0.001), mandibular width (standardized ß [95% CI] = 0.15 [0.10-0.20]; P < 0.001), and tongue thickness (standardized ß [95% CI] = 0.06 [0.02-0.10]; P = 0.001) and smaller airway width (standardized ß [95% CI] = -0.08 [-0.15 to -0.002]; P = 0.043). Other traits, including maxillary and mandibular depth angles and lower face height, demonstrated different associations with OSA severity on the basis of ancestrally defined subgroups. Conclusions: We confirm that multiple facial and intraoral photographic measurements are associated with OSA severity independent of ancestral background, whereas others differ in their associations among the ancestrally defined subgroups.

Cross-sectional interrelationships between chronotype, obstructive sleep apnea and blood pressure in a middle-aged community cohort.

Chronotype is linked to adverse health measures and may have important associations with obstructive sleep apnea and blood pressure, but data are limited. This study aimed to determine the separate and combined associations of chronotype with obstructive sleep apnea and blood pressure in a middle-aged community population. Adults (n = 811) from the Raine Study (female = 59.2%; age mean [range] = 56.6 [42.1-76.6] years) were assessed for chronotype (Morningness-Eveningness Questionnaire), blood pressure and hypertension (doctor diagnosed or systolic blood pressure ≥ 140 mmHg and/or diastolic ≥ 90 mmHg), and obstructive sleep apnea at different in-laboratory apnea-hypopnea index thresholds (5, 10, 15 events per hr). Linear and logistic regression models examined relationships between chronotype and the presence and severity of obstructive sleep apnea, blood pressure, hypertension, and blood pressure stratified by obstructive sleep apnea severity at above-mentioned apnea-hypopnea index thresholds. Covariates included age, sex, body mass index, alcohol consumption, smoking, physical activity, sleep duration, anti-hypertensive medication, insomnia, and depressive symptoms. Most participants were categorised as morning (40%) or intermediate (43%), with 17% meeting criteria for evening chronotypes. Participants with apnea-hypopnea index ≥ 15 events per hr and morning chronotype had higher systolic (9.9 mmHg, p < 0.001) and a trend for higher diastolic blood pressure (3.4 mmHg, p = 0.07) compared with those with an evening chronotype, and higher systolic blood pressure compared with those with an intermediate chronotype (4.8 mmHg, p = 0.03). Across chronotype categories, no differences in systolic or diastolic blood pressure or odds of hypertension were found at apnea-hypopnea index thresholds of ≥ 5 or ≥ 10 events per hr. Among participants with apnea-hypopnea index ≥ 15 events per hr, systolic blood pressure is higher in those with a morning chronotype than evening and intermediate chronotypes. Assessment for morning chronotype may improve risk stratification for hypertension in patients with obstructive sleep apnea.

Influence of social jetlag on daytime sleepiness in obstructive sleep apnea.

Social jetlag is the discrepancy between socially determined sleep timing on workdays and biologically determined sleep timing on days free of social obligation. Poor circadian timing of sleep may worsen sleep quality and increase daytime sleepiness in obstructive sleep apnea (OSA). We analysed de-identified data from 2,061 participants (75.2% male, mean [SD] age 48.6 [13.4] years) who completed Sleep Apnea Global Interdisciplinary Consortium (SAGIC) research questionnaires and underwent polysomnography at 11 international sleep clinic sites. Social jetlag was calculated as the absolute difference in the midpoints of sleep between weekdays and weekends. Daytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS). Linear regression analyses were performed to estimate the association between social jetlag and daytime sleepiness, with consideration of age, sex, body mass index, ethnicity, insomnia, alcohol consumption, and habitual sleep duration as confounders. Of the participants, 61.5% had <1 h of social jetlag, 27.5% had 1 to <2 h, and 11.1% had ≥2 h. Compared to those with <1 h of social jetlag, those with ≥2 h of social jetlag had 2.07 points higher ESS (95% confidence interval [CI] 0.77-3.38, p = 0.002), and those with 1 to <2 h of social jetlag had 0.80 points higher ESS (95% CI 0.04-1.55, p = 0.04) after adjustment for potential confounding. Interaction with OSA severity was observed; social jetlag appeared to have the greatest effect on daytime sleepiness in mild OSA. As social jetlag exacerbates daytime sleepiness in OSA, improving sleep timing may be a simple but novel therapeutic target for reducing the impact of OSA.

Shift work, clinically significant sleep disorders and mental health in a representative, cross-sectional sample of young working adults.

Mental health conditions confer considerable global disease burden in young adults, who are also the highest demographic to work shifts, and of whom 20% meet criteria for a sleep disorder. We aimed to establish the relationship between the combined effect of shift work and sleep disorders, and mental health. The Raine Study is the only longitudinal, population-based birth cohort in the world with gold-standard, Level 1 measurement of sleep (polysomnography, PSG) collected in early adulthood. Participants (aged 22y) underwent in-laboratory PSG and completed detailed sleep questionnaires. Multivariable adjusted robust linear regression models were conducted to explore associations with anxiety (GAD7) and depression (PHQ9), adjusted for sex, health comorbidities, and work hours/week. Data were from 660 employed young adults (27.3% shift workers). At least one clinically significant sleep disorder was present in 18% of shift workers (day, evening and night shifts) and 21% of non-shift workers (p = 0.51); 80% were undiagnosed. Scores for anxiety and depression were not different between shift and non-shift workers (p = 0.29 and p = 0.82); but were higher in those with a sleep disorder than those without (Md(IQR) anxiety: 7.0(4.0-10.0) vs 4.0(1.0-6.0)), and depression: (9.0(5.0-13.0) vs 4.0(2.0-6.0)). Considering evening and night shift workers only (i.e. excluding day shift workers) revealed an interaction between shift work and sleep disorder status for anxiety (p = 0.021), but not depression (p = 0.96), with anxiety scores being highest in those shift workers with a sleep disorder (Md(IQR) 8.5(4.0-12.2). We have shown that clinical sleep disorders are common in young workers and are largely undiagnosed. Measures of mental health do not appear be different between shift and non-shift workers. These findings indicate that the identification and treatment of clinical sleep disorders should be prioritised for young workers as these sleep disorders, rather than shift work per se, are associated with poorer mental health. These negative mental health effects appear to be greatest in those who work evening and/or night shift and have a sleep disorder.

Telemedicine compared to standard face-to-face care for continuous positive airway pressure treatment: real-world Australian experience.

STUDY OBJECTIVES: We tested a telemedicine model of care to initiate continuous positive airway pressure (CPAP) for patients with obstructive sleep apnea (OSA) living in remote Western Australia. METHODS: A prospective study comparing telemedicine for CPAP initiation in a remote population versus standard face-to-face CPAP initiation in a metropolitan population. The primary outcome was average nightly CPAP use in the final week of a CPAP trial. RESULTS: A total of 186 participants were allocated to either telemedicine (n = 56) or standard care (n = 130). The average distance from the study center for the telemedicine group was 979 km (±792 km) compared to 19 km (±14 km) for the standard care group. The CPAP trial duration in the standard care group was less than the telemedicine group (37.6 vs 69.9 days, p < .001). CPAP adherence in the telemedicine group was not inferior to standard care (Standard 4.7 ± 0.2 h, Telemedicine 4.7 ± 0.3 h, p = 0.86). No differences were found between groups in residual apnea-hypopnea index, symptom response, sleep specific quality of life at the end of the trial, and continued CPAP use (3-6 months). Participant satisfaction was high in both groups. Total health care costs of the telemedicine model were less than the standard model of care. An estimated A$4538 per participant in travel costs was saved within the telemedicine group by reducing the need to travel to the sleep center for in-person management. CONCLUSIONS: In remote dwelling adults starting CPAP for the treatment of OSA, outcomes using telemedicine were comparable to in-person management in a metropolitan setting.

The changing profile of obstructive sleep apnea: long term trends in characteristics of patients presenting for diagnostic polysomnography.

Introduction: We aimed to analyze long-term trends in characteristics of patients undergoing diagnostic polysomnography (PSG) and subsequently diagnosed with obstructive sleep apnea (OSA) to inform delivery of sleep services. Material and Methods: We studied 24,510 consecutive patients undergoing PSG at a tertiary-care sleep service between 1989 and 2013. OSA was defined by an apnea hypopnea index (AHI)≥ 5 events/hour. Changes to hypopnea definition and flow sensing techniques in 2002 created two distinct AHI scoring periods: American Sleep Disorders Association (ASDA) 1989 - July 2002 and American Academy of Sleep Medicine (Chicago) from August 2002. Results: Over 23.5 years there was a steady increase in proportion of females (15% to 45%), small increases in average age and BMI, and a small decline in socioeconomic status in the overall group. AHI varied between scoring periods both overall [ASDA 10.8/h (3.2-29.6), Chicago 24.3/h (11.8-48.1)] and in the large subgroup (80.7%) diagnosed with OSA [ASDA 20.7/h (10.6-44.1), Chicago 27.4/h (14.8-51.5)]. OSA diagnosis rates increased in the Chicago period (ASDA 66%, Chicago 91%). Increases in AHI and proportion diagnosed appeared better explained by changes in scoring methods than key OSA risk factors. Conclusion: Temporal increases in proportion of females and decreases in socioeconomic status of people undergoing PSG may reflect greater community awareness of sleep disorders. Temporal increases in age and obesity are consistent with secular trends. Changes in scoring methods have major impacts on OSA diagnosis and judgement of disease severity, with important implications for contemporary resourcing of sleep services and interpretation of historical OSA data.

Prevalence of common sleep disorders in a middle-aged community sample.

STUDY OBJECTIVES: There is a paucity of contemporary prevalence estimates for common sleep disorders of insomnia, obstructive sleep apnea (OSA), and restless legs syndrome. We aimed to assess the prevalence of clinically significant common sleep disorders in a middle-aged community sample. METHODS: Parents of participants in the community-based Raine Study underwent assessments between 2015 and 2017, including comprehensive questionnaires, anthropometric measures, and in-laboratory polysomnography. Clinically significant sleep disorders were defined as chronic insomnia using the Pittsburgh Sleep Symptom Questionnaire-Insomnia with duration criterion ≥ 3 months; OSA as apnea-hypopnea index ≥ 5 events/h with excessive sleepiness (Epworth Sleepiness Scale ≥ 11) or apnea-hypopnea index ≥ 15 events/h (even in the absence of symptoms); restless legs syndrome when participants endorsed the International Restless Legs Syndrome Study Group diagnostic criteria (2003) with symptoms ≥ 5 times/month involving moderate-severe distress. RESULTS: At least 1 sleep-related assessment was completed by 1,005 (female = 586, 58.3%) middle-aged (45-65 years) participants, 72.5% of eligible Raine Study parents. The respective prevalences for clinically significant disease in females and males were as follows: OSA, 24.0% (95% confidence interval [CI]: 20.5-27.7) and 47.3% (95% CI: 42.2-53.4); insomnia, 15.8% (95% CI: 13.1-19.0) and 9.3% (95% CI: 6.8-12.4); restless legs syndrome, 3.7% (95% CI: 2.4-5.4) and 2.2% (95% CI: 1.1-3.9). At least 1 sleep disorder was present in 42.9% of those with complete data on all assessments (n = 895). CONCLUSIONS: Common sleep disorders are highly prevalent, to a clinically important extent, in an Australian community sample of middle-aged adults. Contemporary OSA prevalence is notably higher than previously reported and further work is needed to determine the communal impact of OSA. CITATION: McArdle N, Reynolds AC, Hillman D, et al. Prevalence of common sleep disorders in a middle-aged community sample. J Clin Sleep Med. 2022;18(6):1503-1514.

Diagnostic Performance of Machine Learning-Derived OSA Prediction Tools in Large Clinical and Community-Based Samples.

BACKGROUND: Prediction tools without patient-reported symptoms could facilitate widespread identification of OSA. RESEARCH QUESTION: What is the diagnostic performance of OSA prediction tools derived from machine learning using readily available data without patient responses to questionnaires? Also, how do they compare with STOP-BANG, an OSA prediction tool, in clinical and community-based samples? STUDY DESIGN AND METHODS: Logistic regression and machine learning techniques, including artificial neural network (ANN), random forests (RF), and kernel support vector machine, were used to determine the ability of age, sex, BMI, and race to predict OSA status. A retrospective cohort of 17,448 subjects from sleep clinics within the international Sleep Apnea Global Interdisciplinary Consortium (SAGIC) were randomly split into training (n = 10,469) and validation (n = 6,979) sets. Model comparisons were performed by using the area under the receiver-operating curve (AUC). Trained models were compared with the STOP-BANG questionnaire in two prospective testing datasets: an independent clinic-based sample from SAGIC (n = 1,613) and a community-based sample from the Sleep Heart Health Study (n = 5,599). RESULTS: The AUCs (95% CI) of the machine learning models were significantly higher than logistic regression (0.61 [0.60-0.62]) in both the training and validation datasets (ANN, 0.68 [0.66-0.69]; RF, 0.68 [0.67-0.70]; and kernel support vector machine, 0.66 [0.65-0.67]). In the SAGIC testing sample, the ANN (0.70 [0.68-0.72]) and RF (0.70 [0.68-0.73]) models had AUCs similar to those of the STOP-BANG (0.71 [0.68-0.72]). In the Sleep Heart Health Study testing sample, the ANN (0.72 [0.71-0.74]) had AUCs similar to those of STOP-BANG (0.72 [0.70-0.73]). INTERPRETATION: OSA prediction tools using machine learning without patient-reported symptoms provide better diagnostic performance than logistic regression. In clinical and community-based samples, the symptomless ANN tool has diagnostic performance similar to that of a widely used prediction tool that includes patient symptoms. Machine learning-derived algorithms may have utility for widespread identification of OSA.