Apnea-hypopnea index: time to wake up

Gut microbiota has important roles in the obstructive sleep apnea-induced inflammation and consequent neurocognitive impairment

Obstructive sleep apnea (OSA) is a state of sleep disorder, characterized by repetitive episodes of apnea and chronic intermittent hypoxia. OSA has an extremely high prevalence worldwide and represents a serious challenge to public health, yet its severity is frequently underestimated. It is now well established that neurocognitive dysfunction, manifested as deficits in attention, memory, and executive functions, is a common complication observed in patients with OSA, whereas the specific pathogenesis remains poorly understood, despite the likelihood of involvement of inflammation. Here, we provide an overview of the current state of the art, demonstrating the intimacy of OSA with inflammation and cognitive impairment. Subsequently, we present the recent findings on the investigation of gut microbiota alteration in the OSA conditions, based on both patients-based clinical studies and animal models of OSA. We present an insightful discussion on the role of changes in the abundance of specific gut microbial members, including short-chain fatty acid (SCFA)-producers and/or microbes with pathogenic potential, in the pathogenesis of inflammation and further cognitive dysfunction. The transplantation of fecal microbiota from the mouse model of OSA can elicit inflammation and neurobehavioral disorders in naïve mice, thereby validating the causal relationship to inflammation and cognitive abnormality. This work calls for greater attention on OSA and the associated inflammation, which require timely and effective therapy to protect the brain from irreversible damage. This work also suggests that modification of the gut microbiota using prebiotics, probiotics or fecal microbiota transplantation may represent a potential adjuvant therapy for OSA.

Prevalence and risks of sleep bruxism in children and adolescents presenting for orthodontic treatment

OBJECTIVES

This study determined the prevalence and risks of definite sleep bruxism (SB) among children and adolescents presenting for orthodontic treatment.

METHODS

This was a cross-sectional study of 7-16-year-old subjects pursuing orthodontic treatment for the first time. The presence or absence of SB was determined using an overnight mandibular movement monitoring inertial measurement sensor, worn by each participant for two consecutive nights. Data from the sensor were extrapolated, then processed and analyzed to automatically identify rhythmic masticatory muscle activity for SB assessment. SB risks were evaluated from previously validated questionnaires, clinical examinations, lateral cephalometric radiographs, and digital study models.

RESULTS

A total of 87 subjects with a mean age of 12.82 years ± 2.24 and body mass index of 21.45 ± 5.49 participated in the study. The prevalence of SB was 60.7%. Multiple linear regression analysis revealed that SB had statistically significant association with microarousals (events/h) (β=0.31, 95% Confidence Interval [CI] 0.25-0.36, P < .001) and maxillary 6-6 dimension (mm) (β = 0.08, 95% CI 0.02-0.13, P = .008). A second model excluding microarousals showed that SB had a statistically significant association with sleep efficiency (SE) percentage (β = -0.15, 95% CI -0.28 to -0.01, P = .026) and obstructive respiratory disturbance index (ORDI) (events/h) (β = 0.33, 95% CI 0.15-0.51, P < .001).

CONCLUSIONS AND IMPLICATIONS

In a growing orthodontic population, definite SB is very common. SB is related to microarousals, maxillary intermolar width, SE percentage, and ORDI.

Obstructive Sleep Apnea Characterization: A Multimodal Cross-Recurrence-Based Approach for Investigating Atrial Fibrillation

Obstructive sleep apnea (OSA) is believed to contribute significantly to atrial fibrillation (AF) development in certain patients. Recent studies indicate a rising risk of AF with increasing OSA severity. However, the commonly used apnea-hypopnea index in clinical practice may not adequately account for the potential cardiovascular risks associated with OSA. 1) Objective: to propose and explore a novel method for assessing OSA severity considering potential connection to cardiac arrhythmias. 2) Method: the approach utilizes cross-recurrence features to characterize OSA and AF by considering the relationships among oxygen desaturation, pulse arrival time, and heart-beat intervals. Multinomial logistic regression models were trained to predict four levels of OSA severity and four groups related to heart rhythm issues. The rank biserial correlation coefficient, rrb, was used to estimate effect size for statistical analysis. The investigation was conducted using the MESA database, which includes polysomnography data from 2055 subjects. 3) Results: a derived cross-recurrence-based index showed a significant association with a higher OSA severity (p 0.01) and the presence of AF (p 0.01). Additionally, the proposed index had a significantly larger effect, rrb, than the conventional apnea-hypopnea index in differentiating increasingly severe heart rhythm issue groups: 0.14 0.06, 0.33 0.10, and 0.41 0.07. 4) Significance: the proposed method holds relevance as a supplementary diagnostic tool for assessing the authentic state of sleep apnea in clinical practice.

Airway Collapsibility during Drug-Induced Sleep Endoscopy Relates with Clinical Features of Obstructive Sleep Apnea

INTRODUCTION

Increased pharyngeal collapsibility leads to obstructive sleep apnea (OSA). Positive airway pressure titration during drug-induced sleep endoscopy (DISE-PAP) provides objective collapsibility metrics, the pharyngeal opening pressure (PhOP), and active pharyngeal critical pressure (PcritA ). We examined the interrelationships between risk factors of OSA, airway collapsibility measures, and clinical manifestations of the disease.

METHODS

This is a cross-sectional analysis of consecutive OSA patients undergoing DISE-PAP. Nasal PAP was increased stepwise until inspiratory flow limitation was abolished, signifying PhOP. PcritA was derived from the resulting titration pressure-flow relationships. Clinical data including demographics, anthropometrics, sleep studies, and patient-symptom questionnaires were obtained from the electronic medical record. Multivariate regression was used to evaluate the relationship between risk factors, airway collapsibility, and clinical data.

RESULTS

On average, the 164 patients meeting inclusion criteria were middle-aged (54.2 ± 14.7 years), overweight/obese (BMI 29.9 ± 4.5 kg/m2 ), male (72.6%), White (79.3%) and had severe OSA (AHI 32.0 ± 20.5 events/hour). Mean PhOP was 7.5 ± 3.3 cm H2 O and mean PcritA was 0.80 ± 3.70 cm H2 O. Younger age (Standardized β = -0.191, p = 0.015) and higher BMI (Standardized β = 0.176, p = 0.028) were associated with higher PhOP, but not PcritA . PhOP and PcritA were both associated with AHI, supine AHI, and SpO2 nadir. Higher PhOP was associated with higher snoring scores (Standardized β = 0.246, p = 0.008), but not other patient-reported outcomes.

CONCLUSION

Objective assessment of passive and active airway mechanics during DISE relates with clinical risk factors for OSA. Quantitative measures of collapsibility provide accessible and meaningful data, enhancing the standard sleep surgery evaluation.

LEVEL OF EVIDENCE

4 Laryngoscope, 134:1978-1985, 2024.

Achieving Better Understanding of Obstructive Sleep Apnea Treatment Effects on Cardiovascular Disease Outcomes through Machine Learning Approaches: A Narrative Review

Obstructive sleep apnea (OSA) affects almost a billion people worldwide and is associated with a myriad of adverse health outcomes. Among the most prevalent and morbid are cardiovascular diseases (CVDs). Nonetheless, randomized controlled trials (RCTs) of OSA treatment have failed to show improvements in CVD outcomes. A major limitation in our field is the lack of precision in defining OSA and specifically subgroups with the potential to benefit from therapy. Further, this has called into question the validity of using the time-honored apnea-hypopnea index as the ultimate defining criteria for OSA. Recent applications of advanced statistical methods and machine learning have brought to light a variety of OSA endotypes and phenotypes. These methods also provide an opportunity to understand the interaction between OSA and comorbid diseases for better CVD risk stratification. Lastly, machine learning and specifically heterogeneous treatment effects modeling can help uncover subgroups with differential outcomes after treatment initiation. In an era of data sharing and big data, these techniques will be at the forefront of OSA research. Advanced data science methods, such as machine-learning analyses and artificial intelligence, will improve our ability to determine the unique influence of OSA on CVD outcomes and ultimately allow us to better determine precision medicine approaches in OSA patients for CVD risk reduction. In this narrative review, we will highlight how team science via machine learning and artificial intelligence applied to existing clinical data, polysomnography, proteomics, and imaging can do just that.

Review and perspective on sleep-disordered breathing research and translation to clinics

Sleep-disordered breathing, ranging from habitual snoring to severe obstructive sleep apnea, is a prevalent public health issue. Despite rising interest in sleep and awareness of sleep disorders, sleep research and diagnostic practices still rely on outdated metrics and laborious methods reducing the diagnostic capacity and preventing timely diagnosis and treatment. Consequently, a significant portion of individuals affected by sleep-disordered breathing remain undiagnosed or are misdiagnosed. Taking advantage of state-of-the-art scientific, technological, and computational advances could be an effective way to optimize the diagnostic and treatment pathways. We discuss state-of-the-art multidisciplinary research, review the shortcomings in the current practices of SDB diagnosis and management in adult populations, and provide possible future directions. We critically review the opportunities for modern data analysis methods and machine learning to combine multimodal information, provide a perspective on the pitfalls of big data analysis, and discuss approaches for developing analysis strategies that overcome current limitations. We argue that large-scale and multidisciplinary collaborative efforts based on clinical, scientific, and technical knowledge and rigorous clinical validation and implementation of the outcomes in practice are needed to move the research of sleep-disordered breathing forward, thus increasing the quality of diagnostics and treatment.

Ventilatory Burden as a Measure of Obstructive Sleep Apnea Severity Is Predictive of Cardiovascular and All-Cause Mortality

Rationale: The apnea-hypopnea index (AHI), used for the diagnosis of obstructive sleep apnea, captures only the frequency of respiratory events and has demonstrable limitations. Objectives: We propose a novel automated measure, termed "ventilatory burden" (VB), that represents the proportion of overnight breaths with less than 50% normalized amplitude, and we show its ability to overcome limitations of AHI. Methods: Data from two epidemiological cohorts (EPISONO [Sao Paolo Epidemiological Study] and SHHS [Sleep Heart Health Study]) and two retrospective clinical cohorts (DAYFUN; New York University Center for Brain Health) were used in this study to 1) derive the normative range of VB, 2) assess the relationship between degree of upper airway obstruction and VB, and 3) assess the relationship between VB and all-cause and cardiovascular disease (CVD) mortality with and without hypoxic burden that was derived using an in-house automated algorithm. Measurements and Main Results: The 95th percentiles of VB in asymptomatic healthy subjects across the EPISONO and the DAYFUN cohorts were 25.2% and 26.7%, respectively (median [interquartile range], VBEPISONO, 5.5 [3.5-9.7]%; VBDAYFUN, 9.8 [6.4-15.6]%). VB was associated with the degree of upper airway obstruction in a dose-response manner (VBuntreated, 31.6 [27.1]%; VBtreated, 7.2 [4.7]%; VBsuboptimally treated, 17.6 [18.7]%; VBoff-treatment, 41.6 [18.1]%) and exhibited low night-to-night variability (intraclass correlation coefficient [2,1], 0.89). VB was predictive of all-cause and CVD mortality in the SHHS cohort before and after adjusting for covariates including hypoxic burden. Although AHI was predictive of all-cause mortality, it was not associated with CVD mortality in the SHHS cohort. Conclusions: Automated VB can effectively assess obstructive sleep apnea severity, is predictive of all-cause and CVD mortality, and may be a viable alternative to the AHI.

Documentation of polysomnographic and home sleep apnea test interpretations: room for improvement?

STUDY OBJECTIVES

Obstructive sleep apnea (OSA), a heterogeneous disorder with many different presentations, is diagnosed with sleep studies. In standard clinical practice, test data are reviewed and scored, and interpretations are documented. Little standardization exists regarding what should be included in interpretations. We aimed to determine how consistently the documented interpretation included references to study quality parameters and accepted disease phenotypes.

METHODS

This study was performed at a single academic center in January 2021. From the literature, we formulated a list of test and titration quality criteria and OSA phenotypes that should be reflected in study interpretations, including total recording time, total sleep time, positionality, and supine rapid eye movement (REM) sleep during titration. We retrospectively reviewed the documentation of sleep studies to determine how often these factors were reflected in interpretation reports or clinical notes.

RESULTS

Of 134 patients in the study, 81 were diagnosed with OSA. A finding of inadequate total recording time during polysomnography or total sleep time on home sleep apnea testing was most often not documented. Positionality of OSA was not documented in 33% of applicable studies. The absence of supine REM sleep during positive airway pressure titration was not mentioned in 15% of interpretations.

CONCLUSIONS

The documentation of quality concerns and clinically important OSA phenotypes in interpretations was inconsistent. Documentation of meaningful test quality information and sleep apnea phenotypes might be improved with report standardization or by developing enhanced data displays.

CITATION

Herberts MB, Morgenthaler TI. Documentation of polysomnographic and home sleep apnea test interpretations: room for improvement? J Clin Sleep Med. 2023;19(6):1043-1049.

Serum Urotensin II Levels Are Elevated in Patients with Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) has become major public concern and is continuously investigated in new aspects of pathophysiology and management. Urotensin II (UII) is a powerful vasoconstrictor with a role in cardiovascular diseases. The main goal of this study was to evaluate serum UII levels in OSA patients and matched controls. A total of 89 OSA patients and 89 controls were consecutively enrolled. A medical history review and physical examination of the participants was conducted, with polysomnography performed in the investigated group. UII levels and other biochemical parameters were assessed according to the standard laboratory protocols. The median AHI in the OSA group was 39.0 (31.4-55.2) events/h, and they had higher levels of hsCRP when compared to control group (2.87 ± 0.71 vs. 1.52 ± 0.68 mg/L; p < 0.001). Additionally, serum UII levels were significantly higher in the OSA group (3.41 ± 1.72 vs. 2.18 ± 1.36 ng/mL; p < 0.001), while positive correlation was found between UII levels and hsCRP (r = 0.450; p < 0.001) and systolic blood pressure (SPB) (r = 0.317; p < 0.001). Finally, multiple regression analysis showed significant association of UII levels with AHI (0.017 ± 0.006, p = 0.013), SBP (0.052 ± 0.008, p < 0.001) and hsCRP (0.538 ± 0.164, p = 0.001). As UII levels were associated with blood pressure and markers of inflammation and OSA severity, it might play an important role in the complex pathophysiology of OSA and its cardiometabolic complications.

Incidence of venous thromboembolism in patients with obstructive sleep apnea: a cohort study

BACKGROUND

Previous studies suggesting that obstructive sleep apnea (OSA) may be an independent risk factor for venous thromboembolism (VTE) have been limited by reliance on administrative data and lack of adjustment for clinical variables, including obesity.

RESEARCH QUESTION

Does OSA confer an independent risk of incident VTE among a large clinical cohort referred for sleep disordered breathing evaluation?

STUDY DESIGN AND METHODS

We analyzed the clinical outcomes of 31,309 patients undergoing overnight polysomnography within a large hospital system. We evaluated the association of OSA severity with incident VTE using Cox proportional hazards modeling accounting for age, sex, body mass index (BMI), and common comorbid conditions.

RESULTS

Patients were of mean age 50.4 years and 50.1% female. There were 1,791 VTE events identified over a mean follow-up of 5.3 years. In age and sex-adjusted analyses, each 10 event/hr increase in the apnea hypopnea index (AHI) was associated with a 4% increase in incident VTE risk (hazard ratio [HR] 1.04, 95% confidence interval [CI] 1.02-1.05). After adjusting for BMI, this association disappeared (HR 1.01, 95% CI 0.99-1.03). In contrast, nocturnal hypoxemia had an independent association with incident VTE. Patients with >50% sleep time spent with oxyhemoglobin saturation <90% are at 48% increased VTE risk compared to those without nocturnal hypoxemia (HR 1.48, 95% CI 1.16-1.69).

INTERPRETATION

In this large cohort, we found that patients with more severe OSA as measured by the AHI are more likely to have incident VTE. Adjusted analyses suggest that this association is explained due to confounding by obesity. However, severe nocturnal hypoxemia may be a mechanism by which OSA heightens VTE risk.

Metrics of sleep apnea severity: beyond the apnea-hypopnea index

Obstructive sleep apnea (OSA) is thought to affect almost 1 billion people worldwide. OSA has well established cardiovascular and neurocognitive sequelae, although the optimal metric to assess its severity and/or potential response to therapy remains unclear. The apnea-hypopnea index (AHI) is well established; thus, we review its history and predictive value in various different clinical contexts. Although the AHI is often criticized for its limitations, it remains the best studied metric of OSA severity, albeit imperfect. We further review the potential value of alternative metrics including hypoxic burden, arousal intensity, odds ratio product, and cardiopulmonary coupling. We conclude with possible future directions to capture clinically meaningful OSA endophenotypes including the use of genetics, blood biomarkers, machine/deep learning and wearable technologies. Further research in OSA should be directed towards providing diagnostic and prognostic information to make the OSA diagnosis more accessible and to improving prognostic information regarding OSA consequences, in order to guide patient care and to help in the design of future clinical trials.

Overnight airway obstruction severity prediction centered on acoustic properties of smart phone: validation with esophageal pressure

OBJECTIVE

Obstructive sleep apnea is characterized by a number of airway obstructions. Esophageal pressure manometry (EPM) based estimation of consecutive peak to trough differences (ΔPes) is the gold standard method to quantify the severity of airway obstructions. However, the procedure is rarely available in sleep laboratories due to invasive nature. There is a clinical need for a simplified, scalable technology that can quantify the severity of airway obstructions. In this paper, we address this and propose a pioneering technology, centered on sleep related respiratory sound (SRS) to predict overnight ΔPes signal.

APPROACH

We recorded streams of SRS using a bedside iPhone 7 smartphone from subjects undergoing diagnostic polysomnography (PSG) studies and EPM was performed concurrently. Overnight data was divided into epochs of 10 s duration with 50% overlap. Altogether, we extracted 42 181 such epochs from 13 subjects. Acoustic features and features from the two PSG signals serve as an input to train a machine learning algorithm to achieve mapping between non-invasive features and ΔPes values. A testing dataset of 14 171 epochs from four new subjects was used for validation.

MAIN RESULTS

The SRS based model predicted the ΔPes with a median of absolute error of 6.75 cmH2O (±0.59, r = 0.83(±0.03)). When information from the PSG were combined with the SRS, the model performance became: 6.37cmH2O (±1.02, r = 0.85(±0.04)).

SIGNIFICANCE

The smart phone based SRS alone, or in combination with routinely collected PSG signals can provide a non-invasive method to predict overnight ΔPes. The method has the potential to be automated and scaled to provide a low-cost alternative to EPM.

Severe desaturations increase psychomotor vigilance task-based median reaction time and number of lapses in obstructive sleep apnoea patients

Current diagnostic parameters estimating obstructive sleep apnoea (OSA) severity have a poor connection to the psychomotor vigilance of OSA patients. Thus, we aimed to investigate how the severity of apnoeas, hypopnoeas and intermittent hypoxaemia is associated with impaired vigilance.

We retrospectively examined type I polysomnography data and corresponding psychomotor vigilance tasks (PVTs) of 743 consecutive OSA patients (apnoea–hypopnoea index (AHI) ≥5 events·h⁻¹). Conventional diagnostic parameters (e.g. AHI and oxygen desaturation index (ODI)) and novel parameters (e.g. desaturation severity and obstruction severity) incorporating duration of apnoeas and hypopnoeas as well as depth and duration of desaturations were assessed. Patients were grouped into quartiles based on PVT outcome variables. The odds of belonging to the worst-performing quartile were assessed. Analyses were performed for all PVT outcome variables using binomial logistic regression.

A relative 10% increase in median depth of desaturations elevated the odds (OR_range 1.20–1.37, p<0.05) of prolonged mean and median reaction times as well as increased lapse count. Similarly, an increase in desaturation severity (OR_range 1.26–1.52, p<0.05) associated with prolonged median reaction time. Female sex (OR_range 2.21–6.02, p<0.01), Epworth Sleepiness Scale score (OR_range 1.05–1.07, p<0.01) and older age (OR_range 1.01–1.05, p<0.05) were significant risk factors in all analyses. In contrast, increases in conventional AHI, ODI and arousal index were not associated with deteriorated PVT performance.

These results show that our novel parameters describing the severity of intermittent hypoxaemia are significantly associated with increased risk of impaired PVT performance, whereas conventional OSA severity and sleep fragmentation metrics are not. These results underline the importance of developing the assessment of OSA severity beyond the AHI.

Parameters considering characteristic properties of desaturations have a significant association with impaired vigilance, highlighting the importance of developing methods beyond the AHI for a more detailed assessment of OSA severityhttp://bit.ly/2veqxD9

Apnea-Hypopnea Event Duration Predicts Mortality in Men and Women in the Sleep Heart Health Study

RATIONALE

Obstructive sleep apnea is a risk factor for mortality, but its diagnostic metric-the apnea-hypopnea index-is a poor risk predictor. The apnea-hypopnea index does not capture the range of physiological variability within and between patients, such as degree of hypoxemia and sleep fragmentation, that reflect differences in pathophysiological contributions of airway collapsibility, chemoreceptive negative feedback loop gain, and arousal threshold.

OBJECTIVES

To test whether respiratory event duration, a heritable sleep apnea trait reflective of arousal threshold, predicts all-cause mortality.

METHODS

Mortality risk as a function of event duration was estimated by Cox proportional hazards in the Sleep Heart Health Study, a prospective community-based cohort. Gender-specific hazard ratios were also calculated.

MEASUREMENTS AND MAIN RESULTS

Among 5,712 participants, 1,290 deaths occurred over 11 years of follow-up. After adjusting for demographic factors (mean age, 63 yr; 52% female), apnea-hypopnea index (mean, 13.8; SD, 15.0), smoking, and prevalent cardiometabolic disease, individuals with the shortest-duration events had a significant hazard ratio for all-cause mortality of 1.31 (95% confidence interval, 1.11-1.54). This relationship was observed in both men and women and was strongest in those with moderate sleep apnea (hazard ratio, 1.59; 95% confidence interval, 1.11-2.28).

CONCLUSIONS

Short respiratory event duration, a marker for low arousal threshold, predicts mortality in men and women. Individuals with shorter respiratory events may be predisposed to increased ventilatory instability and/or have augmented autonomic nervous system responses that increase the likelihood of adverse health outcomes, underscoring the importance of assessing physiological variation in obstructive sleep apnea.

Intra-night variation in apnea-hypopnea index affects diagnostics and prognostics of obstructive sleep apnea

Background

Diagnostics of obstructive sleep apnea (OSA) is based on apnea-hypopnea index (AHI) determined as full-night average of occurred events. We investigate our hypothesis that intra-night variation in the frequency of obstructive events affects diagnostics and prognostics of OSA and should therefore be considered in clinical practice.

Methods

Polygraphic recordings of 1989 patients (mean follow-up 18.3 years) with suspected OSA were analyzed. Number and severity of individual obstructive events were calculated hourly for the first 6 h of sleep. OSA severity was determined based on the full-night AHI and AHI for the 2 h when the obstructive event frequency was highest (AHI_2h). Hazard ratios for all-cause, cardiovascular, and non-cardiovascular mortalities were calculated for different OSA severity categories based on the full-night AHI and AHI_2h.

Results

Frequency and duration of obstructive events varied hour-by-hour increasing towards morning. Using AHI_2h led to a statistically significant rearrangement of patients between the OSA severity categories. The use of AHI_2h for severity classification showed clearer relationship between the OSA severity and mortality than the full-night AHI.

Conclusions

Currently, the intra-night variation in frequency and severity of obstructive events is completely ignored by conventional, full-night AHI and considering this information could improve the diagnostics of OSA.

The STOP-Bang Questionnaire as a Screening Tool for Obstructive Sleep Apnea in Pregnancy

STUDY OBJECTIVES

We examined the validity of the STOP-Bang questionnaire and a modified STOP-Bang questionnaire to screen for obstructive sleep apnea (OSA) in women with obesity during the second trimester of pregnancy.

METHODS

Ninety-nine pregnant women age 18 years or older with body mass index ≥ 40 kg/m² completed the STOP-Bang questionnaire during their second trimester. The number of oxygen desaturation events (≥ 4% from baseline) was measured using overnight pulse oximetry, with OSA defined as ≥ 5 events/h. A Modified STOP-Bang score was derived by replacing the "Tired" item with Epworth Sleepiness Scale score ≥ 10. Seven candidate models were compared using information theoretic criteria: STOP-Bang, Modified STOP-Bang, and individual STOP-Bang items (Snore, Tired, Observed to stop breathing, high blood Pressure and Neck circumference). We used penalized logistic regression and negative binomial regression to derive predicted probabilities of having OSA and the predicted total event counts.

RESULTS

The predicted probability of meeting oximetry criteria for OSA increased with higher STOP-Bang scores, from < 10% for a score < 3 to 68% with a score of 6. The total number of disordered breathing events was 1.26 (95% confidence interval 1.06 to 1.50) times greater for a 1-unit increase in STOP-Bang. Of the candidate models, the best relative fit was the Snore item followed by STOP-Bang score (essentially equivalent). The predicted probability of having OSA was 5.0% for no snoring and 26.4% for snoring.

CONCLUSIONS

STOP-Bang has been shown to be a useful screening tool for OSA in pregnant women with obesity; however, the snoring question alone might be a simpler, effective predictor.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; Title: STOPBANG As A Screening Tool for Obstructive Sleep Apnoea in Pregnancy; URL: https://clinicaltrials.gov/ct2/show/NCT02542488; Identifier: NCT02542488.

PREVALENCE OF OBSTRUCTIVE SLEEP APNEA DETERMINED BY THE WATCHPAT IN NONOBESE JAPANESE PATIENTS WITH POOR GLUCOSE CONTROL AND TYPE 2 DIABETES

OBJECTIVE

Diagnosing obstructive sleep apnea (OSA) usually involves high cost, patient inconvenience, and the need for examination at a specialized center. This study employed a portable, wearable, diagnostic device (WatchPAT) to investigate the prevalence of OSA in nonobese Japanese patients with type 2 diabetes.

METHODS

Patients with type 2 diabetes were tested for OSA over one night using the WatchPAT. Logistic regression analysis was used to estimate the odds ratios (ORs) of risk factors for OSA in nonobese subjects.

RESULTS

A total of 200 eligible patients with type 2 diabetes were studied (64.5% men; aged 60.1 ± 13.6 years; body mass index [BMI], 26.3 ± 5.2 kg/m²). When OSA was defined as apnea-hypopnea index ≥5/hour, its prevalence was 80.5%. The prevalence of OSA in subjects with a BMI <20 kg/m², ≥20 and <25 kg/m², ≥25 and <30 kg/m², and ≥30 kg/m² was 38.9%, 73.5%, 86.5%, and 97.5%, respectively. The severity of OSA increased in proportion to BMI, especially when the BMI was >25 kg/m². The prevalence of OSA was also high (66.3%) in normal-weight subjects (BMI <25 kg/m²). Furthermore, the serum triglyceride level (OR, 1.01; 95% confidence interval, 1.00 to 1.02; P = .042) was significantly related to OSA.

CONCLUSION

A high prevalence of OSA was observed in this nonobese population of Japanese patients with type 2 diabetes. The triglyceride level was associated with OSA among nonobese patients.

ABBREVIATIONS

AHI = apnea-hypopnea Index; BMI = body mass index; CI = confidence interval; ESS = Epworth Sleepiness Scale; HbA1c = glycated hemoglobin; OR = odds ratio; OSA = obstructive sleep apnea; PAT = peripheral arterial tone; T2D = type 2 diabetes; TG = triglyceride.

Mortality-risk-based apnea-hypopnea index thresholds for diagnostics of obstructive sleep apnea

The severity of obstructive sleep apnea is clinically assessed mainly using the apnea-hypopnea index. Based on the apnea-hypopnea index, patients are classified into four severity groups: non-obstructive sleep apnea (apnea-hypopnea index < 5); mild (5 ≤ apnea-hypopnea index < 15); moderate (15 ≤ apnea-hypopnea index < 30); and severe obstructive sleep apnea (apnea-hypopnea index ≥ 30). However, these thresholds lack solid clinical and scientific evidence. We hypothesize that the current apnea-hypopnea index thresholds are not optimal despite their global use, and aim to assess this clinical shortcoming by optimizing the thresholds with respect to the risk of all-cause mortality. We analysed ambulatory polygraphic recordings of 1,783 patients with suspected obstructive sleep apnea (mean follow-up 18.3 years). We simulated 79,079 different threshold combinations in 100 randomized subgroups of the population and studied the relative risk of all-cause mortality corresponding to each combination and randomization. The optimal thresholds were chosen according to three criteria: (a) the hazard ratios increase linearly between severity groups towards more severe obstructive sleep apnea; (b) each group includes at least 15% of the study population; (c) group sizes decrease with increasing obstructive sleep apnea severity. The risk of all-cause mortality varied greatly across simulations; the threshold defining non-obstructive sleep apnea group having the largest effect on the hazard ratios. The apnea-hypopnea index threshold combination of 3-9-24 was optimal in most of the subgroups. In conclusion, the assessment of obstructive sleep apnea severity based on the current apnea-hypopnea index thresholds is not optimal. Our novel approach provides methods for optimizing apnea-hypopnea index-based severity classification, and the revised thresholds better differentiate patients into severity groups, ensuring that an increase in the severity corresponds to an increase in the risk of all-cause mortality.

Gender differences in severity of desaturation events following hypopnea and obstructive apnea events in adults during sleep

OBJECTIVE

Severity estimation of obstructive sleep apnea (OSA) is currently based on the apnea-hypopnea index (AHI), which ignores individual breathing cessation event characteristics. Gender differences in the relationship between the breathing cessation event duration and the related desaturation event severity could mean that the severity of OSA is different in males and females despite a similar AHI. The aim of this work was to evaluate gender differences in the severity of peripheral oxygen desaturation events following obstructive apneas or hypopneas.

APPROACH

Type I polysomnographic recordings of 220 males and 175 females were analyzed. The obstructive apnea and hypopnea events were divided into eight different durational categories from 10 s to 45 s with 5 s interval and  >45 s. The desaturation event severities following obstructive apneas or hypopneas were compared between genders within these durational categories.

MAIN RESULTS

Desaturations following obstructive apneas with a duration of 30-45 s were substantially more severe (p  <  0.05) in females compared to males. In contrast, areas of desaturations following hypopneas (with related hypopnea event durations  ⩽30 s) were smaller (p  <  0.05) in females compared to males. In general, desaturation events following obstructive apneas were more severe compared to desaturations following hypopneas and the increase in the duration of obstructive apnea and hypopnea events led to an increase in the related desaturation severity in both genders.

SIGNIFICANCE

We found gender differences in the desaturation event severities following obstructive apneas and hypopneas. The results indicate that in females longer obstructive apneas (>30 s) could be more detrimental compared to those of males. As severe health consequences are related to the desaturation severity these aspects should be considered when estimating the severity of OSA.

Severity of desaturation events differs between hypopnea and obstructive apnea events and is modulated by their duration in obstructive sleep apnea

PURPOSE

Frequency of apnea and hypopnea events is used to estimate the severity of obstructive sleep apnea (OSA). However, comprehensive information on whether apneas and hypopneas cause an equal biological effect is not available. The purpose of the present work was to evaluate the effect of the breathing cessation event type (i.e., obstructive apnea or hypopnea) and duration on the severity of related SpO₂ desaturation events.

METHODS

Type 1 polysomnographies of 395 patients (220 males and 175 females) examined for suspected OSA were analyzed. Desaturation severity related to hypopnea and obstructive apnea events were compared and comparison was controlled for gender, sleep stage, sleeping position, age, and body mass index. Hypopneas and obstructive apneas were further divided into eight different durational categories and related desaturation event characteristics were compared between the categories.

RESULTS

SpO₂ desaturation events caused by obstructive apneas were statistically significantly (p ≤ 0.004) longer, greater in area, and deeper compared to the SpO₂ desaturations caused by hypopneas. The increase in the duration of hypopnea and obstructive apnea events led to increase in the duration and area of related SpO₂ desaturations. The increase in the obstructive apnea event duration also led to increase in the depth of related desaturation event.

CONCLUSIONS

Obstructive apneas led to more severe SpO₂ desaturation compared to hypopneas. Increased event duration led to increase in the severity of the related SpO₂ desaturation. In addition to considering event duration, obstructive apneas should have more weight than hypopneas when estimating severity of OSA and associated long-term cardiovascular risk.

Can we discriminate between apnea and hypopnea using audio signals?

Obstructive sleep apnea (OSA) affects up to 14% of the population. OSA is characterized by recurrent apneas and hypopneas during sleep. The apnea-hypopnea index (AHI) is frequently used as a measure of OSA severity. In the current study, we explored the acoustic characteristics of hypopnea in order to distinguish it from apnea. We hypothesize that we can find audio-based features that can discriminate between apnea, hypopnea and normal breathing events. Whole night audio recordings were performed using a non-contact microphone on 44 subjects, simultaneously with the polysomnography study (PSG). Recordings were segmented into 2015 apnea, hypopnea, and normal breath events and were divided to design and validation groups. A classification system was built using a 3-class cubic-kernelled support vector machine (SVM) classifier. Its input is a 36-dimensional audio-based feature vector that was extracted from each event. Three-class accuracy rate using the hold-out method was 84.7%. A two-class model to separate apneic events (apneas and hypopneas) from normal breath exhibited accuracy rate of 94.7%. Here we show that it is possible to detect apneas or hypopneas from whole night audio signals. This might provide more insight about a patient's level of upper airway obstruction during sleep. This approach may be used for OSA severity screening and AHI estimation.