Predictors of Obstructive Sleep Apnea on Polysomnography after a Technically Inadequate or Normal Home Sleep Test

Multi-night measurement for diagnosis and simplified monitoring of obstructive sleep apnoea

Substantial night-to-night variability in obstructive sleep apnoea (OSA) severity has raised misdiagnosis and misdirected treatment concerns with the current prevailing single-night diagnostic approach. In-home, multi-night sleep monitoring technology may provide a feasible complimentary diagnostic pathway to improve both the speed and accuracy of OSA diagnosis and monitor treatment efficacy. This review describes the latest evidence on night-to-night variability in OSA severity, and its impact on OSA diagnostic misclassification. Emerging evidence for the potential impact of night-to-night variability in OSA severity to influence important health risk outcomes associated with OSA is considered. This review also characterises emerging diagnostic applications of wearable and non-wearable technologies that may provide an alternative, or complimentary, approach to traditional OSA diagnostic pathways. The required evidence to translate these devices into clinical care is also discussed. Appropriately sized randomised controlled trials are needed to determine the most appropriate and effective technologies for OSA diagnosis, as well as the optimal number of nights needed for accurate diagnosis and management. Potential risks versus benefits, patient perspectives, and cost-effectiveness of these novel approaches should be carefully considered in future trials.

Systematic review and meta-analysis of the prevalence of obstructive sleep apnea in Indian adults

Obstructive sleep apnea (OSA) is a common sleep disorder associated with considerable morbidity. However, there is an underrepresentation of data from India and other developing countries in global reviews of OSA prevalence. This systematic review and meta-analysis examined the prevalence of OSA in India. The MEDLINE, Embase, and Scopus databases were searched for articles that reported the prevalence of OSA in the general Indian adult population using sleep studies. Eight studies were included comprising 11,009 subjects with mean age ranging from 35.5 to 47.8 years. On the Joanna Briggs Institute (JBI) checklist for prevalence studies, the study quality ranged from 3/9 to 9/9. Meta-analysis was performed using the random-effects model. The pooled prevalence of OSA (AHI ≥5 events/hour) was 11% overall (95% CI: 7%-15%; I2 = 98.0%, p<0.001), 13% in males (95% CI: 7%-18%; I2 = 96.0%, p<0.001), and 5% in females (95% CI: 3%-7%; I2 = 73.3%, p = 0.01). The pooled prevalence of moderate-to-severe OSA (AHI ≥15 events/hour) was 5% (95% CI: 2%-8%, I2 = 95.3%; p = 0.01). Based on these findings, approximately 104 million Indians of working age suffer from OSA, of whom 47 million have moderate-to-severe OSA. This represents a major public health problem in India with important implications for the global burden of the disease.

International Consensus Statement on Obstructive Sleep Apnea

BACKGROUND

Evaluation and interpretation of the literature on obstructive sleep apnea (OSA) allows for consolidation and determination of the key factors important for clinical management of the adult OSA patient. Toward this goal, an international collaborative of multidisciplinary experts in sleep apnea evaluation and treatment have produced the International Consensus statement on Obstructive Sleep Apnea (ICS:OSA).

METHODS

Using previously defined methodology, focal topics in OSA were assigned as literature review (LR), evidence-based review (EBR), or evidence-based review with recommendations (EBR-R) formats. Each topic incorporated the available and relevant evidence which was summarized and graded on study quality. Each topic and section underwent iterative review and the ICS:OSA was created and reviewed by all authors for consensus.

RESULTS

The ICS:OSA addresses OSA syndrome definitions, pathophysiology, epidemiology, risk factors for disease, screening methods, diagnostic testing types, multiple treatment modalities, and effects of OSA treatment on multiple OSA-associated comorbidities. Specific focus on outcomes with positive airway pressure (PAP) and surgical treatments were evaluated.

CONCLUSION

This review of the literature consolidates the available knowledge and identifies the limitations of the current evidence on OSA. This effort aims to create a resource for OSA evidence-based practice and identify future research needs. Knowledge gaps and research opportunities include improving the metrics of OSA disease, determining the optimal OSA screening paradigms, developing strategies for PAP adherence and longitudinal care, enhancing selection of PAP alternatives and surgery, understanding health risk outcomes, and translating evidence into individualized approaches to therapy.

Screening the risk of obstructive sleep apnea by utilizing supervised learning techniques based on anthropometric features and snoring events

Objectives

Obstructive sleep apnea (OSA) is typically diagnosed by polysomnography (PSG). However, PSG is time-consuming and has some clinical limitations. This study thus aimed to establish machine learning models to screen for the risk of having moderate-to-severe and severe OSA based on easily acquired features.

Methods

We collected PSG data on 3529 patients from Taiwan and further derived the number of snoring events. Their baseline characteristics and anthropometric measures were obtained, and correlations among the collected variables were investigated. Next, six common supervised machine learning techniques were utilized, including random forest (RF), extreme gradient boosting (XGBoost), k-nearest neighbor (kNN), support vector machine (SVM), logistic regression (LR), and naïve Bayes (NB). First, data were independently separated into a training and validation dataset (80%) and a test dataset (20%). The approach with the highest accuracy in the training and validation phase was employed to classify the test dataset. Next, feature importance was investigated by calculating the Shapley value of every factor, which represented the impact on OSA risk screening.

Results

The RF produced the highest accuracy (of >70%) in the training and validation phase in screening for both OSA severities. Hence, we employed the RF to classify the test dataset, and results showed a 79.32% accuracy for moderate-to-severe OSA and 74.37% accuracy for severe OSA. Snoring events and the visceral fat level were the most and second most essential features of screening for OSA risk.

Conclusions

The established model can be considered for screening for the risk of having moderate-to-severe or severe OSA.

Multiple-access versus telemedicine home-based sleep apnea testing for obstructive sleep apnea (OSA) diagnosis: a cost-minimization study

PURPOSE

The aim of the present study was to compare two clinical pathways: the multiple-access outpatient pathway versus the telemedicine pathway.

METHODS

The multiple-access outpatient pathway and the telemedicine pathway were both performed with WatchPAT and implemented in a real-life healthcare scenario, adopting a cost-minimization approach. A cost-minimization analysis was undertaken to assess the economic impact of the two alternatives. The cost analyses were performed in euros for the year 2021 adopting the patient, the hospital, and the societal perspectives. Given the chosen perspectives, direct medical costs, direct nonmedical costs, and indirect costs were considered. In addition, a univariate sensitivity analysis was conducted.

RESULTS

From a hospital perspective, the telemedicine approach was estimated to cost €49 more than the multiple-access alternative. Considering the patient perspective, the telemedicine approach was estimated to cost €167 less than the multiple-access pathway. Considering the societal perspective, the telemedicine approach is estimated to cost €119 less than the multiple-access pathway.

CONCLUSION

The adoption of telemedicine home sleep apnea testing could improve the efficiency of the healthcare processes if considering the direct and indirect costs incurred by patients and not only by healthcare providers.

Association between obstructive sleep apnea and cardiovascular diseases

Obstructive sleep apnea (OSA) is a common respiratory disorder characterized by partial obstruction of upper respiratory tract and repetitive cessation of breathing during sleep. The etiology behind OSA is associated with the occurrence of intermittent hypoxemia, recurrent arousals and intrathoracic pressure swings. These contributing factors may turn on various signaling mechanisms including elevated sympathetic tone, oxidative stress, inflammation, endothelial dysfunction, cardiovascular variability, abnormal coagulation and metabolic defect ( e.g., insulin resistance, leptin resistance and altered hepatic metabolism). Given its close tie with major cardiovascular risk factors, OSA is commonly linked to the pathogenesis of a wide array of cardiovascular diseases (CVDs) including hypertension, heart failure, arrhythmias, coronary artery disease, stroke, cerebrovascular disease and pulmonary hypertension (PH). The current standard treatment for OSA using adequate nasal continuous positive airway pressure (CPAP) confers a significant reduction in cardiovascular morbidity. Nonetheless, despite the availability of effective therapy, patients with CVDs are still deemed highly vulnerable to OSA and related adverse clinical outcomes. A better understanding of the etiology of OSA along with early diagnosis should be essential for this undertreated disorder in the clinical setting.

Evaluation and Management of Adults with Obstructive Sleep Apnea Syndrome

Obstructive sleep apnea syndrome (OSAS) is a common and underdiagnosed medical condition characterized by recurrent sleep-dependent pauses and reductions in airflow. While a narrow, collapsible oropharynx plays a central role in the pathophysiology of OSAS, there are other equally important nonanatomic factors including sleep-stage dependent muscle tone, arousal threshold, and loop gain that drive obstructive apneas and hypopneas. Through mechanisms of intermittent hypoxemia, arousal-related sleep fragmentation, and intrathoracic pressure changes, OSAS impacts multiple organ systems. Risk factors for OSAS include obesity, male sex, age, specific craniofacial features, and ethnicity. The prevalence of OSAS is rising due to increasing obesity rates and improved sensitivity in the tools used for diagnosis. Validated questionnaires have an important but limited role in the identification of patients that would benefit from formal testing for OSA. While an in-laboratory polysomnography remains the gold standard for diagnosis, the widespread availability and accuracy of home sleep apnea testing modalities increase access and ease of OSAS diagnosis for many patients. In adults, the most common treatment involves the application of positive airway pressure (PAP), but compliance continues to be a challenge. Alternative treatments including mandibular advancement device, hypoglossal nerve stimulator, positional therapies, and surgical options coupled with weight loss and exercise offer possibilities of an individualized personal approach to OSAS. Treatment of symptomatic patients with OSAS has been found to be beneficial with regard to sleep-related quality of life, sleepiness, and motor vehicle accidents. The benefit of treating asymptomatic OSA patients, particularly with regard to cardiovascular outcomes, is controversial and more data are needed.

Sleep-disordered breathing in cystic fibrosis

Sleep-disordered breathing (SBD) is an under recognized comorbidity in the cystic fibrosis (CF) population across the lifespan. Nocturnal hypoxemia, obstructive sleep apnea, and nocturnal hypoventilation are respiratory abnormalities that occur commonly during sleep in patients with lung disease, and have deleterious consequences to the quality of life in people with CF. Effective screening for these abnormalities is needed to allow for timely initiation of treatment, which has been reported to be efficacious. Lack of treatment leads to worsened pulmonary, cardiovascular, and metabolic outcomes in patients. In this review, we give an overview of SBD for the CF clinician, including prevalence, treatment, and suggestions for future research. We strongly encourage the CF community to incorporate evaluation for SBD in CF clinical care so that outcomes for the subset of the CF patients with comorbid SBD improve.

Technologic advances in the assessment and management of obstructive sleep apnoea beyond the apnoea-hypopnoea index: a narrative review

Obstructive sleep apnoea (OSA) is a growing and serious worldwide health problem with significant health and socioeconomic consequences. Current diagnostic testing strategies are limited by cost, access to resources and over reliance on one measure, namely the apnoea-hypopnoea frequency per hour (AHI). Recent evidence supports moving away from the AHI as the principle measure of OSA severity towards a more personalised approach to OSA diagnosis and treatment that includes phenotypic and biological traits. Novel advances in technology include the use of signals such as heart rate variability (HRV), oximetry and peripheral arterial tonometry (PAT) as alternative or additional measures. Ubiquitous use of smartphones and developments in wearable technology have also led to increased availability of applications and devices to facilitate home screening of at-risk populations, although current evidence indicates relatively poor accuracy in comparison with the traditional gold standard polysomnography (PSG). In this review, we evaluate the current strategies for diagnosing OSA in the context of their limitations, potential physiological targets as alternatives to AHI and the role of novel technology in OSA. We also evaluate the current evidence for using newer technologies in OSA diagnosis, the physiological targets such as smartphone applications and wearable technology. Future developments in OSA diagnosis and assessment will likely focus increasingly on systemic effects of sleep disordered breathing (SDB) such as changes in nocturnal oxygen and blood pressure (BP); and may also include other factors such as circulating biomarkers. These developments will likely require a re-evaluation of the diagnostic and grading criteria for clinically significant OSA.

Night-to-night fluctuations in sleep apnea severity: diagnostic and treatment implications

STUDY OBJECTIVES

Sleep apnea is a common disorder with serious consequences; however, effective treatments are available. Successful implementation of treatment strategies relies on accurate diagnosis, which may be hampered by the presence of substantial nightly fluctuation in sleep apnea severity. We examined the amount of nightly fluctuation in the severity of sleep apnea around commonly used diagnostic and treatment cut points in individuals who underwent two nights of home sleep apnea testing (HSAT).

METHODS

A nationwide retrospective cohort study of adults thought to have sleep apnea underwent two nights of HSAT between 2005 and 2017.

RESULTS

The study included 47,423 adults (mean age, 55.2 [14.6] years; 53.7% male). The average apnea-hypopnea index (AHI) for the sample was 26.9. The average amount of nightly fluctuation in AHI was 5.5. More than a third of the sample, 16,115 individuals, had fluctuations between diagnostic cut points across the two nights of HSAT. The negative predictive value of the HSAT in the first night was 47.42%, 73.57%, and 88.65% for detecting an AHI ≥ 5, AHI ≥ 15, and AHI ≥ 30, respectively.

CONCLUSIONS

The addition of a second night of HSAT has the potential to reduce the likelihood of missed diagnoses that could result from nightly fluctuation in the severity of sleep apnea.

Diagnosis and Management of Obstructive Sleep Apnea: A Review

IMPORTANCE

Obstructive sleep apnea (OSA) affects 17% of women and 34% of men in the US and has a similar prevalence in other countries. This review provides an update on the diagnosis and treatment of OSA.

OBSERVATIONS

The most common presenting symptom of OSA is excessive sleepiness, although this symptom is reported by as few as 15% to 50% of people with OSA in the general population. OSA is associated with a 2- to 3-fold increased risk of cardiovascular and metabolic disease. In many patients, OSA can be diagnosed with home sleep apnea testing, which has a sensitivity of approximately 80%. Effective treatments include weight loss and exercise, positive airway pressure, oral appliances that hold the jaw forward during sleep, and surgical modification of the pharyngeal soft tissues or facial skeleton to enlarge the upper airway. Hypoglossal nerve stimulation is effective in select patients with a body mass index less than 32. There are currently no effective pharmacological therapies. Treatment with positive airway pressure lowers blood pressure, especially in patients with resistant hypertension; however, randomized clinical trials of OSA treatment have not demonstrated significant benefit on rates of cardiovascular or cerebrovascular events.

CONCLUSIONS AND RELEVANCE

OSA is common and the prevalence is increasing with the increased prevalence of obesity. Daytime sleepiness is among the most common symptoms, but many patients with OSA are asymptomatic. Patients with OSA who are asymptomatic, or whose symptoms are minimally bothersome and pose no apparent risk to driving safety, can be treated with behavioral measures, such as weight loss and exercise. Interventions such as positive airway pressure are recommended for those with excessive sleepiness and resistant hypertension. Managing asymptomatic OSA to reduce cardiovascular and cerebrovascular events is not currently supported by high-quality evidence.

Stimulants associated with reduced risk of hospitalization for motor vehicle accident injury in patients with obstructive sleep apnea-a nationwide cohort study

Background

The risk of injury directly related to hospitalization for motor vehicle accidents (MVAs) in the obstructive sleep apnea (OSA) patients has not been thoroughly understood. Our study aimed to examine the association between the OSA and the hospitalization for an MVA injury.

Methods

This retrospective cohort study used Taiwan’s National Health Insurance Research Database (NHIRD) between 2000 and 2015. The OSA patients aged ≥20 years by age, sex, and index-year matched by non-OSA controls were enrolled (1:3). We used the Cox proportional regression model to evaluate the association between the OSA and the hospitalization for an MVA injury.

Results

The incidence rate of hospitalization for an MVA injury was higher in the OSA cohort (N = 3025) when compared with the non-OSA controls (N = 9075), as 575.3 and 372.0 per 100,000 person-years, respectively (p < 0.001). The Kaplan-Meier analysis showed that the OSA cohort had a significantly higher incidence of hospitalization for the MVA injury (log-rank test, p < 0.001). After adjusting for the covariates, the risk of hospitalization for the MVA injury among the OSA was significantly higher (hazard ratio [HR] =2.18; 95% confidence interval [CI] = 1.79–2.64; p < 0.001). Stimulants usage was associated with a nearly 20% decrease in the risk of an overall hospitalization for an MVA injury in the OSA patients.

Conclusions

This study provides evidence that patients with OSA are at a two-fold higher risk of developing hospitalization for an MVA injury, and the usage of modafinil and methylphenidate was associated with a lower risk of an overall hospitalization for the MVA injury.

Predicting Nondiagnostic Home Sleep Apnea Tests Using Machine Learning

STUDY OBJECTIVES

Home sleep apnea testing (HSAT) is an efficient and cost-effective method of diagnosing obstructive sleep apnea (OSA). However, nondiagnostic HSAT necessitates additional tests that erode these benefits, delaying diagnoses and increasing costs. Our objective was to optimize this diagnostic pathway by using predictive modeling to identify patients who should be referred directly to polysomnography (PSG) due to their high probability of nondiagnostic HSAT.

METHODS

HSAT performed as the initial test for suspected OSA within the Veterans Administration Greater Los Angeles Healthcare System was analyzed retrospectively. Data were extracted from pre-HSAT questionnaires and the medical record. Tests were diagnostic if there was a respiratory event index (REI) ≥ 5 events/h. Tests with REI < 5 events/h or technical inadequacy-two outcomes requiring additional testing with PSG-were considered nondiagnostic. Standard logistic regression models were compared with models trained using machine learning techniques.

RESULTS

Models were trained using 80% of available data and validated on the remaining 20%. Performance was evaluated using partial area under the precision-recall curve (pAUPRC). Machine learning techniques consistently yielded higher pAUPRC than standard logistic regression, which had pAUPRC of 0.574. The random forest model outperformed all other models (pAUPRC 0.862). Preferred calibration of this model yielded the following: sensitivity 0.46, specificity 0.95, positive predictive value 0.81, negative predictive value 0.80.

CONCLUSIONS

Compared with standard logistic regression models, machine learning models improve prediction of patients requiring in-laboratory PSG. These models could be implemented into a clinical decision support tool to help clinicians select the optimal test to diagnose OSA.

Obstructive Sleep Apnea in Children and Adolescents and the Risk of Major Adverse Cardiovascular Events: A Nationwide Cohort Study in Taiwan

STUDY OBJECTIVES

This study has investigated the risk of major adverse cardiovascular events (MACEs), including acute myocardial infarction, coronary artery disease, peripheral artery disease, and acute stroke, among children and adolescents (age younger than 20 years) with obstructive sleep apnea (OSA).

METHODS

In this study, the population-based National Health Insurance Research Database of Taiwan was used to identify patients in whom OSA had been first diagnosed between 2000 and 2015. Children and adolescents with OSA (n = 6,535) were included with 1:3 ratio by age, sex, and index year of control participants without OSA (n = 19,605). The Cox proportional regression model was used to evaluate the risk of MACEs in this cohort study.

RESULTS

After a 15-year follow-up, the incidence rate of MACEs was higher in the OSA cohort when compared with the non-OSA control cohort (15.97 and 8.20 per 100,000 person-years, respectively). After adjusting for covariates, the risk of MACEs among children and adolescents with OSA was still significantly higher (hazard ratio = 2.050; 95% confidence interval = 1.312-3.107; P = .010). No MACEs were found in the children and adolescents with OSA who received continuous airway positive pressure treatment or pharyngeal surgery.

CONCLUSIONS

This study found a significantly higher risk of MACEs in children and adolescents with OSA. These findings strongly suggest that clinicians should provide careful follow-up and medical treatment for children and adolescents with OSA.

The role of home sleep testing for evaluation of patients with excessive daytime sleepiness: focus on obstructive sleep apnea and narcolepsy

Excessive daytime sleepiness (EDS) is a common complaint in the general population, which may be associated with a wide range of sleep disorders and other medical conditions. Narcolepsy is a sleep disorder characterized primarily by EDS, which involves a substantial burden of illness but is often overlooked or misdiagnosed. In addition to identifying low cerebrospinal fluid (CSF) hypocretin (orexin) levels, evaluation for narcolepsy requires in-laboratory polysomnography (PSG). Polysomnography is the gold standard for diagnosis of obstructive sleep apnea (OSA) as well as other sleep disorders. However, the use of home sleep apnea testing (HSAT) to screen for OSA in adults with EDS has increased greatly based on its lower cost, lower technical complexity, and greater convenience, versus PSG. The most commonly used, types 3 and 4, portable monitors for HSAT lack capability for electroencephalogram recording, which is necessary for the diagnosis of narcolepsy and other sleep disorders and is provided by PSG. These limitations, combined with the increased use of HSAT for evaluation of EDS, may further exacerbate the under-recognition of narcolepsy and other hypersomnias, either as primary or comorbid disorders with OSA. Adherence to expert consensus guidelines for use of HSAT is essential. Differential clinical characteristics of patients with narcolepsy and OSA may help guide correct diagnosis. Continued EDS in patients diagnosed and treated for OSA may indicate comorbid narcolepsy or another sleep disorder. Although HSAT may diagnose OSA in appropriately selected patients, it cannot rule out or diagnose narcolepsy. Therefore, at present, PSG and MSLT remain the cornerstone for narcolepsy diagnosis.

Addition of frontal EEG to adult home sleep apnea testing: does a more accurate determination of sleep time make a difference?

RATIONALE

Home sleep apnea testing (HSAT) typically does not include electroencephalogram (EEG) monitoring for sleep assessment. In patients with insomnia and low sleep efficiency, overestimation of the sleep period can result from absence of EEG, which will reduce sleep disordered breathing (SDB) indices and may lead to a false-negative result.

OBJECTIVE

To validate a single channel frontal EEG for scoring sleep versus wake against full EEG during polysomnography, and then to examine the utility of adding this single channel EEG to standard HSAT to prevent false-negative results.

METHODS

Epoch-by-epoch validation for sleep scoring of single channel EEG versus full PSG was first performed in 21 subjects. This was followed by a separate retrospective analysis of 207 consecutive HSATs in adults performed in a university-affiliated sleep center using the Somte (Compumedics) HSAT with one frontal EEG as well as chin EMG, nasal airflow, oxyhemoglobin saturation, respiratory effort, pulse rate, and body position. Each study was scored twice, with (HSAT_EEG) and without the EEG signal visible (HSAT_Polygraphy), to calculate AHI4 and RDI and the effect on OSA diagnosis and severity. Analyses were repeated in 69 patients with poor sleep suggesting insomnia plus Epworth Sleepiness Scale < 7 as well as in 38 patients ultimately shown to have sleep efficiency < 70% on HSAT with EEG.

MEASUREMENTS AND MAIN RESULTS

Single channel and full EEG during polysomnography agreed on sleep versus wake in 92-95% of all epochs. HSAT without EEG overestimated the sleep period by 20% (VST = 440 ± 76 min vs TST = 356 ± 82 min), had a false-negative rate of 8% by AHI4 criteria, and underestimated disease severity in 11% of all patients. Sub-group analysis of patients with subjective poor sleep suggesting insomnia did not change the results. Patients later shown to have low sleep efficiency had lower SDB indices and a 20.8% false negative rate of sleep apnea diagnosis.

CONCLUSIONS

Although overall false negative rates using HSAT_Polygraphy were moderate, suggesting utility for ruling out OSA, there was a specific subgroup in whom there were significant missed diagnoses. However, we were unable to identify this subgroup a priori.

When a private community neurology practice executes home sleep apnea testing: benefits identified and lessons learned in a retrospective observational study

OBJECTIVE

To investigate the feasibility and utility of a private community neurology practice-initiated home sleep apnea testing (HSAT) program.

METHODS

A private community neurology practice conducted HSAT on patients clinically identified as high risk for obstructive sleep apnea (OSA). An academic board-certified sleep specialist performed all study interpretations. The presence and severity of OSA and its association with patient demographics (eg, sex, age) and comorbid health conditions relevant to OSA were evaluated.

RESULTS

During 2011-2014, 147 consecutive patients clinically identified as highly "at risk for OSA" during their neurological visit underwent HSAT. Sixty-one percent (n=89) of patients had a "positive" study with evidence of an apnea-hypopnea index of greater than 5 events per hour. Of those, 37% (n=54) had mild OSA and 24% (n=35) had moderate-severe OSA. OSA was more common among men (54%, n=48) and in individuals with a previous documented history of depression (33%, n=48) and hypertension 44% (n=64). OSA treatment was ordered in 44% (n=39) of patients by the neurologists or by a sleep specialist. Twenty-four percent (n=21) of all patients studied were referred to a sleep specialist.

CONCLUSION

Implementation of HSAT in a (nonsleep) private community neurology practice in collaboration with an academic sleep program is recommended. Based on this observational study, community-based neurological practices and board-certified sleep specialists should consider teaming up to develop HSAT collaborative programs to open new sleep care access pathways for neurological patients often at risk for sleep apnea.

The utility of home sleep apnea tests in patients with low versus high pre-test probability for moderate to severe OSA

PURPOSE

Home sleep apnea tests (HSATs) are an alternative to attended polysomnograms (PSGs) when the pre-test probability for moderate to severe OSA is high. However, insurers often mandate use anytime OSA is suspected regardless of the pre-test probability. Our objective was to determine the ability of HSATs to rule in OSA when the pre-test probability of an apnea hypopnea index (AHI) in the moderate to severe range is low.

METHODS

Patients who underwent HSATs were characterized as low or high pre-test probability based on the presence of two symptoms of the STOP instrument plus either BMI > 35 or male gender. The odds of HSAT diagnostic for OSA dependent on pre-test probability was calculated. Stepwise selection determined predictors of non-diagnostic HSAT. As PSG is performed after HSATs that do not confirm OSA, false negative results were assessed.

RESULTS

Among 196 individuals, pre-test probability was low in 74 (38%) and high in 122 (62%). A lower percentage of individuals with a low versus high pre-test probability for moderate to severe OSA had HSAT results that confirmed OSA (61 versus 84%, p = 0.0002) resulting in an odds ratio (OR) of 0.29 for confirmatory HSAT in the low pre-test probability group (95% CI [0.146, 0.563]). Multivariate logistic regression demonstrated that age ≤ 50 (OR 3.10 [1.24-7.73]), female gender (OR 3.58[1.50-8.66]), non-enlarged neck circumference (OR 11.50 [2.50-52.93]), and the absence of loud snoring (OR 3.47 [1.30-9.25]) best predicted non-diagnostic HSAT. OSA was diagnosed by PSG in 54% of individuals with negative HSAT which was similar in both pre-test probability groups.

CONCLUSION

HSATs should be reserved for individuals with high pre-test probability for moderate to severe disease as opposed to any individual with suspected OSA.

Outcome after one year of upper airway stimulation for obstructive sleep apnea in a multicenter German post-market study

OBJECTIVE/HYPOTHESIS

Upper airway stimulation (UAS) of the hypoglossal nerve has been implemented in the routine clinical practice for patients with moderate-to-severe obstructive sleep apnea (OSA) who could not adhere to continuous positive airway pressure. This study reports objective and patient-reported outcome after 12 months of implantation.

STUDY DESIGN

Multicenter prospective single-arm study.

METHODS

Consecutive patients who received the UAS system (Inspire Medical Systems, Inc., Minneapolis, Minnesota, Maple Grove, MN, U.S.A.) were enrolled in three German centers. Key study exclusion criteria included body mass index > 35 kg/m² , apnea-hypopnea index (AHI) < 15 or > 65, or complete concentric collapse at the soft palate during sedated endoscopy. Data collection at 6- and 12-month visit include home sleep test and patient-reported outcome measures.

RESULTS

Among the total of 60 participants, the median AHI reduced from 28.6 to 9.5 from baseline to 12 months. Patient-reported outcome measured in Epworth Sleepiness Scale and Functional Outcomes of Sleep Questionnaire both improved significantly from baseline to 12 months. The average usage time was 39.1 ± 14.9 hours per week among all participants based on recordings by the implanted device. One patient requested a removal of the device for cosmetic and other personal reasons and was completed without sequelae.

CONCLUSION

This study supported that UAS is a safe and effective treatment option for patients with OSA in routine clinical practice.

LEVEL OF EVIDENCE

4. Laryngoscope, 128:509-515, 2018.

Accuracy of Automatic Polysomnography Scoring Using Frontal Electrodes

STUDY OBJECTIVES

The economic cost of performing sleep monitoring at home is a major deterrent to adding sleep data during home studies for investigation of sleep apnea and to investigating non-respiratory sleep complaints. Michele Sleep Scoring System (MSS) is a validated automatic system that utilizes central electroencephalography (EEG) derivations and requires minimal editing. We wished to determine if MSS' accuracy is maintained if frontal derivations are used instead. If confirmed, home sleep monitoring would not require home setup or lengthy manual scoring by technologists.

METHODS

One hundred two polysomnograms (PSGs) previously recorded from patients with assorted sleep disorders were scored using MSS once with central and once with frontal derivations. Total sleep time, sleep/stage R sleep onset latencies, awake time, time in different sleep stages, arousal/awakening index and apnea-hypopnea index were compared. In addition, odds ratio product (ORP), a continuous index of sleep depth/quality (Sleep 2015;38:641-54), was generated for every 30-sec epoch in each PSG and epoch-by-epoch comparison of ORP was performed.

RESULTS

Intraclass correlation coefficients (ICCs) ranged from 0.89 to 1.0 for the various sleep variables (0.96 ± 0.03). For epoch-by-epoch comparisons of ORP, ICC was > 0.85 in 96 PSGs. Lower values in the other six PSGs were related to signal artifacts in either derivation. ICC for whole-record average ORP was 0.98.

CONCLUSIONS

MSS is as accurate with frontal as with central EEG derivations. The use of frontal electrodes along with MSS should make it possible to obtain high-quality sleep data without requiring home setup or lengthy scoring time by expert technologists.