The Frequency and Energy of Snoring Sounds Are Associated with Common Carotid Artery Intima-Media Thickness in Obstructive Sleep Apnea Patients

Study on the flow mechanism and frequency characteristics of rales in lower respiratory tract

The frequency characteristics of lung sounds have great significance for noninvasive diagnosis of respiratory diseases. The rales in the lower respiratory tract region that can provide rich information about symptoms of respiratory diseases are not clear. In this paper, a three-dimensional idealized bifurcated lower respiratory tract geometric model, which contains 3rd to 13th generation (G3-G13) bronchi is constructed, where Re ∼ 10 1 - 10 3 , and then the large eddy simulation and volume of fluid are used to study the fluid flow characteristics. Ffowcs Williams and Hawkings model are subsequently used to study the frequency characteristics of rale of different generations of bronchi. The results showed that bronchial blockage and sputum movement will enhance the turbulence intensity and vortex shedding intensity of flow. The dominant frequency and highest value of sound pressure level (SPL) of rhonchi/moist crackles decrease with the increase of bronchial generation. The change rates of dominant frequency of rhonchi / moist crackles in adjacent generations were 5.0 ± 0.1 ~ 9.1 ± 0.2% and 3.1 ± 0.1 ~ 11.9 ± 0.3%, respectively, which is concentrated in 290 ~ 420 Hz and 200 ~ 300 Hz, respectively. The change rates of SPL of rhonchi/moist crackles were 8.8 ± 0.1 ~ 15.7 ± 0.1% and 7.1 ± 0.1 ~ 19.5 ± 0.2%, respectively, which is concentrated in 28 ~ 50 dB and 16 ~ 32 dB, respectively. In the same generation of bronchus (e.g., G8, G9) with the same degree of initial blockage, the dominant frequency and SPL of moist crackles can be 3.7 ± 0.2% and 4.5 ± 0.3% slightly higher than that of rhonchi, respectively. This research is conducive to the establishment of a rapid and accurate noninvasive diagnosis system for respiratory diseases.

Anti-inflammatory therapy of atherosclerosis: focusing on IKKβ

Chronic low-grade inflammation has been identified as a major contributor in the development of atherosclerosis. Nuclear Factor-κappa B (NF-κB) is a critical transcription factors family of the inflammatory pathway. As a major catalytic subunit of the IKK complex, IκB kinase β (IKKβ) drives canonical activation of NF-κB and is implicated in the link between inflammation and atherosclerosis, making it a promising therapeutic target. Various natural product derivatives, extracts, and synthetic, show anti-atherogenic potential by inhibiting IKKβ-mediated inflammation. This review focuses on the latest knowledge and current research landscape surrounding anti-atherosclerotic drugs that inhibit IKKβ. There will be more opportunities to fully understand the complex functions of IKKβ in atherogenesis and develop new effective therapies in the future.

Dependable algorithm for visualizing snoring duration through acoustic analysis: A pilot study

Snoring is a nuisance for the bed partners of people who snore and is also associated with chronic diseases. Estimating the snoring duration from a whole-night sleep period is challenging. The authors present a dependable algorithm for visualizing snoring durations through acoustic analysis. Both instruments (Sony digital recorder and smartphone's SnoreClock app) were placed within 30 cm from the examinee's head during the sleep period. Subsequently, spectrograms were plotted based on audio files recorded from Sony recorders. The authors thereby developed an algorithm to validate snoring durations through visualization of typical snoring segments. In total, 37 snoring recordings obtained from 6 individuals were analyzed. The mean age of the participants was 44.6 ± 9.9 years. Every recorded file was tailored to a regular 600-second segment and plotted. Visualization revealed that the typical features of the clustered snores in the amplitude domains were near-isometric spikes (most had an ascending-descending trend). The recorded snores exhibited 1 or more visibly fixed frequency bands. Intervals were noted between the snoring clusters and were incorporated into the whole-night snoring calculation. The correlative coefficients of snoring rates from digitally recorded files examined between Examiners A and B were higher (0.865, P < .001) than those with SnoreClock app and Examiners (0.757, P < .001; 0.787, P < .001, respectively). A dependable algorithm with high reproducibility was developed for visualizing snoring durations.

Combined Airway and Bariatric Surgery (CABS) for Obstructive Sleep Apnea Patients with Morbid Obesity: A Comprehensive Alternative Preliminary Study

Although continuous positive airway pressure is the gold standard for obstructive sleep apnea (OSA), it does not improve obesity. By contrast, bariatric surgery significantly improves obesity but with sustained OSA in the majority of patients. This study proposes a comprehensive technique—combined airway and bariatric surgery (CABS)—to improve both obesity and OSA. The aims of the study are to evaluate the feasibility, safety and efficacy of CABS in morbidly obese OSA patients. The retrospective study enrolled 20 morbidly obese OSA patients (13 males; median age, 44 years; median apnea−hypopnea index (AHI), 63.2 event/h; median body mass index (BMI), 41.4 kg/m2). The study population was divided into two groups based on patients’ volition after shared decision making. The bariatric surgery (BS) group included laparoscopic sleeve gastrectomy (LSG, n = 8) and laparoscopic Roux-en-Y gastric bypass (LRYGB, n = 2). CABS involved bariatric surgery—LSG (n = 8) and LRYGB (n = 2) in conjunction with airway surgery (concurrent nasal/palatal/lingual surgery [n = 8], concurrent palatal/lingual surgery [n = 2]). Patients received a home sleep apnea test at baseline and one year after surgery. The two patient groups were not different in age, sex, preoperative AHI or preoperative BMI. There was no airway compromise, wound bleeding or infection throughout the postoperative period. One year after surgery, patients in both groups achieved significant improvement in AHI and BMI. Furthermore, the improvement in AHI was significantly higher (p = 0.04) in the CABS group than in the BS group despite the insignificant change in BMI reduction (p = 0.63) between the two groups. In the CABS group, the BMI dropped from 40.4 to 28.4 kg/m2 (p < 0.0001) and the AHI decreased from 75.1 to 4.5 event/h (p = 0.0004). The classic success rate for OSA was 90% and the cure rate was 60% in the CABS group. A perioperative assessment of CABS group patients also revealed a significant improvement in the Epworth sleepiness scale, minimal O2 saturation, snoring index and heart rate. CABS is feasible and safe in treating OSA with morbid obesity. CABS achieves more reduction in AHI than BS alone with high success and cure rates for OSA. CABS can also significantly improve quality of life and general health and offers a comprehensive alternative for morbidly obese OSA patients.

Obstructive Sleep Apnea and Auditory Dysfunction—Does Snoring Sound Play a Role?

The objective of the study was to investigate the relationship between obstructive sleep apnea (OSA) and auditory dysfunction, and to clarify the role of snoring sounds in contributing to auditory dysfunction. A comprehensive assessment of OSA and the auditory system was performed, including overnight polysomnography, detection of the intra-ear canal snoring sound energy (SSE), pure tone average (PTA), tinnitus pitch matching, the tinnitus handicap inventory (THI), and the Epworth sleepiness scale (ESS). The patients were identified as having tinnitus if their THI score was higher than zero or their tinnitus pitches were matched to specific frequencies. The median age, body mass index, and apnea–hypopnea index score were 41 years, 26.4 kg/m², and 29.9 events/h, respectively. Among the 50 participants, 46 (92%) had a normal PTA, and only 4 (8%) patients had mild hearing loss. There was no significant difference in PTA among OSA severities (p = 0.52). Among the 50 participants, 33 patients (66%) were identified as having tinnitus. In the tinnitus group (n = 33), the ESS score (p = 0.01) and intra-ear canal SSE of 851–1500 Hz (p = 0.04) were significantly higher than those in the non-tinnitus group (n = 17). OSA patients with a higher ESS score had a higher risk of tinnitus (odds ratio 1.22 [95% CI: 1.01–1.46]). OSA-related auditory dysfunction emerged in tinnitus rather than in hearing impairment. OSA patients with daytime sleepiness had a higher risk of tinnitus. High-frequency SSE can jeopardize cochlea and is a potential mechanism contributing to tinnitus. Detection of snoring sounds through an intra-ear canal device may be more precise in assessing acoustic trauma from snoring sounds to vulnerable auditory system and thus warrants further research.

Long-term benefits of a new oral appliance on adult snoring: a trend analysis

Background: Snoring constitutes a worldwide public health concern that may be associated with daytime fatigue, endothelial dysfunction, vascular injury, stroke, cardiovascular diseases, and diabetes among female patients. This study explored the effects of the so-called Lin Oral Appliance (LOA) on Taiwanese adults’ snoring rates.Methods: A time series analysis was conducted to examine the associations between LOAs’ tongue compressors of different lengths, and snoring rates were calculated using the SnoreClock app. The LOA comprises 2 components: custom-made dental braces and tongue compressors of adjustable lengths; different versions had different-length compressors.Results: Our multiple linear regression time-series model revealed the effects of the LOA on snoring rates. The results indicated the following: i) LOA tongue compressor lengths of 1 and 2.5 cm (LOA-1 and LOA-2.5, respectively) were associated with reduced snoring rates; ii) sleep durations of 5.5-7.5 h and daytime sleepiness were associated with increased snoring rates; and iii) among participants with snoring rates above 10%, the snoring rates observed 1-7 days before a given day constituted a significant factor influencing snoring rates on the given day.Conclusions: We discovered that the LOA could reduce snoring rates and that the 2.5-cm compressor length in the LOA produced the best results.

Obstructive sleep apnea and stroke: The mechanisms, the randomized trials, and the road ahead

When considered separately from cardiovascular disease, stroke is the third leading cause of death in the U.S. and is the leading cause of long-term disability in adults. New approaches that can be offered to the majority of ischemic stroke patients, can be continued throughout post-stroke care, can limit stroke severity, and can complement or even enhance rehabilitation, would transform ischemic stroke recovery. The treatment of obstructive sleep apnea (OSA) in patients with acute ischemic stroke may represent one such approach. This manuscript reviews the epidemiologic studies of the bidirectional association between OSA and stroke, and the mechanisms and molecular signatures of OSA leading to transient ischemic attack and stroke as well as the randomized controlled trials and observational cohort studies examining continuous positive airway treatment efficacy on the impact of stroke outcomes. Finally, the insights these studies provide on future research are also discussed.

Sleep apnea severity based on estimated tidal volume and snoring features from tracheal signals

Sleep apnea can be characterized by reductions in the respiratory tidal volume. Previous studies showed that the tidal volume can be estimated from tracheal sounds and movements called tracheal signals. Additionally, tracheal sounds include the sounds of snoring, a common symptom of obstructive sleep apnea. This study investigates the feasibility of estimating the severity of sleep apnea, as quantified by the apnea/hypopnea index (AHI), using the estimated tidal volume and snoring sounds extracted from tracheal signals. Tracheal signals were recorded simultaneously with polysomnography (PSG). The tidal volume was estimated from tracheal signals. The reductions in the tidal volume were detected as potential respiratory events. Additionally, features related to snoring sounds, which quantified variability, temporal clusters, and dominant frequency of snores, were extracted. A step-wise regression model and a greedy search algorithm were used sequentially to select the optimal set of features to estimate the apnea/hypopnea index and classify participants into healthy individuals and patients with sleep apnea. Sixty-one participants with suspected sleep apnea (age: 51 ± 16, body mass index: 29.5 ± 6.4 kg/m² , apnea/hypopnea index: 20.2 ± 21.2 event/h) who were referred for a sleep test were recruited. The estimated apnea/hypopnea index was strongly correlated with the polysomnography-based apnea/hypopnea index (R²  = 0.76, p < 0.001). The accuracy of detecting sleep apnea for the apnea/hypopnea index cutoff of 15 events/h was 78.69% and 83.61% with and without using snore-related features. These findings suggest that acoustic estimation of airflow and snore-related features can provide a convenient and reliable method for screening of sleep apnea.

Screening Severe Obstructive Sleep Apnea in Children with Snoring

Efficient screening for severe obstructive sleep apnea (OSA) is important for children with snoring before time-consuming standard polysomnography. This retrospective cross-sectional study aimed to compare clinical variables, home snoring sound analysis, and home sleep pulse oximetry on their predictive performance in screening severe OSA among children who habitually snored. Study 1 included 9 (23%) girls and 30 (77%) boys (median age of 9 years). Using univariate logistic regression models, 3% oxygen desaturation index (ODI3) ≥ 6.0 events/h, adenoidal-nasopharyngeal ratio (ANR) ≥ 0.78, tonsil size = 4, and snoring sound energy of 801–1000 Hz ≥ 22.0 dB significantly predicted severe OSA in descending order of odds ratio. Multivariate analysis showed that ODI3 ≥ 6.0 events/h independently predicted severe pediatric OSA. Among several predictive models, the combination of ODI3, tonsil size, and ANR more optimally screened for severe OSA with a sensitivity of 91% and a specificity of 94%. In Study 2 (27 (27%) girls and 73 (73%) boys; median age, 7 years), this model was externally validated to predict severe OSA with an accuracy of 76%. Our results suggested that home sleep pulse oximetry, combined with ANR, can screen for severe OSA more optimally than ANR and tonsil size among children with snoring.

Cardiovascular risks of children with primary snoring: A 5-year follow-up study

BACKGROUND AND OBJECTIVE

This study aimed to investigate if childhood primary snoring (PS) was associated with adverse cardiovascular outcomes at 5-year follow-up.

METHODS

This was a prospective matched cohort study. Subjects were recruited from a hospital-based cohort established from years 2006 to 2012 and they were aged 6-18 years at baseline. Each subject with PS was gender, age and BMI z-score matched with a control who had normal sleep study (obstructive apnoea-hypopnoea index [OAHI] < 1/h) and without habitual snoring (<3 nights/week) at baseline. All subjects underwent measurements of flow-mediated dilation (FMD) and carotid intima-media thickness (cIMT) and sleep study at baseline and follow-up visits. Twenty-four hour ambulatory blood pressure (ABP) was also recorded at follow-up.

RESULTS

Fifty-five case-control pairs were recruited and the length of follow-up was 5.1 ± 1.3 years. At follow-up visit, subjects with PS at baseline had significantly lower FMD (-0.34% [-0.59 to -0.10]), greater cIMT (+0.01 mm [+0.001 to +0.013]), higher wake systolic blood pressure (SBP) (+2.6 mm Hg [+0.02 to +5.1]), sleep SBP (+3.0 mm Hg [+0.3 to +5.6]), sleep diastolic blood pressure (+2.2 mm Hg [+0.04 to +4.4]) and sleep mean arterial pressure (+2.2 mm Hg [+0.1 to +4.2]) compared to matched controls in the fully adjusted model for variables including change in OAHI and parental history of cardiovascular diseases.

CONCLUSION

Childhood PS is associated with poorer endothelial function, greater cIMT and higher ABP at 5-year follow-up irrespective of change in obstructive sleep apnoea severity.

Automatic classification of excitation location of snoring sounds

STUDY OBJECTIVES

For surgical treatment of patients with obstructive sleep apnea-hypopnea syndrome, it is crucial to locate accurately the obstructive sites in the upper airway; however, noninvasive methods for locating the obstructive sites have not been well explored. Snoring, as the cardinal symptom of obstructive sleep apnea-hypopnea syndrome, should contain information that reflects the state of the upper airway. Through the classification of snores produced at four different locations, this study aimed to test the hypothesis that snores generated by various obstructive sites differ.

METHODS

We trained and tested our model on a public data set that comprised 219 participants. For each snore episode, an acoustic and a physiological feature were extracted and concatenated, forming a 59-dimensional fusion feature. A principal component analysis and a support machine vector were used for dimensional reduction and snore classification. The performance of the proposed model was evaluated using several metrics: sensitivity, precision, specificity, area under the receiver operating characteristic curve, and F1 score.

RESULTS

The unweighted average values of sensitivity, precision, specificity, area under the curve, and F1 were 86.36%, 89.09%, 96.4%, 87.9%, and 87.63%, respectively. The model achieved 98.04%, 80.56%, 72.73%, and 94.12% sensitivity for types V (velum), O (oropharyngeal), T (tongue), and E (epiglottis) snores.

CONCLUSIONS

The characteristics of snores are related to the state of the upper airway. The machine-learning-based model can be used to locate the vibration sites in the upper airway.

Validation of snoring detection using a smartphone app

Purpose

Snoring is closely related to obstructive sleep apnea in adults. The increasing abundance and availability of smartphone technology has facilitated the examination and monitoring of snoring at home through snoring apps. However, the accuracy of snoring detection by snoring apps is unclear. This study explored the snoring detection accuracy of Snore Clock—a paid snoring detection app for smartphones.

Methods

Snoring rates were detected by smartphones that had been installed with the paid app Snore Clock. The app provides information on the following variables: sleep duration, snoring duration, snoring loudness (in dB), maximum snoring loudness (in dB), and snoring duration rate (%). In brief, we first reviewed the snoring rates detected by Snore Clock; thereafter, an ear, nose, and throat specialist reviewed the actual snoring rates by using the playback of the app recordings.

Results

In total, the 201 snoring records of 11 patients were analyzed. Snoring rates measured by Snore Clock and those measured manually were closely correlated (r = 0.907). The mean snoring detection accuracy rate of Snore Clock was 95%, with a positive predictive value, negative predictive value, sensitivity, and specificity of 65% ± 35%, 97% ± 4%, 78% ± 25%, and 97% ± 4%, respectively. However, the higher the snoring rates, the higher were the false-negative rates for the app.

Conclusion

Snore Clock is compatible with various brands of smartphones and has a high predictive value for snoring. Based on the strong correlation between Snore Clock and manual approaches for snoring detection, these findings have validated that Snore Clock has the capacity for at-home snoring detection.

Relative tidal volume and respiratory airflow estimation using tracheal sound and movement during sleep

Airflow is the reference signal to assess sleep respiratory disorders, such as sleep apnea. Previous studies estimated airflow using tracheal sounds in short segments with specific airflow rates, while requiring calibration or a few breaths for tuning the relationship between sound energy and airflow. Airflow-sound relationship can change by posture, sleep stage and airflow rate or tidal volume. We investigated the possibility of estimating surrogates of tidal volume without calibration in the adult sleep apnea population using tracheal sounds and movements. Two surrogates of tidal volume: thoracoabdominal range of sum movement and airflow level were estimated. Linear regression was used to estimate thoracoabdominal range of sum movement from sound energy and the range of movements. The sound energy lower envelope was found to correlate with airflow level. The agreement between reference and estimated signals was assessed by repeated-measure correlation analysis. The estimated tidal volumes were used to estimate the airflow signal. Sixty-one participants (30 females, age: 51 ± 16 years, body mass index: 29.5 ± 6.4 kg m^-2 , and apnoea-hypopnea index: 20.2 ± 21.2) were included. Reference and estimated thoracoabdominal range of sum movement of whole night data were significantly correlated with the reference signal extracted from polysomnography (r = 0.5 ± 0.06). Similarly, significant correlations (r = 0.3 ± 0.05) were found for airflow level. Significant differences in estimated surrogates of tidal volume were found between normal breathing and apnea/hypopnea. Surrogate of airflow can be extracted from tracheal sounds and movements, which can be used for assessing the severity of sleep apnea and even phenotyping sleep apnea patients based on the estimated airflow shape.

Automatic Respiratory Phase Identification Using Tracheal Sounds and Movements During Sleep

One of the most important signals to assess respiratory function, especially in patients with sleep apnea, is airflow. A convenient method to estimate airflow is based on analyzing tracheal sounds and movements. However, this method requires accurate identification of respiratory phases. Our goal is to develop an automatic algorithm to analyze tracheal sounds and movements to identify respiratory phases during sleep. Data from adults with suspected sleep apnea who were referred for in-laboratory sleep studies were included. Simultaneously with polysomnography, tracheal sounds and movements were recorded with a small wearable device attached to the suprasternal notch. First, an adaptive detection algorithm was developed to localize the respiratory phases in tracheal sounds. Then, for each phase, a set of morphological features from sound energy and tracheal movement were extracted to classify the localized phases into inspirations or expirations. The average error and time delay of detecting respiratory phases were 7.62% and 181 ms during normal breathing, 8.95% and 194 ms during snoring, and 13.19% and 220 ms during respiratory events, respectively. The average classification accuracy was 83.7% for inspirations and 75.0% for expirations. Respiratory phases were accurately identified from tracheal sounds and movements during sleep.

Snoring severity is associated with carotid vascular remodeling in young adults with overweight and obesity

BACKGROUND

Snoring is often used as a surrogate measure for obstructive sleep apnea (OSA), a sleep disorder associated with cardiovascular disease (CVD) risk. Whether snoring is linked to CVD independent of OSA remains unclear. We aimed to explore the snoring and subclinical CVD association in adults with and without OSA.

METHODS

We conducted a cross-sectional study in 122 overweight/obese participants (24% male; mean age 40.1 years) attending the 24-month follow-up visit of a lifestyle intervention. Using home-based objective measures of sleep-disordered breathing, we stratified participants into 3 snoring/OSA categories using the snoring index (SI), a measure of snoring vibration, and oxygen desaturation index (ODI): (1) OSA (ODI ≥ 5), (2) non-OSA heavy snorer (ODI <5, above-median SI), and (3) non-OSA low snorer (ODI <5, below-median SI). Vascular measures including pulse wave velocity ([PWV]; carotid-femoral [cf], femoral-ankle [fa], brachial-ankle [ba]), carotid intima-media thickness (IMT), and carotid interadventitial diameter (IAD) were compared across snoring/OSA categories. Linear regressions assessed the association between snoring and subclinical CVD independent of traditional CVD risk factors.

RESULTS

Compared to non-OSA low snorers, common carotid IMT and IAD were higher in non-OSA heavy snorers, and faPWV, IMT, and IAD were higher among those with OSA. The difference between non-OSA heavy snorers and low snorers persisted after adjusting for age, race, sex, blood pressure, body mass index, lipids, and insulin resistance (P < .05 for IMT and IAD).

CONCLUSIONS

In overweight/obese young to middle-aged adults, objectively measured snoring was related to vascular remodeling in those without OSA. Snoring may contribute to CVD risk but warrants further examination in larger prospective cohorts.

Snoring Sound Characteristics are Associated with Common Carotid Artery Profiles in Patients with Obstructive Sleep Apnea

BACKGROUND

Obstructive sleep apnea (OSA) and snoring have been reported to be modifiable risk factors for thick carotid intima-media thickness (CIMT) and carotid atherosclerosis, which are closely linked to cardiovascular disease.

METHODS

This cross-sectional study prospectively recruited 70 participants with OSA and without a history of carotid artery disorder, who primarily sought surgical Intervention. OSA and snoring were assessed with the Epworth Sleepiness Scale, Snore Outcomes Survey, polysomnography, and snoring sound recording. The carotid arteries were evaluated with ultrasonography and divided into three types of carotid artery profiles (normal carotid artery, thick CIMT, or significant carotid atherosclerosis). Multivariate linear/logistic/categorical regressions were performed with the forward selection approaches/logistic least absolute shrinkage and selection operator, as appropriate.

RESULTS

Normalized snoring sound energy (301-850 Hz) was independently associated with the carotid intima-media thickness (regression coefficient [β] = 0.01, standard error [SE] = 0.004, P = 0.03; R ² = 0.067) and type of carotid profile (β = 0.40, SE = 0.09, P < 0.001; R ² = 0.156). Normalized snoring sound energy (4-300 Hz) (β = -0.10, SE = 0.04, P = 0.01) and female sex (β = 1.90, SE = 0.94, P = 0.04) were independently related to the presence of carotid stenosis (R ² = 0.159). The optimal regression model of the type of carotid artery profile included normalized snoring sound energy (301-850 Hz) (β = 0.33, SE = 0.14, P = 0.03), snoring time (β = 0.26, SE = 0.13, P = 0.047), female sex (β = 0.26, SE = 0.13, P = 0.047), and increased age (β = 0.20, SE = 0.10, P = 0.04) under the control of the Snore Outcomes Survey score, 3% oxygen desaturation index, snoring sound energy (4-1500 Hz), normalized snoring sound energy (851-1500 Hz), cigarette smoking, and hyperlipidemia (R ² = 0.427).

CONCLUSION

Our findings suggested that snoring sound characteristics are associated with carotid artery profiles among early OSA patients who cannot be noticed by ultrasound because organic changes of the carotid artery have not yet started. Future studies are warranted to verify the clinical significance of the results.

Removing of Snoring Segments from Tracheal Breathing Sounds using a Wavelet-based Algorithm

Tracheal sounds represent information about the upper airway and respiratory airflow, however, they can be contaminated by the snoring sounds. The sound of snoring has spectral content in a wide range that overlaps with that of breathing sounds during sleep. For assessing respiratory airflow using tracheal breathing sound, it is essential to remove the effect of snoring. In this paper, an automatic and unsupervised wavelet-based snoring removal algorithm is presented. Simultaneously with full-night polysomnography, the tracheal sound signals of 9 subjects with different levels of airway obstruction were recorded by a microphone placed over the trachea during sleep. The segments of tracheal sounds that were contaminated by snoring were manually identified through listening to the recordings. The selected segments were automatically categorized based on including discrete or continuous snoring pattern. Segments with discrete snoring were analyzed by an iterative wave-based filtering optimized to separate large spectral components related to snoring from smaller ones corresponded to breathing. Those with continuous snoring were first segmented into shorter segments. Then, each short segments were similarly analyzed along with a segment of normal breathing extracted from the recordings during wakefulness. The algorithm was evaluated by visual inspection of the denoised sound energy and comparison of the spectral densities before and after removing snores, where the overall rate of detectability of snoring was less than 2%.Clinical Relevance- The algorithm provides a way of separating snoring pattern from the tracheal breathing sounds. Therefore, each of them can be analyzed separately to assess respiratory airflow and the pathophysiology of the upper airway during sleep.

Self-reported Snoring Patterns Predict Stroke Events in High-Risk Patients With OSA: Post Hoc Analyses of the SAVE Study

BACKGROUND

The relation of snoring to risks of stroke and other major cardiovascular (CV) events is uncertain.

RESEARCH QUESTION

We aimed to determine associations of snoring patterns and major CV events in relation to OSA among participants of the international Sleep Apnea cardiovascular Endpoints (SAVE) trial.

STUDY DESIGN AND METHODS

Post hoc analyses of the SAVE trial, which involved 2,687 patients with coexisting moderate-to-severe OSA and established coronary or cerebral CV disease, who were randomly allocated to CPAP treatment plus usual care or usual care alone, and followed-up for a median 3.5 years. Associations of self-reported snoring patterns (frequency and loudness) and breathing pauses collected on the Berlin questionnaire at baseline and multiple times during follow-up, and adjudicated composites of CV outcomes (primary, CV death, nonfatal myocardial infarction, nonfatal stroke, and hospitalization for unstable angina, heart failure, or transient ischemic attack; and separately of cardiac and cerebral events), were evaluated in time-dependent Cox proportional hazards models adjusted for various confounders including the apnea-hypopnea index.

RESULTS

Increase (per category) of snoring frequency (adjusted hazard ratio [HR], 1.10; 95% CI, 1.02-1.20; P = .015), loudness (HR, 1.16; 95% CI, 1.06-1.27; P = .001), and breathing pauses (HR, 1.16; 95% CI, 1.08-1.25; P < .001) at any time point during follow-up were each associated with the primary composite CV outcome. These associations were driven by significant associations for cerebral rather than cardiac events, and positive interactions between the three snoring patterns for cerebral events. There was no significant interaction between CPAP treatment and snoring variables for cerebral events.

INTERPRETATION

Snoring in patients with OSA with established CV disease is associated with greater risks of cerebral but not cardiac events, independent of CPAP treatment and frequency of apnea and hypopnea events.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT00738179; URL: www.clinicaltrials.gov.

Why and When to Treat Snoring

It is estimated that half of the adult population older than 60 years snores. This article discusses the many aspects of snoring, including impacts on bed partners, the individual who snores, and when and how to appropriately evaluate, diagnose, and treat the perpetrator. The goal is for clinicians to expand their knowledge regarding diagnosis and treatment of the phenomenon of snoring.It is estimated that half of the adult population over the age of 60 years of age snores. This chapter discusses snoring, including the impact on bed partners, the individual that snores and when and how to treat the snorer. The goal is for clinicians to expand their knowledge regarding diagnosis and treatment of patients who snores.

A Deep Learning Model for Snoring Detection and Vibration Notification Using a Smart Wearable Gadget

Snoring, a form of sleep-disordered breathing, interferes with sleep quality and quantity, both for the person who snores and often for the person who sleeps with the snorer. Poor sleep caused by snoring can create significant physical, mental, and economic problems. A simple and natural solution for snoring is to sleep on the side, instead of sleeping on the back. In this project, a deep learning model for snoring detection is developed and the model is transferred to an embedded system—referred to as the listener module—to automatically detect snoring. A novel wearable gadget is developed to apply a vibration notification on the upper arm until the snorer sleeps on the side. The gadget is rechargeable, and it is wirelessly connected to the listener module using low energy Bluetooth. A smartphone app—connected to the listener module using home Wi-Fi—is developed to log the snoring events with timestamps, and the data can be transferred to a physician for treating and monitoring diseases such as sleep apnea. The snoring detection deep learning model has an accuracy of 96%. A prototype system consisting of the listener module, the wearable gadget, and a smartphone app has been developed and tested successfully.

Snoring sound energy as a potential biomarker for disease severity and surgical response in childhood obstructive sleep apnoea: A pilot study

OBJECTIVE

To investigate the relationship between baseline snoring sound energy (SSE) and disease severity, changes in SSE after adenotonsillectomy, and the predictors of surgical success in children with obstructive sleep apnoea (OSA).

DESIGN

Prospective cohort study.

SETTING

Tertiary referral medical centre.

PARTICIPANTS

Thirty-two children with OSA whose apnoea-hypopnoea index ≥5 or apnoea-hypopnoea index ≥1.5 with OSA comorbidities were recruited. Patients with complicated OSA were excluded. All participants underwent snoring sound analysis, polysomnography, and adenotonsillectomy.

MAIN OUTCOME MEASURES

Snoring sound energy and apnoea-hypopnoea index were assessed at baseline and 6 months after adenotonsillectomy. Surgical success was defined as a postoperative apnoea-hypopnoea index <1.5.

RESULTS

The median age, body mass index, and apnoea-hypopnoea index was 9 years, 19.0 kg/m² , and 13.2 events/h, respectively. Multivariate logistic regression showed that a baseline tonsil size of IV (odds ratio 15.7 [95% CI: 1.5-166.3]) and SSE of 801-1000 Hz > 21.9 dB (odds ratio 32.3 [95% CI: 2.6-396.6]) were significantly related to severe OSA. Following adenotonsillectomy, apnoea-hypopnoea index decreased significantly (P < 0.001). SSE of 41-200 Hz, 201-400 Hz and 801-1000 Hz also decreased significantly (P = 0.04, 0.01 and 0.006, respectively). Baseline SSE of 801-1000 Hz < 8.5 dB significantly predicted surgical success (odds ratio 11.0 [95% CI: 1.4-85.2]).

CONCLUSIONS

Our findings suggest the potential utility of SSE of 801-1000 Hz to screen for severe OSA, predict surgical success and assess therapeutic outcomes. Specific baseline SSE may represent a potential biomarker for childhood OSA.

Snoring and carotid artery disease: A new risk factor emerges

OBJECTIVES/HYPOTHESIS

Previous studies have identified a relationship between snoring, carotid intima media thickening, and the presence of atherosclerosis. This study examines the correlation between snoring and carotid artery disease through use of duplex ultrasound identifying greater than 50% internal carotid artery stenosis.

STUDY DESIGN

Prospective cohort study.

METHODS

Patients presenting to three academic vascular laboratories for carotid duplex examination completed the following surveys: demographic information, assessment of risk factors for carotid stenosis, assessment of history of obstructive sleep apnea, or continuous positive airway pressure use and Snoring Outcomes Survey. Patients were categorized into 2 groups based on the presence or absence of carotid disease. Data were analyzed by univariate contingency tables and logistic regression analysis.

RESULTS

Five hundred one patients completed the survey, of whom 243/501 (49%) had evidence of carotid occlusive disease. On univariate analysis, smoking, hypertension, heart disease, hypercholesterolemia, diabetes, and stroke all correlated with greater than 50% carotid stenosis. Multivariate analysis indicated that snorers were significantly more likely to have carotid disease. Three hundred twenty-seven participants were thought to have primary snoring. On univariate analysis, snorers were found to be significantly more likely to have carotid disease. After adjustment for covariates, snoring was not significant for carotid disease. However, multivariate analysis showed snorers to be significantly more likely to have bilateral carotid disease.

CONCLUSIONS

This study shows a potential relationship between snoring and bilateral carotid artery stenosis greater than 50%; snorers have risk of carotid stenosis twice that of nonsnorers. Further investigation is warranted to better elucidate this relationship.

LEVEL OF EVIDENCE

2b Laryngoscope, 129:265-268, 2019.

Assessment of atherosclerotic plaque activity in patients with sleep apnea using hybrid positron emission tomography/magnetic resonance imaging (PET/MRI): a feasibility study

PURPOSE

Evidence suggests that the inflammatory state of an atherosclerotic plaque is important in predicting future risk of plaque rupture. This study aims to investigate the feasibility of measuring plaque inflammation in patients with obstructive sleep apnea (OSA) utilizing advanced vascular imaging - hybrid positron-emission tomography/magnetic resonance imaging (PET/MRI) with fluorodeoxyglucose (FDG) tracer-before and after continuous positive airway pressure (CPAP).

METHODS

Patients with newly diagnosed moderate to severe OSA underwent baseline PET/MRI for assessment of vascular inflammation of the carotid arteries and thoracic aorta prior to initiation of CPAP. Those adherent to CPAP returned for repeat imaging after 3-6 months of CPAP use. Atherosclerotic plaque activity, as measured by arterial wall FDG uptake, was calculated using target-to-background ratios (TBR) before and after CPAP.

RESULTS

Five patients were recruited as part of a focused project. Mean age was 52 years (80% male), and mean apnea-hypopnea index (AHI) was 33. Three patients were objectively adherent with CPAP. In the pre-CPAP phase, all patients had focal FDG uptake in the carotid arteries and aorta. After CPAP, there was an average reduction in TBR of 5.5% (TBR_mean) and 6.2% (TBR_max) in carotid and aortic plaque inflammation, similar in magnitude to the reduction observed with statin therapy alone in non-OSA patients (previously reported by others).

CONCLUSIONS

We demonstrate the feasibility of using hybrid PET/MRI to assess atherosclerotic plaque inflammation in patients with OSA before and after CPAP. Use of the vascular PET/MRI platform in patients with OSA may provide better insight into the role of OSA and its treatment in reducing atherosclerotic inflammation.

Numerical study of dynamic glottis and tidal breathing on respiratory sounds in a human upper airway model

BACKGROUND

Human snores are caused by vibrating anatomical structures in the upper airway. The glottis is a highly variable structure and a critical organ regulating inhaled flows. However, the effects of the glottis motion on airflow and breathing sound are not well understood, while static glottises have been implemented in most previous in silico studies. The objective of this study is to develop a computational acoustic model of human airways with a dynamic glottis and quantify the effects of glottis motion and tidal breathing on airflow and sound generation.

METHODS

Large eddy simulation and FW-H models were adopted to compute airflows and respiratory sounds in an image-based mouth-lung model. User-defined functions were developed that governed the glottis kinematics. Varying breathing scenarios (static vs. dynamic glottis; constant vs. sinusoidal inhalations) were simulated to understand the effects of glottis motion and inhalation pattern on sound generation. Pressure distributions were measured in airway casts with different glottal openings for model validation purpose.

RESULTS

Significant flow fluctuations were predicted in the upper airways at peak inhalation rates or during glottal constriction. The inhalation speed through the glottis was the predominating factor in the sound generation while the transient effects were less important. For all frequencies considered (20-2500 Hz), the static glottis substantially underestimated the intensity of the generated sounds, which was most pronounced in the range of 100-500 Hz. Adopting an equivalent steady flow rather than a tidal breathing further underestimated the sound intensity. An increase of 25 dB in average was observed for the life condition (sine-dynamic) compared to the idealized condition (constant-rigid) for the broadband frequencies, with the largest increase of approximately 40 dB at the frequency around 250 Hz.

CONCLUSION

Results show that a severely narrowing glottis during inhalation, as well as flow fluctuations in the downstream trachea, can generate audible sound levels.

Sleep apnea and risk of vertigo: A nationwide population-based cohort study

OBJECTIVE

To investigate the risk of vertigo in patients with sleep apnea.

STUDY DESIGN

Retrospective cohort study.

METHODS

This study used data from the National Health Insurance Research Database of Taiwan, a population-based database. A total of 5,025 patients who were newly diagnosed with sleep apnea between January 1, 1997, and December 31, 2012, were identified from the Longitudinal Health Insurance Database 2000, a nationally representative database of 1 million randomly selected patients. Moreover, 20,100 patients without sleep apnea were matched at a 1:4 ratio by age, sex, socioeconomic status, and urbanization level. Patients were followed up until death or the end of the study period (December 31, 2013). The primary outcome was the occurrence of vertigo.

RESULTS

Patients with sleep apnea had a significantly higher cumulative incidence of vertigo than those without sleep apnea (P < 0.001). The adjusted Cox proportional hazard model showed that sleep apnea was significantly associated with a higher incidence of vertigo (hazard ratio, 1.71; 95% confidence interval [CI], 1.48-1.97; P < 0.001). Sensitivity and subgroup analyses were performed to adjust for confounders, including head trauma, diabetes mellitus, hypertension, stroke, and obesity. Sleep apnea was demonstrated to be an independent risk factor for vertigo.

CONCLUSION

This is the first nationwide population-based cohort study to investigate the association between sleep apnea and vertigo. The findings strongly support that sleep apnea is an independent risk factor for vertigo. Based on the study results, physicians should be aware of potential vertigo occurrence following sleep apnea.

LEVEL OF EVIDENCE

4. Laryngoscope, 128:763-768, 2017.

Association between Snoring and High-Risk Carotid Plaque Features

Objectives Previous studies have demonstrated an association between snoring and carotid disease independent of sleep apnea. The aim of this study was to quantify the association between self-reported snoring and high-risk carotid plaque features on magnetic resonance imaging (MRI) that predict stroke. Study Design Cross-sectional. Setting Tertiary care university hospital and affiliated county hospital. Methods We surveyed 133 subjects with asymptomatic carotid artery disease that had been previously evaluated with high-resolution MRI. The survey captured data on self-reported snoring (exposure) and covariates (age, sex, body mass index, and sleep apnea via the STOP-Bang questionnaire). A subset of patients underwent home sleep apnea testing. High-risk carotid plaque features were identified on the high-resolution MRI and included thin/ruptured fibrous cap and intraplaque hemorrhage (outcomes). We quantified the association between snoring and high-risk carotid plaque features with the chi-square test (unadjusted analysis) and multivariate logistic regression adjusting for the covariates. Results Of 133 subjects surveyed, 61 (46%) responded; 32 (52%) reported snoring. Significantly higher proportions of snorers than nonsnorers had a thin/ruptured fibrous cap (56% vs 25%, P = .01) and intraplaque hemorrhage (63% vs 29%, P < .01). In multivariate analysis, snoring was associated with thin/ruptured fibrous cap (odds ratio, 4.4; 95% CI, 1.1-16.6; P = .04) and intraplaque hemorrhage (odds ratio, 8.2; 95% CI, 2.1-31.6; P < .01) after adjusting for age, sex, body mass index, and sleep apnea. Conclusion This pilot study suggests a significant independent association between snoring and high-risk carotid plaque features on MRI. Further study is warranted to confirm these results in a larger cohort of subjects.