The utility of single-channel nasal airflow pressure transducer in the diagnosis of OSA at home

Obstructive sleep apnea diagnosis and beyond using portable monitors

Obstructive sleep apnea (OSA) is a chronic sleep and breathing disorder with significant health complications, including cardiovascular disease and neurocognitive impairments. To ensure timely treatment, there is a need for a portable, accurate and rapid method of diagnosing OSA. This review examines the use of various physiological signals used in the detection of respiratory events and evaluates their effectiveness in portable monitors (PM) relative to gold standard polysomnography. The primary objective is to explore the relationship between these physiological parameters and OSA, their application in calculating the apnea hypopnea index (AHI), the standard metric for OSA diagnosis, and the derivation of non-AHI metrics that offer additional diagnostic value. It is found that increasing the number of parameters in PMs does not necessarily improve OSA detection. Several factors can cause performance variations among different PMs, even if they extract similar signals. The review also highlights the potential of PMs to be used beyond OSA diagnosis. These devices possess parameters that can be utilized to obtain endotypic and other non-AHI metrics, enabling improved characterization of the disorder and personalized treatment strategies. Advancements in PM technology, coupled with thorough evaluation and validation of these devices, have the potential to revolutionize OSA diagnosis, personalized treatment, and ultimately improve health outcomes for patients with OSA. By identifying the key factors influencing performance and exploring the application of PMs beyond OSA diagnosis, this review aims to contribute to the ongoing development and utilization of portable, efficient, and effective diagnostic tools for OSA.

Longitudinal associations between sleep and BMI in a low-income, predominantly Black American sample

OBJECTIVE

Black individuals and those experiencing socioeconomic disadvantage are at increased risk for sleep problems and obesity. This study adds to the limited extant literature examining longitudinal associations between objectively measured sleep and changes in body mass index (BMI) in Black Americans.

DESIGN

We focused on individuals with at least 1 observation of sleep and BMI at 1 of 3 study time points (2013, 2016, and 2018). We modeled longitudinal trends in BMI as a function of time, average of each sleep variable across assessments, and within-person deviations in each sleep variable over time.

SETTING

Data were collected via interviewer-administered at-home surveys and actigraphy in Pittsburgh, PA.

PARTICIPANTS

Our sample comprised 1115 low-income, primarily Black adults, including 862 women and 253 men.

MEASUREMENTS

Sleep measures included actigraphy-measured total sleep time, sleep efficiency, and wakefulness after sleep onset, as well as self-reported sleep quality. We also included objectively measured BMI.

RESULTS

In models adjusted for age, gender, and other sociodemographic covariates (eg, income, marital status), there were no significant longitudinal associations between total sleep time, sleep efficiency, wakefulness after sleep onset, or subjective sleep quality and changes in BMI.

CONCLUSIONS

This study provides further evidence that, among a sample of low-income Black adults, sleep problems are not longitudinally predictive of BMI. Although ample cross-sectional evidence demonstrates that sleep problems and obesity commonly co-occur, longitudinal evidence is mixed. Better understanding the overlap of sleep and obesity over time may contribute to prevention and intervention efforts.

Portable evaluation of obstructive sleep apnea in adults: A systematic review

Obstructive sleep apnea (OSA) is a significant healthcare burden affecting approximately one billion people worldwide. The prevalence of OSA is rising with the ongoing obesity epidemic, a key risk factor for its development. While in-laboratory polysomnography (PSG) is the gold standard for diagnosing OSA, it has significant drawbacks that prevent widespread use. Portable devices with different levels of monitoring are available to allow remote assessment for OSA. To better inform clinical practice and research, this comprehensive systematic review evaluated diagnostic performances, study cost and patients' experience of different levels of portable sleep studies (type 2, 3, and 4), as well as wearable devices and non-contact systems, in adults. Despite varying study designs and devices used, portable diagnostic tests are found to be sufficient for initial screening of patients at risk of OSA. Future studies are needed to evaluate cost effectiveness with the incorporation of portable diagnostic tests into the diagnostic pathway for OSA, as well as their application in patients with chronic respiratory diseases and other comorbidities that may affect test performance.

Helping early obstructive sleep apnea diagnosis with machine learning: A systematic review (Preprint)

Background

American Academy of Sleep Medicine guidelines suggest that clinical prediction algorithms can be used to screen patients with obstructive sleep apnea (OSA) without replacing polysomnography, the gold standard.

Objective

We aimed to identify, gather, and analyze existing machine learning approaches that are being used for disease screening in adult patients with suspected OSA.

Methods

We searched the MEDLINE, Scopus, and ISI Web of Knowledge databases to evaluate the validity of different machine learning techniques, with polysomnography as the gold standard outcome measure and used the Prediction Model Risk of Bias Assessment Tool (Kleijnen Systematic Reviews Ltd) to assess risk of bias and applicability of each included study.

Results

Our search retrieved 5479 articles, of which 63 (1.15%) articles were included. We found 23 studies performing diagnostic model development alone, 26 with added internal validation, and 14 applying the clinical prediction algorithm to an independent sample (although not all reporting the most common discrimination metrics, sensitivity or specificity). Logistic regression was applied in 35 studies, linear regression in 16, support vector machine in 9, neural networks in 8, decision trees in 6, and Bayesian networks in 4. Random forest, discriminant analysis, classification and regression tree, and nomogram were each performed in 2 studies, whereas Pearson correlation, adaptive neuro-fuzzy inference system, artificial immune recognition system, genetic algorithm, supersparse linear integer models, and k-nearest neighbors algorithm were each performed in 1 study. The best area under the receiver operating curve was 0.98 (0.96-0.99) for age, waist circumference, Epworth Somnolence Scale score, and oxygen saturation as predictors in a logistic regression.

Conclusions

Although high values were obtained, they still lacked external validation results in large cohorts and a standard OSA criteria definition.

Trial Registration

PROSPERO CRD42021221339; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=221339

A generalized algorithm for the automatic diagnosis of sleep apnea from per-sample encoding of airflow and oximetry

OBJECTIVE

Sleep apnea is a common sleep breathing disorder that can significantly decrease sleep quality and have major health consequences. It is diagnosed based on the apnea hypopnea index (AHI). This study explored a novel, generalized algorithm for the automatic diagnosis of sleep apnea employing airflow (AF) and oximetry (SpO2) signals.

APPROACH

Of the 988 polysomnography records, 45 were randomly selected for developing the automatic algorithm and the remainder 943 for validating purposes. The algorithm detects apnea events by a per-sample encoding process applied to the peak excursion of AF signal. Hypopnea events were detected from the per-sample encoding of AF and SpO2 with an adjustment to time lag in SpO2. Total recording time was automatically processed and optimized for computation of total sleep time (TST). Total number of detected events and computed TST were used to estimate AHI. The estimated AHI was validated against the scored data from the Sleep Heart Health Study.

MAIN RESULTS

Intraclass correlation coefficient of 0.94 was obtained between estimated and scored AHIs. The diagnostic accuracies were 93.5%, 92.4%, and 96.6% for AHI cut-off values of ≥5, ≥15, and ≥30 respectively. The overall accuracy for the combined severity categories (normal, mild, moderate, and severe) and kappa were 83.4% and 0.77 respectively.

SIGNIFICANCE

This new automatic technique was found to be superior to the other existing methods and can be applied to any portable sleep devices especially for home sleep apnea tests.

Development and validation of a model for diagnosis of obstructive sleep apnoea in primary care

BACKGROUND AND OBJECTIVE

Use of in-laboratory polysomnography (PSG) to diagnose obstructive sleep apnoea (OSA) is cost and resource intensive. Questionnaires, physical measurements and home monitors have been studied as potential simpler alternatives. This study aimed to develop a diagnostic model for OSA for use in primary care.

METHODS

Primary care practitioners were trained to recognize symptoms of sleep apnoea and recruited patients based on the clinical need to investigate OSA. Assessment was by symptom questionnaires, anthropomorphic measurements, digital facial photography, and a single-channel nasal flow monitor (Flow Wizard©, DiagnoseIT, Sydney, Australia) worn at home for 3 nights. The in-laboratory PSG was the reference test, with OSA defined as apnoea-hypopnoea index (AHI) ≥10 events/h.

RESULTS

In the model development phase, 25 primary care practitioners studied 315 patients in whom they suspected OSA, of which 57% had AHI≥10 and 22% had AHI≥30. Published OSA questionnaires provided low to moderate prediction of OSA (area under the curve [AUC] 0.53-0.73). The nasal flow monitor alone yielded high accuracy for predicting OSA with AUC of 0.87. Sensitivity was 0.87 and specificity 0.77 at a threshold respiratory event index (REI) of 18 events/h. A model adding age, gender, symptoms and BMI to the nasal flow monitor REI only modestly improved OSA prediction (AUC 0.89), with similar AUC (0.88) confirmed in the validation population of 114 patients.

CONCLUSION

Sleep apnoea can be diagnosed in the primary care setting with a combination of clinical judgement and portable monitor test outcomes.

Examining the diagnostic validity of the Berlin Questionnaire in a low-income Black American sample

STUDY OBJECTIVES

Black individuals and individuals of low socioeconomic status are at increased risk for obstructive sleep apnea (OSA). The Berlin Questionnaire is one of the most widely used screening tools for OSA; however, there is limited research on its diagnostic accuracy in low-income, Black populations.

METHODS

This study analyzed data from an ongoing study taking place among a cohort from two predominantly Black neighborhoods in Pittsburgh, PA (96.3% Black, 79.6% female). The sample included 269 individuals without a prior diagnosis of OSA who completed the Berlin Questionnaire and also participated in a home sleep apnea test (HSAT). An apnea-hypopnea index (AHI) ≥ 15 was used to identify individuals with moderate or severe OSA.

RESULTS

19.3% of individuals met criteria for moderate to severe OSA based on HSAT, while 31.2% of participants screened as high risk for OSA based on the overall Berlin index. Using AHI>=15 as the reference standard, the Berlin Questionnaire had a sensitivity of 46.2%, specificity of 72.4%, positive predictive value (PPV) of 28.6%, and negative predictive value of 84.9% among this sample. Analyses stratified by sex suggested that the Berlin Questionnaire had better diagnostic validity in women than men.

CONCLUSIONS

The Berlin Questionnaire has lower sensitivity and PPV in our sample than those observed in general population samples. The measure performed better among women, though a higher proportion of men fell into the moderate or severe OSA range based on the HSAT. Given the significant downstream consequences of OSA, utilizing screening tools that better detect OSA in Black communities is key.

Validation of a new wearable device for type 3 sleep test without flowmeter

BACKGROUND

Ventilation monitoring during sleep is performed by sleep test instrumentation that is uncomfortable for the patients due to the presence of the flowmeter. The objective of this study was to evaluate if an innovative type 3 wearable system, the X10X and X10Y, is able to correctly detect events of apnea and hypopnea and to classify the severity of sleep apnea without the use of a flowmeter.

METHODS

40 patients with sleep disordered breathing were analyzed by continuous and simultaneous recording of X10X and X10Y and another certified type 3 system, SOMNOtouch, used for comparison. Evaluation was performed in terms of quality of respiratory signals (scores from 1, lowest, to 5, highest), duration and classification of apneas, as well as identification and duration of hypopneas.

RESULTS

580 periods were evaluated. Mean quality assigned score was 3.37±1.42 and 3.25±1.35 for X10X and X10Y and SOMNOtouch, respectively. The agreement between the two systems was evaluated with grades 4 and 5 in 383 out of 580 cases. A high correlation (r2 = 0.921; p<0.001) was found between the AHI indexes obtained from the two systems. X10X and X10Y devices were able to correctly classify 72.3% of the obstructive apneas, 81% of the central apneas, 61.3% of the hypopneas, and 64.6% of the mixed apneas when compared to SOMNOtouch device.

CONCLUSION

The X10X and X10Y devices are able to provide a correct grading of sleep respiratory disorders without the need of a nasal cannula for respiratory flow measurement and can be considered as a type 3 sleep test device for screening tests.

A novel algorithm for automatic diagnosis of sleep apnea from airflow and oximetry signals

OBJECTIVE

Sleep apnea significantly decreases the quality of life. The apnea hypopnea index (AHI) is the main indicator for sleep apnea diagnosis. This study explored a novel automatic algorithm to diagnose sleep apnea from nasal airflow (AF) and pulse oximetry (SpO₂) signals.

APPROACH

Of the 988 polysomnography (PSG) records from the sleep heart health study (SHHS), 45 were randomly selected for the development of an algorithm and the remainder for validation (n = 943). The algorithm detects apnea events by a digitization process, following the determination of the peak excursion (peak-to-trough amplitude) from AF envelope. Hypopnea events were determined from the AF envelope and oxygen desaturation with correction to time lag in SpO₂. Total sleep time (TST) was estimated from an optimized percentage of artefact-free total recording time. AHI was estimated from the number of detected events divided by the estimated TST. The estimated AHI was compared to the scored SHHS data for performance evaluation.

MAIN RESULTS

The validation showed good agreement between the estimated and scored AHI (intraclass correlation coefficient of 0.95 and mean ±95% limits of agreement of -1.6 ±12.5 events h^-1). The diagnostic accuracies were found: 90.7%, 91%, and 96.7% for AHI cut-off ≥5, ≥15, and ≥30 respectively.

SIGNIFICANCE

The new algorithm is accurate over other existing methods for the automatic diagnosis of sleep apnea. It is applicable to any portable sleep screeners especially for the home diagnosis of sleep apnea.

Prevalence and correlates of obstructive sleep apnea in urban-dwelling, low-income, predominantly African-American women

STUDY OBJECTIVES

The current study examined the prevalence and correlates of obstructive sleep apnea in a sample of low-income, predominantly African-American women using two waves of data.

METHODS

Participants were adults from two urban neighborhoods who enrolled in the PHRESH Zzz Study (N = 828; Pittsburgh Hill/Homewood Research on Neighborhoods, Sleep, and Health). A subsample who reported never receiving OSA diagnosis completed home sleep apnea testing in 2016 (n = 269, mean age 55.0 years, 79.6% female) and again in 2018 (n = 135). Correlates of OSA tested included demographic and anthropometric variables, health behavior/conditions, psychological distress and general health, smoking status, actigraphy-measured sleep, and neighborhood factors measured at baseline.

RESULTS

18.0% of all 2016 participants reported receiving physician diagnoses of OSA. Among those who completed in-home assessment, 19.3% had AHI ≥15 and 33.8% had AHI ≥5 plus one or more sleep symptoms. Estimates of the prevalence of OSA in all 2016 participants were 33.8%-45.7% based on physician diagnoses and AHI results, depending on the criteria used. Age, gender, BMI, blood pressure, habitual snoring, neighborhood walkability, actigraphy-measured sleep characteristics, and smoking were concurrently associated with OSA in 2016. Changes in AHI categories from 2016 to 2018 were documented.

CONCLUSIONS

Low-income African Americans, including women, are a high-risk group for OSA, but remain under-diagnosed and under-treated. The current findings show a high prevalence of OSA in African-American women and are among the first to demonstrate that both individual and neighborhood factors are implicated in OSA prevalence.

A machine learning-based test for adult sleep apnoea screening at home using oximetry and airflow

The most appropriate physiological signals to develop simplified as well as accurate screening tests for obstructive sleep apnoea (OSA) remain unknown. This study aimed at assessing whether joint analysis of at-home oximetry and airflow recordings by means of machine-learning algorithms leads to a significant diagnostic performance increase compared to single-channel approaches. Consecutive patients showing moderate-to-high clinical suspicion of OSA were involved. The apnoea-hypopnoea index (AHI) from unsupervised polysomnography was the gold standard. Oximetry and airflow from at-home polysomnography were parameterised by means of 38 time, frequency, and non-linear variables. Complementarity between both signals was exhaustively inspected via automated feature selection. Regression support vector machines were used to estimate the AHI from single-channel and dual-channel approaches. A total of 239 patients successfully completed at-home polysomnography. The optimum joint model reached 0.93 (95%CI 0.90–0.95) intra-class correlation coefficient between estimated and actual AHI. Overall performance of the dual-channel approach (kappa: 0.71; 4-class accuracy: 81.3%) significantly outperformed individual oximetry (kappa: 0.61; 4-class accuracy: 75.0%) and airflow (kappa: 0.42; 4-class accuracy: 61.5%). According to our findings, oximetry alone was able to reach notably high accuracy, particularly to confirm severe cases of the disease. Nevertheless, oximetry and airflow showed high complementarity leading to a remarkable performance increase compared to single-channel approaches. Consequently, their joint analysis via machine learning enables accurate abbreviated screening of OSA at home.

Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline

INTRODUCTION

This guideline establishes clinical practice recommendations for the diagnosis of obstructive sleep apnea (OSA) in adults and is intended for use in conjunction with other American Academy of Sleep Medicine (AASM) guidelines on the evaluation and treatment of sleep-disordered breathing in adults.

METHODS

The AASM commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence. The task force developed recommendations and assigned strengths based on the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use. In addition, the task force adopted foundational recommendations from prior guidelines as "good practice statements", that establish the basis for appropriate and effective diagnosis of OSA. The AASM Board of Directors approved the final recommendations.

RECOMMENDATIONS

The following recommendations are intended as a guide for clinicians diagnosing OSA in adults. Under GRADE, a STRONG recommendation is one that clinicians should follow under most circumstances. A WEAK recommendation reflects a lower degree of certainty regarding the outcome and appropriateness of the patient-care strategy for all patients. The ultimate judgment regarding propriety of any specific care must be made by the clinician in light of the individual circumstances presented by the patient, available diagnostic tools, accessible treatment options, and resources. Good Practice Statements: Diagnostic testing for OSA should be performed in conjunction with a comprehensive sleep evaluation and adequate follow-up. Polysomnography is the standard diagnostic test for the diagnosis of OSA in adult patients in whom there is a concern for OSA based on a comprehensive sleep evaluation.Recommendations: We recommend that clinical tools, questionnaires and prediction algorithms not be used to diagnose OSA in adults, in the absence of polysomnography or home sleep apnea testing. (STRONG). We recommend that polysomnography, or home sleep apnea testing with a technically adequate device, be used for the diagnosis of OSA in uncomplicated adult patients presenting with signs and symptoms that indicate an increased risk of moderate to severe OSA. (STRONG). We recommend that if a single home sleep apnea test is negative, inconclusive, or technically inadequate, polysomnography be performed for the diagnosis of OSA. (STRONG). We recommend that polysomnography, rather than home sleep apnea testing, be used for the diagnosis of OSA in patients with significant cardiorespiratory disease, potential respiratory muscle weakness due to neuromuscular condition, awake hypoventilation or suspicion of sleep related hypoventilation, chronic opioid medication use, history of stroke or severe insomnia. (STRONG). We suggest that, if clinically appropriate, a split-night diagnostic protocol, rather than a full-night diagnostic protocol for polysomnography be used for the diagnosis of OSA. (WEAK). We suggest that when the initial polysomnogram is negative and clinical suspicion for OSA remains, a second polysomnogram be considered for the diagnosis of OSA. (WEAK).

Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline

INTRODUCTION

This guideline establishes clinical practice recommendations for the diagnosis of obstructive sleep apnea (OSA) in adults and is intended for use in conjunction with other American Academy of Sleep Medicine (AASM) guidelines on the evaluation and treatment of sleep-disordered breathing in adults.

METHODS

The AASM commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence. The task force developed recommendations and assigned strengths based on the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use. In addition, the task force adopted foundational recommendations from prior guidelines as "good practice statements", that establish the basis for appropriate and effective diagnosis of OSA. The AASM Board of Directors approved the final recommendations.

RECOMMENDATIONS

The following recommendations are intended as a guide for clinicians diagnosing OSA in adults. Under GRADE, a STRONG recommendation is one that clinicians should follow under most circumstances. A WEAK recommendation reflects a lower degree of certainty regarding the outcome and appropriateness of the patient-care strategy for all patients. The ultimate judgment regarding propriety of any specific care must be made by the clinician in light of the individual circumstances presented by the patient, available diagnostic tools, accessible treatment options, and resources. Good Practice Statements: Diagnostic testing for OSA should be performed in conjunction with a comprehensive sleep evaluation and adequate follow-up. Polysomnography is the standard diagnostic test for the diagnosis of OSA in adult patients in whom there is a concern for OSA based on a comprehensive sleep evaluation.Recommendations: We recommend that clinical tools, questionnaires and prediction algorithms not be used to diagnose OSA in adults, in the absence of polysomnography or home sleep apnea testing. (STRONG). We recommend that polysomnography, or home sleep apnea testing with a technically adequate device, be used for the diagnosis of OSA in uncomplicated adult patients presenting with signs and symptoms that indicate an increased risk of moderate to severe OSA. (STRONG). We recommend that if a single home sleep apnea test is negative, inconclusive, or technically inadequate, polysomnography be performed for the diagnosis of OSA. (STRONG). We recommend that polysomnography, rather than home sleep apnea testing, be used for the diagnosis of OSA in patients with significant cardiorespiratory disease, potential respiratory muscle weakness due to neuromuscular condition, awake hypoventilation or suspicion of sleep related hypoventilation, chronic opioid medication use, history of stroke or severe insomnia. (STRONG). We suggest that, if clinically appropriate, a split-night diagnostic protocol, rather than a full-night diagnostic protocol for polysomnography be used for the diagnosis of OSA. (WEAK). We suggest that when the initial polysomnogram is negative and clinical suspicion for OSA remains, a second polysomnogram be considered for the diagnosis of OSA. (WEAK).

Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline

INTRODUCTION

This guideline establishes clinical practice recommendations for the diagnosis of obstructive sleep apnea (OSA) in adults and is intended for use in conjunction with other American Academy of Sleep Medicine (AASM) guidelines on the evaluation and treatment of sleep-disordered breathing in adults.

METHODS

The AASM commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence. The task force developed recommendations and assigned strengths based on the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use. In addition, the task force adopted foundational recommendations from prior guidelines as "good practice statements", that establish the basis for appropriate and effective diagnosis of OSA. The AASM Board of Directors approved the final recommendations.

RECOMMENDATIONS

The following recommendations are intended as a guide for clinicians diagnosing OSA in adults. Under GRADE, a STRONG recommendation is one that clinicians should follow under most circumstances. A WEAK recommendation reflects a lower degree of certainty regarding the outcome and appropriateness of the patient-care strategy for all patients. The ultimate judgment regarding propriety of any specific care must be made by the clinician in light of the individual circumstances presented by the patient, available diagnostic tools, accessible treatment options, and resources. Good Practice Statements: Diagnostic testing for OSA should be performed in conjunction with a comprehensive sleep evaluation and adequate follow-up. Polysomnography is the standard diagnostic test for the diagnosis of OSA in adult patients in whom there is a concern for OSA based on a comprehensive sleep evaluation.Recommendations: We recommend that clinical tools, questionnaires and prediction algorithms not be used to diagnose OSA in adults, in the absence of polysomnography or home sleep apnea testing. (STRONG). We recommend that polysomnography, or home sleep apnea testing with a technically adequate device, be used for the diagnosis of OSA in uncomplicated adult patients presenting with signs and symptoms that indicate an increased risk of moderate to severe OSA. (STRONG). We recommend that if a single home sleep apnea test is negative, inconclusive, or technically inadequate, polysomnography be performed for the diagnosis of OSA. (STRONG). We recommend that polysomnography, rather than home sleep apnea testing, be used for the diagnosis of OSA in patients with significant cardiorespiratory disease, potential respiratory muscle weakness due to neuromuscular condition, awake hypoventilation or suspicion of sleep related hypoventilation, chronic opioid medication use, history of stroke or severe insomnia. (STRONG). We suggest that, if clinically appropriate, a split-night diagnostic protocol, rather than a full-night diagnostic protocol for polysomnography be used for the diagnosis of OSA. (WEAK). We suggest that when the initial polysomnogram is negative and clinical suspicion for OSA remains, a second polysomnogram be considered for the diagnosis of OSA. (WEAK).

Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline

INTRODUCTION

This guideline establishes clinical practice recommendations for the diagnosis of obstructive sleep apnea (OSA) in adults and is intended for use in conjunction with other American Academy of Sleep Medicine (AASM) guidelines on the evaluation and treatment of sleep-disordered breathing in adults.

METHODS

The AASM commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence. The task force developed recommendations and assigned strengths based on the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use. In addition, the task force adopted foundational recommendations from prior guidelines as "good practice statements", that establish the basis for appropriate and effective diagnosis of OSA. The AASM Board of Directors approved the final recommendations.

RECOMMENDATIONS

The following recommendations are intended as a guide for clinicians diagnosing OSA in adults. Under GRADE, a STRONG recommendation is one that clinicians should follow under most circumstances. A WEAK recommendation reflects a lower degree of certainty regarding the outcome and appropriateness of the patient-care strategy for all patients. The ultimate judgment regarding propriety of any specific care must be made by the clinician in light of the individual circumstances presented by the patient, available diagnostic tools, accessible treatment options, and resources. Good Practice Statements: Diagnostic testing for OSA should be performed in conjunction with a comprehensive sleep evaluation and adequate follow-up. Polysomnography is the standard diagnostic test for the diagnosis of OSA in adult patients in whom there is a concern for OSA based on a comprehensive sleep evaluation.Recommendations: We recommend that clinical tools, questionnaires and prediction algorithms not be used to diagnose OSA in adults, in the absence of polysomnography or home sleep apnea testing. (STRONG). We recommend that polysomnography, or home sleep apnea testing with a technically adequate device, be used for the diagnosis of OSA in uncomplicated adult patients presenting with signs and symptoms that indicate an increased risk of moderate to severe OSA. (STRONG). We recommend that if a single home sleep apnea test is negative, inconclusive, or technically inadequate, polysomnography be performed for the diagnosis of OSA. (STRONG). We recommend that polysomnography, rather than home sleep apnea testing, be used for the diagnosis of OSA in patients with significant cardiorespiratory disease, potential respiratory muscle weakness due to neuromuscular condition, awake hypoventilation or suspicion of sleep related hypoventilation, chronic opioid medication use, history of stroke or severe insomnia. (STRONG). We suggest that, if clinically appropriate, a split-night diagnostic protocol, rather than a full-night diagnostic protocol for polysomnography be used for the diagnosis of OSA. (WEAK). We suggest that when the initial polysomnogram is negative and clinical suspicion for OSA remains, a second polysomnogram be considered for the diagnosis of OSA. (WEAK).

Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline

INTRODUCTION

This guideline establishes clinical practice recommendations for the diagnosis of obstructive sleep apnea (OSA) in adults and is intended for use in conjunction with other American Academy of Sleep Medicine (AASM) guidelines on the evaluation and treatment of sleep-disordered breathing in adults.

METHODS

The AASM commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence. The task force developed recommendations and assigned strengths based on the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use. In addition, the task force adopted foundational recommendations from prior guidelines as "good practice statements", that establish the basis for appropriate and effective diagnosis of OSA. The AASM Board of Directors approved the final recommendations.

RECOMMENDATIONS

The following recommendations are intended as a guide for clinicians diagnosing OSA in adults. Under GRADE, a STRONG recommendation is one that clinicians should follow under most circumstances. A WEAK recommendation reflects a lower degree of certainty regarding the outcome and appropriateness of the patient-care strategy for all patients. The ultimate judgment regarding propriety of any specific care must be made by the clinician in light of the individual circumstances presented by the patient, available diagnostic tools, accessible treatment options, and resources. Good Practice Statements: Diagnostic testing for OSA should be performed in conjunction with a comprehensive sleep evaluation and adequate follow-up. Polysomnography is the standard diagnostic test for the diagnosis of OSA in adult patients in whom there is a concern for OSA based on a comprehensive sleep evaluation.Recommendations: We recommend that clinical tools, questionnaires and prediction algorithms not be used to diagnose OSA in adults, in the absence of polysomnography or home sleep apnea testing. (STRONG). We recommend that polysomnography, or home sleep apnea testing with a technically adequate device, be used for the diagnosis of OSA in uncomplicated adult patients presenting with signs and symptoms that indicate an increased risk of moderate to severe OSA. (STRONG). We recommend that if a single home sleep apnea test is negative, inconclusive, or technically inadequate, polysomnography be performed for the diagnosis of OSA. (STRONG). We recommend that polysomnography, rather than home sleep apnea testing, be used for the diagnosis of OSA in patients with significant cardiorespiratory disease, potential respiratory muscle weakness due to neuromuscular condition, awake hypoventilation or suspicion of sleep related hypoventilation, chronic opioid medication use, history of stroke or severe insomnia. (STRONG). We suggest that, if clinically appropriate, a split-night diagnostic protocol, rather than a full-night diagnostic protocol for polysomnography be used for the diagnosis of OSA. (WEAK). We suggest that when the initial polysomnogram is negative and clinical suspicion for OSA remains, a second polysomnogram be considered for the diagnosis of OSA. (WEAK).

Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline

INTRODUCTION

This guideline establishes clinical practice recommendations for the diagnosis of obstructive sleep apnea (OSA) in adults and is intended for use in conjunction with other American Academy of Sleep Medicine (AASM) guidelines on the evaluation and treatment of sleep-disordered breathing in adults.

METHODS

The AASM commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence. The task force developed recommendations and assigned strengths based on the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use. In addition, the task force adopted foundational recommendations from prior guidelines as "good practice statements", that establish the basis for appropriate and effective diagnosis of OSA. The AASM Board of Directors approved the final recommendations.

RECOMMENDATIONS

The following recommendations are intended as a guide for clinicians diagnosing OSA in adults. Under GRADE, a STRONG recommendation is one that clinicians should follow under most circumstances. A WEAK recommendation reflects a lower degree of certainty regarding the outcome and appropriateness of the patient-care strategy for all patients. The ultimate judgment regarding propriety of any specific care must be made by the clinician in light of the individual circumstances presented by the patient, available diagnostic tools, accessible treatment options, and resources. Good Practice Statements: Diagnostic testing for OSA should be performed in conjunction with a comprehensive sleep evaluation and adequate follow-up. Polysomnography is the standard diagnostic test for the diagnosis of OSA in adult patients in whom there is a concern for OSA based on a comprehensive sleep evaluation.Recommendations: We recommend that clinical tools, questionnaires and prediction algorithms not be used to diagnose OSA in adults, in the absence of polysomnography or home sleep apnea testing. (STRONG). We recommend that polysomnography, or home sleep apnea testing with a technically adequate device, be used for the diagnosis of OSA in uncomplicated adult patients presenting with signs and symptoms that indicate an increased risk of moderate to severe OSA. (STRONG). We recommend that if a single home sleep apnea test is negative, inconclusive, or technically inadequate, polysomnography be performed for the diagnosis of OSA. (STRONG). We recommend that polysomnography, rather than home sleep apnea testing, be used for the diagnosis of OSA in patients with significant cardiorespiratory disease, potential respiratory muscle weakness due to neuromuscular condition, awake hypoventilation or suspicion of sleep related hypoventilation, chronic opioid medication use, history of stroke or severe insomnia. (STRONG). We suggest that, if clinically appropriate, a split-night diagnostic protocol, rather than a full-night diagnostic protocol for polysomnography be used for the diagnosis of OSA. (WEAK). We suggest that when the initial polysomnogram is negative and clinical suspicion for OSA remains, a second polysomnogram be considered for the diagnosis of OSA. (WEAK).

Clinical Practice Guideline for Diagnostic Testing for Adult Obstructive Sleep Apnea: An American Academy of Sleep Medicine Clinical Practice Guideline

INTRODUCTION

This guideline establishes clinical practice recommendations for the diagnosis of obstructive sleep apnea (OSA) in adults and is intended for use in conjunction with other American Academy of Sleep Medicine (AASM) guidelines on the evaluation and treatment of sleep-disordered breathing in adults.

METHODS

The AASM commissioned a task force of experts in sleep medicine. A systematic review was conducted to identify studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) process was used to assess the evidence. The task force developed recommendations and assigned strengths based on the quality of evidence, the balance of benefits and harms, patient values and preferences, and resource use. In addition, the task force adopted foundational recommendations from prior guidelines as "good practice statements", that establish the basis for appropriate and effective diagnosis of OSA. The AASM Board of Directors approved the final recommendations.

RECOMMENDATIONS

The following recommendations are intended as a guide for clinicians diagnosing OSA in adults. Under GRADE, a STRONG recommendation is one that clinicians should follow under most circumstances. A WEAK recommendation reflects a lower degree of certainty regarding the outcome and appropriateness of the patient-care strategy for all patients. The ultimate judgment regarding propriety of any specific care must be made by the clinician in light of the individual circumstances presented by the patient, available diagnostic tools, accessible treatment options, and resources. Good Practice Statements: Diagnostic testing for OSA should be performed in conjunction with a comprehensive sleep evaluation and adequate follow-up. Polysomnography is the standard diagnostic test for the diagnosis of OSA in adult patients in whom there is a concern for OSA based on a comprehensive sleep evaluation.Recommendations: We recommend that clinical tools, questionnaires and prediction algorithms not be used to diagnose OSA in adults, in the absence of polysomnography or home sleep apnea testing. (STRONG). We recommend that polysomnography, or home sleep apnea testing with a technically adequate device, be used for the diagnosis of OSA in uncomplicated adult patients presenting with signs and symptoms that indicate an increased risk of moderate to severe OSA. (STRONG). We recommend that if a single home sleep apnea test is negative, inconclusive, or technically inadequate, polysomnography be performed for the diagnosis of OSA. (STRONG). We recommend that polysomnography, rather than home sleep apnea testing, be used for the diagnosis of OSA in patients with significant cardiorespiratory disease, potential respiratory muscle weakness due to neuromuscular condition, awake hypoventilation or suspicion of sleep related hypoventilation, chronic opioid medication use, history of stroke or severe insomnia. (STRONG). We suggest that, if clinically appropriate, a split-night diagnostic protocol, rather than a full-night diagnostic protocol for polysomnography be used for the diagnosis of OSA. (WEAK). We suggest that when the initial polysomnogram is negative and clinical suspicion for OSA remains, a second polysomnogram be considered for the diagnosis of OSA. (WEAK).

New Rule-Based Algorithm for Real-Time Detecting Sleep Apnea and Hypopnea Events Using a Nasal Pressure Signal

We developed a rule-based algorithm for automatic real-time detection of sleep apnea and hypopnea events using a nasal pressure signal. Our basic premise was that the performance of our new algorithm using the nasal pressure signal would be comparable to that using other sensors as well as manual annotation labeled by a technician on polysomnography study. We investigated fifty patients with sleep apnea-hypopnea syndrome (age: 56.8 ± 10.5 years, apnea-hypopnea index (AHI): 36.2 ± 18.1/h) during full night PSG recordings at the sleep center. The algorithm was comprised of pre-processing with a median filter, amplitude computation and apnea-hypopnea detection parts. We evaluated the performance of the algorithm a confusion matric for each event and statistical analyses for AHI. Our evaluation achieved a good performance, with a sensitivity of 86.4 %, and a positive predictive value of 84.5 % for detection of apnea and hypopnea regardless of AHI severity. Our results indicated a high correlation with the manually labeled apnea-hypopnea events during PSG, with a correlation coefficient of r = 0.94 (p < 0.0001) and a mean difference of -2.9 ± 11.6 per hour. The proposed new algorithm could provide significant clinical and computational insights to design a PSG analysis system and a continuous positive airway pressure (CPAP) device for screening sleep quality related in patients with sleep apnea-hypopnea syndrome.

Obstructive Sleep Apnea Syndrome in Company Workers: Development of a Two-Step Screening Strategy with a New Questionnaire

STUDY OBJECTIVES

To develop and evaluate a screening questionnaire and a two-step screening strategy for obstructive sleep apnea syndrome (OSAS) in healthy workers.

METHODS

This is a cross-sectional study of 1,861 employees comprising healthy blue- and white-collar workers in two representative plants in the Netherlands from a worldwide consumer electronic company who were approached to participate. Employees were invited to complete various sleep questionnaires, and undergo separate single nasal flow recording and home polysomnography on two separate nights.

RESULTS

Of the 1,861 employees, 249 provided informed consent and all nasal flow and polysomnography data were available from 176 (70.7%). OSAS was diagnosed in 65 (36.9%). A combination of age, absence of insomnia, witnessed breathing stops, and three-way scoring of the Berlin and STOPBANG questionnaires best predicted OSAS. Factor analysis identified a six-factor structure of the resulting new questionnaire: snoring, snoring severity, tiredness, witnessed apneas, sleep quality, and daytime well-being. Subsequently, some questions were removed, and the remaining questions were used to construct a new questionnaire. A scoring algorithm, computing individual probabilities of OSAS as high, intermediate, or low risk, was developed. Subsequently, the intermediate risk group was split into low and high probability for OSAS, based on nasal flow recording. This two-step approach showed a sensitivity of 63.1%, and a specificity of 90.1%. Specificity is important for low prevalence populations.

CONCLUSION

A two-step screening strategy with a new questionnaire and subsequent nasal flow recording is a promising way to screen for OSAS in a healthy worker population.

CLINICAL TRIAL REGISTRATION

Development and validation of a screening instrument for obstructive sleep apnea syndrome in healthy workers. Netherlands Trial Register (www.trailregister.nl), number: NTR2675.

Association of Anterior Cingulate Glutathione with Sleep Apnea in Older Adults At-Risk for Dementia

STUDY OBJECTIVES

Sleep disordered breathing (SDB) is common in older adults and is strongly associated with cognitive decline, with increasing evidence suggesting that it may represent a risk factor for dementia. Given that SDB is characterized by intermittent episodes of hypoxemia during sleep, it is possible that cognitive impairment may relate to cerebral oxidative stress. This study aimed to examine the relationship between nocturnal markers of hypoxemia and proton magnetic resonance spectroscopy ((1)H-MRS) markers of oxidative stress within the anterior cingulate cortex (ACC) of the brain.

METHODS

Twenty-four older adults (mean age = 67.9 y) at-risk for dementia were recruited from our Healthy Brain Ageing Research Clinic. At-risk was defined as participants seeking help for assessment and/or intervention for cognitive decline, including those with subjective and/or objective cognitive complaints. This could occur in the context of prior depression or risk factors (e.g., vascular) for dementia. All participants underwent psychiatric, medical and neuropsychological assessment followed by overnight polysomnography. In addition, participants underwent (1)H-MRS to derive levels of ACC metabolite glutathione (GSH) reported as a ratio to creatine (GSH/Cr).

RESULTS

Increased levels of GSH/Cr were associated with lower oxygen desaturation (r = -0.54, P = 0.007) and more severe apnea-hypopnea index scores during rapid eye movement sleep (r = 0.42, P = 0.050). In addition, ACC GSH/Cr correlated with poorer executive functioning (i.e., response inhibition: r = -0.49, P = 0.015; set shifting: r = -0.43, P = 0.037).

CONCLUSIONS

Markers of nocturnal hypoxemia and SDB are associated with cerebral oxidative stress in older people at-risk for dementia, suggesting a potential mechanism by which SDB may contribute to brain degeneration, cognitive decline, and dementia. Further work focused on utilizing this biomarker for the early identification and treatment of this possible modifiable risk factor in older persons is now warranted.

Metabolic and hormonal effects of 'catch-up' sleep in men with chronic, repetitive, lifestyle-driven sleep restriction

OBJECTIVE

Acutely restricting sleep worsens insulin sensitivity in healthy individuals whose usual sleep is normal in duration and pattern. The effect of recovery or weekend 'catch-up' sleep on insulin sensitivity and metabolically active hormones in individuals with chronic sleep restriction who regularly 'catch-up' on sleep at weekends is as yet unstudied.

DESIGN

19 men (mean ± SEM age 28·6 ± 2·0 years, BMI 26·0 ± 0·8 kg/m(2) ) with at least 6 months' history (5·1 ± 0·9 years) of lifestyle-driven, restricted sleep during the working week (373 ± 6·6 min/night) with regular weekend 'catch-up' sleep (weekend sleep extension 37·4 ± 2·3%) completed an in-laboratory, randomized, crossover study comprising two of three conditions, stratified by age. Conditions were 3 weekend nights of 10 hours, 6 hours or 10 hours time-in-bed with slow wave sleep (SWS) suppression using targeted acoustic stimuli.

MEASUREMENTS

Insulin sensitivity was measured in the morning following the 3rd intervention night by minimal modelling of 19 samples collected during a 2-h oral glucose tolerance test. Glucose, insulin, c-peptide, leptin, peptide YY (PYY), ghrelin, cortisol, testosterone and luteinizing hormone (LH) were measured from daily fasting blood samples; HOMA-IR, HOMA-β and QUICKI were calculated.

RESULTS

Insulin sensitivity was higher following three nights of sleep extension compared to sustained sleep restriction. Fasting insulin, c-peptide, HOMA-IR, HOMA-β, leptin and PYY decreased with 'catch-up' sleep, QUICKI and testosterone increased, while morning cortisol and LH did not change. Targeted acoustic stimuli reduced SWS by 23%, but did not alter insulin sensitivity.

CONCLUSIONS

Three nights of 'catch-up' sleep improved insulin sensitivity in men with chronic, repetitive sleep restriction. Methods to improve metabolic health by optimizing sleep are plausible.

Efficacy of home single-channel nasal pressure for recommending continuous positive airway pressure treatment in sleep apnea

INTRODUCTION

Unlike other prevalent diseases, obstructive sleep apnea (OSA) has no simple tool for diagnosis and therapeutic decision-making in primary healthcare. Home single-channel nasal pressure (HNP) may be an alternative to polysomnography for diagnosis but its use in therapeutic decisions has yet to be explored.

OBJECTIVES

To ascertain whether an automatically scored HNP apnea-hypopnea index (AHI), used alone to recommend continuous positive airway pressure (CPAP) treatment, agrees with decisions made by a specialist using polysomnography and several clinical variables.

METHODS

Patients referred by primary care physicians for OSA suspicion underwent randomized polysomnography and HNP. We analyzed the total sample and both more and less symptomatic subgroups for Bland and Altman plots to explore AHI agreement; receiver operating characteristic curves to establish area under the curve (AUC) measurements for CPAP recommendation; and therapeutic decision efficacy for several HNP AHI cutoff points.

RESULTS

Of the 787 randomized patients, 35 (4%) were lost, 378 (48%) formed the more symptomatic and 374 (48%) the less symptomatic subgroups. AHI bias and agreement limits were 5.8 ± 39.6 for the total sample, 5.3 ± 38.7 for the more symptomatic, and 6 ± 40.2 for the less symptomatic subgroups. The AUC were 0.826 for the total sample, 0.903 for the more symptomatic, and 0.772 for the less symptomatic subgroups. In the more symptomatic subgroup, 70% of patients could be correctly treated with CPAP.

CONCLUSION

Automatic HNP scoring can correctly recommend CPAP treatment in most of more symptomatic patients with OSA suspicion. Our results suggest that this device may be an interesting tool in initial OSA management for primary care physicians, although future studies in a primary care setting are necessary.

CLINICAL TRIALS INFORMATION

Clinicaltrial.gov identifier: NCT01347398.

Effectiveness of home single-channel nasal pressure for sleep apnea diagnosis

INTRODUCTION

Home single-channel nasal pressure (HNP) may be an alternative to polysomnography (PSG) for obstructive sleep apnea (OSA) diagnosis, but no cost studies have yet been carried out. Automatic scoring is simpler but generally less effective than manual scoring.

OBJECTIVES

To determine the diagnostic efficacy and cost of both scorings (automatic and manual) compared with PSG, taking as a polysomnographic OSA diagnosis several apnea-hypopnea index (AHI) cutoff points.

METHODS

We included suspected OSA patients in a multicenter study. They were randomized to home and hospital protocols. We constructed receiver operating characteristic (ROC) curves for both scorings. Diagnostic efficacy was explored for several HNP AHI cutoff points, and costs were calculated for equally effective alternatives.

RESULTS

Of 787 randomized patients, 752 underwent HNP. Manual scoring produced better ROC curves than automatic for AHI < 15; similar curves were obtained for AHI ≥ 15. A valid HNP with manual scoring would determine the presence of OSA (or otherwise) in 90% of patients with a polysomnographic AHI ≥ 5 cutoff point, in 74% of patients with a polysomnographic AHI ≥ 10 cutoff point, and in 61% of patients with a polysomnographic AHI ≥ 15 cutoff point. In the same way, a valid HNP with automatic scoring would determine the presence of OSA (or otherwise) in 73% of patients with a polysomnographic AHI ≥ 5 cutoff point, in 64% of patients with a polysomnographic AHI ≥ 10 cutoff point, and in 57% of patients with a polysomnographic AHI ≥ 15 cutoff point. The costs of either HNP approaches were 40% to 70% lower than those of PSG at the same level of diagnostic efficacy. Manual HNP had the lowest cost for low polysomnographic AHI levels (≥ 5 and ≥ 10), and manual and automatic scorings had similar costs for higher polysomnographic cutoff points (AHI ≥ 15) of diagnosis.

CONCLUSION

Home single-channel nasal pressure (HNP) is a cheaper alternative than polysomnography for obstructive sleep apnea diagnosis. HNP with manual scoring seems to have better diagnostic accuracy and a lower cost than automatic scoring for patients with low apnea-hypopnea index (AHI) levels, although automatic scoring has similar diagnostic accuracy and cost as manual scoring for intermediate and high AHI levels. Therefore, automatic scoring can be appropriately used, although diagnostic efficacy could improve if we carried out manual scoring on patients with AHI < 15.

CLINICAL TRIALS INFORMATION

Clinicaltrials.gov identifier: NCT01347398.

Sleep disordered breathing and polysomnography in Australia: trends in provision from 2005 to 2012 and the impact of home-based diagnosis

STUDY OBJECTIVES

To describe the growth of publicly funded polysomnography (PSG) in Australia since 2004 and to compare this with earlier growth.

METHODS

Longitudinal census-level data stratified by jurisdiction were retrieved from the Medicare Australia online database.

RESULTS

There has been a near doubling in provision of PSG since the introduction of publicly funded in-home PSG under the Australian national Medicare program available to all Australian citizens in 2008. Overall annual PSG rates have risen from 339 in 2005 to 608 in 2012 per 100,000. This growth has exceeded that of comparable diagnostic procedures and all Medicare services overall. Queensland remains the leading jurisdiction per 100,000 Medicare enrollees for accessing Medicare-funded PSG.

CONCLUSION

The continued growth in publicly funded PSG provision in Australia is unlikely to abate. The disparity in Australia between the estimated prevalence of sleep disorders, particularly obstructive sleep apnea, and the number of people having PSGs would suggest there remain a large number of undiagnosed cases. Support for the development of appropriate diagnostic and screening algorithms will be key in ensuring sustainable, effective, efficient, and accessible PSG services.

A comparison of screening methods for sleep disorders in Australian community pharmacies: a randomized controlled trial

BACKGROUND

Community pharmacies may potentially assist in screening for chronic conditions such as sleep disorders, which remain both under-diagnosed and untreated. We aimed to compare a subjective risk-assessment-only questionnaire (RAO) for common sleep disorder screening against the same risk-assessment questionnaire plus a nasal flow monitor as an objective marker of possible underlying obstructive sleep apnea (OSA) (RA+) in a community pharmacy setting. The primary outcome was the number of participants identified in RAO or RA+ group who were likely to have and consequently be diagnosed with OSA. Further outcomes included the number of participants identified as being at risk for, referred for, taking-up referral for, and then diagnosed with OSA, insomnia, and/or restless legs syndrome (RLS) in either group.

METHODS

In a cluster-randomized trial, participants were recruited through 23 community pharmacies. Using validated instruments, 325 (RAO = 152, RA+ = 173) participants were screened for OSA, insomnia, and RLS.

FINDINGS

218 (67%) participants were at risk of OSA, insomnia or RLS and these participants were referred to their primary physician. The proportion of screened participants identified as being at risk of OSA was significantly higher in the RA+ group (36% in RAO vs. 66% in RA+, OR 3.4, 95% CI (1.8-6.5), p<0.001). A 12-month follow-up was completed in 125 RAO and 155 RA+ participants. Actual referral uptake was 34% RAO, 26% RA+, OR 4.4, 95% CI (1.4-19.2), p = 0.31. The OSA diagnosis rate was higher in the RA+ arm (p = 0.01). To yield a single additional confirmed OSA diagnosis, 16 people would need to be screened using the RA+ protocol.

CONCLUSIONS

These results demonstrate that utilising either screening method is feasible in identifying individuals in the community pharmacy setting who are likely to have OSA, insomnia and/or RLS. Secondly, adding an objective marker of OSA to a questionnaire-based prediction tool resulted in more confirmed OSA diagnoses.

TRIAL REGISTRATION

ACTR.org.au ACTRN12608000628347.

The role of sleepiness, sleep disorders, and the work environment on heavy-vehicle crashes in 2 Australian states

Heavy-vehicle driving involves a challenging work environment and a high crash rate. We investigated the associations of sleepiness, sleep disorders, and work environment (including truck characteristics) with the risk of crashing between 2008 and 2011 in the Australian states of New South Wales and Western Australia. We conducted a case-control study of 530 heavy-vehicle drivers who had recently crashed and 517 heavy-vehicle drivers who had not. Drivers' crash histories, truck details, driving schedules, payment rates, sleep patterns, and measures of health were collected. Subjects wore a nasal flow monitor for 1 night to assess for obstructive sleep apnea. Driving schedules that included the period between midnight and 5:59 am were associated with increased likelihood of crashing (odds ratio = 3.42, 95% confidence interval: 2.04, 5.74), as were having an empty load (odds ratio = 2.61, 95% confidence interval: 1.72, 3.97) and being a less experienced driver (odds ratio = 3.25, 95% confidence interval: 2.37, 4.46). Not taking regular breaks and the lack of vehicle safety devices were also associated with increased crash risk. Despite the high prevalence of obstructive sleep apnea, it was not associated with the risk of a heavy-vehicle nonfatal, nonsevere crash. Scheduling of driving to avoid midnight-to-dawn driving and the use of more frequent rest breaks are likely to reduce the risk of heavy-vehicle nonfatal, nonsevere crashes by 2-3 times.

Screening for sleep apnoea in mild cognitive impairment: the utility of the multivariable apnoea prediction index

Purpose. Mild cognitive impairment (MCI) is considered an “at risk” state for dementia and efforts are needed to target modifiable risk factors, of which Obstructive sleep apnoea (OSA) is one. This study aims to evaluate the predictive utility of the multivariate apnoea prediction index (MAPI), a patient self-report survey, to assess OSA in MCI. Methods. Thirty-seven participants with MCI and 37 age-matched controls completed the MAPI and underwent polysomnography (PSG). Correlations were used to compare the MAPI and PSG measures including oxygen desaturation index and apnoea-hypopnoea index (AHI). Receiver-operating characteristics (ROC) curve analyses were performed using various cut-off scores for apnoea severity. Results. In controls, there was a significant moderate correlation between higher MAPI scores and more severe apnoea (AHI: r = 0.47, P = 0.017). However, this relationship was not significant in the MCI sample. ROC curve analysis indicated much lower area under the curve (AUC) in the MCI sample compared to the controls across all AHI severity cut-off scores. Conclusions. In older people, the MAPI moderately correlates with AHI severity but only in those who are cognitively intact. Development of further screening tools is required in order to accurately screen for OSA in MCI.

Evaluation of a single-channel nasal pressure device to assess obstructive sleep apnea risk in laboratory and home environments

STUDY OBJECTIVES

To evaluate the sensitivity and specificity of a portable single-channel (intra-nasal pressure) sleep apnea device (ApneaLink) in both the laboratory and at home for assessment of sleep apnea risk in comparison with standard polysomnography (PSG).

METHODS

Fifty-five participants underwent simultaneous recordings of standard PSG and ApneaLink in the laboratory. Of these, 38 participants also used the ApneaLink device in their own homes for one night. PSG respiratory events were scored using standard criteria. Intra-nasal pressure signals were analyzed using the ApneaLink automated computerized algorithm provided to yield estimates of airflow for detection of apneas and hypopneas. Apnea-hypopnea indices (AHI) were compared.

RESULTS

There was high sensitivity and specificity for the ApneaLink AHI when compared to simultaneous PSG at comparable AHI levels (AHI ≥ 15 events/h; sensitivity 100%, specificity 92%; positive and negative predictive values 70% and 100%, respectively). Home-measured ApneaLink AHI sensitivity and specificity were also reliable when compared with PSG (AHI ≥ 5, 81% and 77%, respectively; AHI ≥ 15, 67% and 91%), and improved slightly when two nights' data were used (AHI ≥ 5, 88% and 85%; AHI ≥ 15, 67% and 93%).

CONCLUSIONS

The ApneaLink demonstrated good sensitivity and specificity in quantifying AHI when compared to PSG in a population with and without confirmed OSA. This simple, easy-to-use device may be useful in de novo large-scale occupational or underserved community OSA diagnostic programs to identify those with unambiguous disease who need immediate treatment or indicate those who may be at increased risk of OSA.

The utility of a portable recording device for screening of obstructive sleep apnea in obese adolescents

STUDY OBJECTIVES

The ApneaLink Plus is a portable recording device that measures air flow, respiratory effort, heart rate, and pulse oximetry. In the current study, we asked whether this device could be used to screen for obstructive sleep apnea in the pediatric population.

METHODS

Sleep-laboratory polysomnography (PSG) was performed simultaneously with measurements using the portable device on obese pediatric patients referred for snoring. The obstructive apnea hypopnea index (OAHI) was calculated automatically by the device (autoscore) and manually by the investigators. Sensitivity, specificity, correlation, and receiver operating curves (ROC) were used to compare the portable device to PSG.

RESULTS

Twenty-five subjects (60% male, mean age 13.6 ± 3.0 years, OAHI on PSG 11.8 ± 27.1) were studied. We identified a significant correlation between the OAHI of the ApneaLink autoscore and PSG (Spearman Rho = 0.886 [p < 0.001]). Using the PSG results as standard, ROC curves comparing the ApneaLink OAHI with the PSG OAHI demonstrated high congruence. The autoscore agreement was very good at PSG OAHI > 1.5 (area under the receiver operating curve [AUC] 0.965, OAHI > 5 [AUC 0.937], and OAHI > 10 [AUC 1.00]). The agreement of the manual score and autoscore were essentially equivalent. The device's autoscore demonstrated high sensitivity at all cutoffs examined (100% at OAHI > 1.5, 85.7% at OAHI > 5, and 100% at OAHI > 10). The specificity increased with increasing cutoffs (46.2% at OAHI > 1.5, 83.3% at OAHI > 5, and 90.0% at OAHI > 10).

CONCLUSION

he ApneaLink Plus is a sensitive screening tool for evaluation of suspected OSAS in obese pediatric patients aged 9-18 years. The specificity improves with increasing OAHI cutoffs. The device detects OSAS when tested in a sleep laboratory on obese adolescents referred for symptoms of sleep related breathing disorder.

Assessing sleepiness and sleep disorders in Australian long-distance commercial vehicle drivers: self-report versus an "at home" monitoring device

STUDY OBJECTIVES

As obstructive sleep apnea (OSA) is associated with a higher risk of motor vehicle crashes, there is increasing regulatory interest in the identification of commercial motor vehicle (CMV) drivers with this condition. This study aimed to determine the relationship between subjective versus objective assessment of OSA in CMV drivers.

DESIGN

Cross-sectional survey.

SETTINGS

Heavy vehicle truck stops located across the road network of 2 large Australian states.

PARTICIPANTS

A random sample of long distance commercial vehicle drivers (n = 517).

INTERVENTIONS

None.

MEASUREMENTS AND RESULTS

Drivers were interviewed regarding their driving experience, personal health, shift schedules, payments, and various questions on sleep and tiredness in order to describe their sleep health across a range of variables. In addition, home recordings using a flow monitor were used during one night of sleep. Only 4.4% of drivers reported a previous diagnosis of sleep apnea, while our at home diagnostic test found a further 41% of long-distance heavy vehicle drivers likely to have sleep apnea. The multivariable apnea prediction index, based on self-report measures, showed poor agreement with the home-monitor detected sleep apnea (AUC 0.58, 95%CI = 0.49-0.62), and only 12% of drivers reported daytime sleepiness (Epworth Sleepiness Scale score > 10). Thirty-six percent of drivers were overweight and a further 50% obese; 49% of drivers were cigarette smokers.

CONCLUSIONS

Sleep apnea remains a significant and unrecognized problem in CMV drivers, who we found to have multiple health risks. Objective testing for this sleep disorder needs to be considered, as symptom reports and self-identification appear insufficient to accurately identify those at risk.

The heavy vehicle study: a case-control study investigating risk factors for crash in long distance heavy vehicle drivers in Australia

BACKGROUND

Heavy vehicle transportation continues to grow internationally; yet crash rates are high, and the risk of injury and death extends to all road users. The work environment for the heavy vehicle driver poses many challenges; conditions such as scheduling and payment are proposed risk factors for crash, yet the precise measure of these needs quantifying. Other risk factors such as sleep disorders including obstructive sleep apnoea have been shown to increase crash risk in motor vehicle drivers however the risk of heavy vehicle crash from this and related health conditions needs detailed investigation.

METHODS AND DESIGN

The proposed case control study will recruit 1034 long distance heavy vehicle drivers: 517 who have crashed and 517 who have not. All participants will be interviewed at length, regarding their driving and crash history, typical workloads, scheduling and payment, trip history over several days, sleep patterns, health, and substance use. All participants will have administered a nasal flow monitor for the detection of obstructive sleep apnoea.

DISCUSSION

Significant attention has been paid to the enforcement of legislation aiming to deter problems such as excess loading, speeding and substance use; however, there is inconclusive evidence as to the direction and strength of associations of many other postulated risk factors for heavy vehicle crashes. The influence of factors such as remuneration and scheduling on crash risk is unclear; so too the association between sleep apnoea and the risk of heavy vehicle driver crash. Contributory factors such as sleep quality and quantity, body mass and health status will be investigated. Quantifying the measure of effect of these factors on the heavy vehicle driver will inform policy development that aims toward safer driving practices and reduction in heavy vehicle crash; protecting the lives of many on the road network.