Digital Morphometrics: A New Upper Airway Phenotyping Paradigm in OSA

Morphometric measurements of intraoral anatomy in children with Beckwith-Wiedemann syndrome: a novel approach

BACKGROUND

An easy-to-use tool to objectively measure intraoral anatomy with meaningful clinical correlations may improve care for patients with Beckwith-Wiedemann syndrome (BWS), who commonly have symptomatic macroglossia.

METHODS

Children aged 2-17 years with BWS were enrolled between 12/2021 and 01/2024. Digital intraoral photographs with a laser ruler were taken, and morphometric measurements were made using ImageJ software. Relationships between morphometrics and outcomes including BWS clinical score, percentage mosaicism, and incidence of tongue reduction surgery were examined using t-tests and multivariate linear models.

RESULTS

Pharyngeal morphometric measurements were obtained in 49 patients with BWS. Mouth area, width, and height differed significantly across BWS molecular subtypes. Right-to-left tongue width and mouth width were larger in those with loss of methylation at imprinting control region 2 (IC2 LOM) than other BWS variants. Patients with paternal uniparental isodisomy of chromosome 11p15 (pUPD11) had narrower mouths than others. Those with tongue reduction surgery had more tongue ridging than those without surgery. There were correlations between mouth area and BWS clinical score, tongue width and BWS clinical score, and tongue length and percentage mosaicism.

CONCLUSION

Intraoral morphometric measurements are associated with phenotypic burden in BWS. Tongue morphology varies across the BWS spectrum, with IC2 LOM having wider tongues and mouths, and pUPD11 having narrower mouths. Tongue ridging is more common in those selected for surgery. Intraoral morphometric measurements may be safely obtained at low costs across centers caring for children with BWS or others at risk of upper airway obstruction.

Can intraoral and facial photos predict obstructive sleep apnea in the general and clinical population?

STUDY OBJECTIVES

This study aimed to evaluate and compare measurements of standardized craniofacial and intraoral photographs between clinical and general population samples, between groups of individuals with an apnea-hypopnea index (AHI) ≥ 15 and AHI < 15, and their interaction, as well as the relationship with the presence and severity of obstructive sleep apnea (OSA).

METHODS

We used data from 929 participants from Sleep Apnea Global Interdisciplinary Consortium, in which 309 patients from a clinical setting and 620 volunteers from a general population.

RESULTS

AHI ≥ 15 were observed in 30.3% of the total sample and there were some interactions between facial/intraoral measures with OSA and both samples. Mandibular volume (p < 0.01) and lateral face height (p = 0.04) were higher in the AHI ≥ 15 group in the clinical sample compared to the AHI ≥ 15 group in the general population and AHI < 15 group in the clinical sample. When adjusted for sex and age, greater mandible width (p < 0.01) differed both in the clinical and in the general population samples, reflecting AHI severity and the likelihood of OSA. The measure of smaller tongue curvature (p < 0.01) reflected the severity and probability of OSA in the clinical sample and the higher posterior mandibular height (p = 0.04) showed a relationship with higher AHI and higher risk of OSA in the general population. When adjusted for sex, age, and body mass index, only smaller tongue curvature (p < 0.01) was associated with moderate/severe OSA.

CONCLUSIONS

Measures of greater tongue and mandible were associated with increased OSA risk in the clinical sample and craniofacial measurement was associated in the general population sample.

The relationship of tongue fat content and efficacy of uvulopalatopharyngoplasty in Chinese patients with obstructive sleep apnea

BACKGROUND

To investigate the relationship between tongue fat content and severity of obstructive sleep apnea (OSA) and its effects on the efficacy of uvulopalatopharyngoplasty (UPPP) in the Chinese group.

METHOD

Fifty-two participants concluded to this study were diagnosed as OSA by performing polysomnography (PSG) then they were divided into moderate group and severe group according to apnea hypopnea index (AHI). All of them were also collected a series of data including age, BMI, height, weight, neck circumference, abdominal circumference, magnetic resonance imaging (MRI) of upper airway and the score of Epworth Sleepiness Scale (ESS) on the morning after they completed PSG. The relationship between tongue fat content and severity of OSA as well as the association between tongue fat content in pre-operation and surgical efficacy were analyzed.Participants underwent UPPP and followed up at 3rd month after surgery, and they were divided into two groups according to the surgical efficacy.

RESULTS

There were 7 patients in the moderate OSA group and 45 patients in the severe OSA group. The tongue volume was significantly larger in the severe OSA group than that in the moderate OSA group. There was no difference in tongue fat volume and tongue fat rate between the two groups. There was no association among tongue fat content, AHI, obstructive apnea hypopnea index, obstructive apnea index and Epworth sleepiness scale (all P > 0.05), but tongue fat content was related to the lowest oxygen saturation (r=-0.335, P < 0.05). There was no significantly difference in pre-operative tongue fat content in two different surgical efficacy groups.

CONCLUSIONS

This study didn't show an association between tongue fat content and the severity of OSA in the Chinese group, but it suggested a negative correlation between tongue fat content and the lowest oxygen saturation (LSaO2). Tongue fat content didn't influence surgical efficacy of UPPP in Chinese OSA patients.

TRIAL REGISTRATION

This study didn't report on a clinical trial, it was retrospectively registered.

Geometric morphometrics and machine learning from three-dimensional facial scans for difficult mask ventilation prediction

Background

Unanticipated difficult mask ventilation (DMV) is a potentially life-threatening event in anesthesia. Nevertheless, predicting DMV currently remains a challenge. This study aimed to verify whether three dimensional (3D) facial scans could predict DMV in patients scheduled for general anesthesia.

Methods

The 3D facial scans were taken on 669 adult patients scheduled for elective surgery under general anesthesia. Clinical variables currently used as predictors of DMV were also collected. The DMV was defined as the inability to provide adequate and stable ventilation. Spatially dense landmarks were digitized on 3D scans to describe sufficient details for facial features and then processed by 3D geometric morphometrics. Ten different machine learning (ML) algorithms, varying from simple to more advanced, were introduced. The performance of ML models for DMV prediction was compared with that of the DIFFMASK score. The area under the receiver operating characteristic curves (AUC) with its 95% confidence interval (95% CI) as well as the specificity and sensitivity were used to evaluate the predictive value of the model.

Results

The incidence of DMV was 35/669 (5.23%). The logistic regression (LR) model performed best among the 10 ML models. The AUC of the LR model was 0.825 (95% CI, 0.765-0.885). The sensitivity and specificity of the model were 0.829 (95% CI, 0.629-0.914) and 0.733 (95% CI, 0.532-0.819), respectively. The LR model demonstrated better predictive performance than the DIFFMASK score, which obtained an AUC of 0.785 (95% CI, 0.710-0.860) and a sensitivity of 0.686 (95% CI, 0.578-0.847). Notably, we identified a significant morphological difference in the mandibular region between the DMV group and the easy mask ventilation group.

Conclusion

Our study indicated a distinct morphological difference in the mandibular region between the DMV group and the easy mask ventilation group. 3D geometric morphometrics with ML could be a rapid, efficient, and non-invasive tool for DMV prediction to improve anesthesia safety.

Tongue size matters: revisiting the Mallampati classification system in patients with obstructive sleep apnea

Objective: The Mallampati classification system has been used to predict obstructive sleep apnea (OSA). Upper airway soft tissue structures are prone to fat deposition, and the tongue is the largest of these structures. Given that a higher Mallampati score is associated with a crowded oropharynx, we hypothesized that the Mallampati score is associated with tongue volume and an imbalance between tongue and mandible volumes. Methods: Adult males underwent clinical evaluation, polysomnography, and upper airway CT scans. Tongue and mandible volumes were calculated and compared by Mallampati class. Results: Eighty patients were included (mean age, 46.8 years). On average, the study participants were overweight (BMI, 29.3 ± 4.0 kg/m2) and had moderate OSA (an apnea-hypopnea index of 26.2 ± 26.7 events/h). Mallampati class IV patients were older than Mallampati class II patients (53 ± 9 years vs. 40 ± 12 years; p < 0.01), had a larger neck circumference (43 ± 3 cm vs. 40 ± 3 cm; p < 0.05), had more severe OSA (51 ± 27 events/h vs. 24 ± 23 events/h; p < 0.01), and had a larger tongue volume (152 ± 19 cm3 vs. 135 ± 18 cm3; p < 0.01). Mallampati class IV patients also had a larger tongue volume than did Mallampati class III patients (152 ± 19 cm3 vs. 135 ± 13 cm3; p < 0.05), as well as having a higher tongue to mandible volume ratio (2.5 ± 0.5 cm3 vs. 2.1 ± 0.4 cm3; p < 0.05). The Mallampati score was associated with the apnea-hypopnea index (r = 0.431, p < 0.001), BMI (r = 0.405, p < 0.001), neck and waist circumference (r = 0.393, p < 0.001), tongue volume (r = 0.283, p < 0.001), and tongue/mandible volume (r = 0.280, p = 0.012). Conclusions: The Mallampati score appears to be influenced by obesity, tongue enlargement, and upper airway crowding.

Clinical Characteristics Combined with Craniofacial Photographic Analysis in Children with Obstructive Sleep Apnea

Purpose

Distinguishing obstructive sleep apnea (OSA) in a high-risk population remains challenging. This study aimed to investigate clinical features to identify children with OSA combined with craniofacial photographic analysis.

Methods

One hundred and forty-five children (30 controls, 62 with primary snoring, and 53 with OSA) were included. Differences in general demographic characteristics and surface facial morphology among the groups were compared. Risk factors and prediction models for determining the presence of OSA (obstructive sleep apnea-hypopnea index>1) were developed using logistic regression analysis.

Results

The BMI (z-score), tonsil hypertrophy, and lower face width (adjusted age, gender, and BMI z-score) were showed significantly different in children with OSA compared with primary snoring and controls (adjusted p<0.05). The screening model based on clinical features and photography measurements correctly classified 79.3% of the children with 64.2% sensitivity and 89.1% specificity. The area under the curve of the model was 81.0 (95% CI, 73.5-98.4%).

Conclusion

A screening model based on clinical features and photography measurements would be helpful in clinical decision-making for children with highly suspected OSA if polysomnography remains inaccessible in resource-stretched healthcare systems.

Do brachycephaly and nose size predict the severity of obstructive sleep apnea (OSA)? A sample-based geometric morphometric analysis of craniofacial variation in relation to OSA syndrome and the role of confounding factors

Obstructive sleep apnea is a common disorder that leads to sleep fragmentation and is potentially bidirectionally related to a variety of comorbidities, including an increased risk of heart failure and stroke. It is often considered a consequence of anatomical abnormalities, especially in the head and neck, but its pathophysiology is likely to be multifactorial in origin. With geometric morphometrics, and a large sample of adults from the Study for Health in Pomerania, we explore the association of craniofacial morphology to the apnea-hypopnea index used as an estimate of obstructive sleep apnea severity. We show that craniofacial size and asymmetry, an aspect of morphological variation seldom analysed in obstructive sleep apnea research, are both uncorrelated to apnea-hypopnea index. In contrast, as in previous analyses, we find evidence that brachycephaly and larger nasal proportions might be associated to obstructive sleep apnea severity. However, this correlational signal is weak and completely disappears when age-related shape variation is statistically controlled for. Our findings suggest that previous work might need to be re-evaluated, and urge researchers to take into account the role of confounders to avoid potentially spurious findings in association studies.

Myofunctional assessment for obstructive sleep apnea and the association with patterns of upper airway collapse: a preliminary study

Objectives

To organize an assessment instrument with questionnaires and myofunctional orofacial/oropharyngeal assessment for OSA patients and correlate it with the upper airway obstructive site detected during drug-induced sleep endoscopy (DISE).

Material and Methods

29 OSA patients aged 22-65 years with an indication to undergo DISE to evaluate an alternative treatment to PAP and signed the consent form. Patients over 65 years old with maxillofacial deficiency and BMI>30 were excluded. The subjects answered the Pittsburgh, Berlin (snore), and Epworth questionnaires. The myofunctional orofacial/oropharyngeal assessment comprised soft palate, palatine pillars, and uvula (structure and mobility), tonsils (size), mandible (bony bases), hard palate (depth and width), tongue (posture, volume, width, and height), floor of mouth (mylohyoid), tongue suction and sustaining (mobility), "lowering of the back of the tongue" (stimulus), which were scored by three speech-language pathologists with expertise. DISE was scored according to VOTE classification. The statistical analysis (t-test) compared groups without and with obstruction in VOTE with questionnaires and myofunctional orofacial/oropharyngeal assessment.

Results

The following were significantly different: snoring frequency (p=0.03) with VOTE/velopharynx; intensity (p=0.02) and frequency of snoring (p=0.03) with VOTE/lateral wall of oropharynx; suction the tongue and sustain (p=0.02) with VOTE/velopharynx; hard palate depth (p=0.02) and width (p=0.05) with obstruction VOTE/epiglottis; tonsils volume (p=0.05) with VOTE/epiglottis; tongue posture (p=0.00) with obstruction VOTE/epiglottis; floor of the mouth (p=0.02) with VOTE/epiglottis.

Conclusion

Higher snoring frequency and intensity was observed in patients with obstruction at the velopharynx and oropharyngeal lateral wall. Obstruction at the velopharynx was associated with poor tongue ability to suck the tongue against the hard palate. Obstruction at the epiglottis had structural and functional associations, including the oropharyngeal lateral wall, affected by the palatine tonsils size, depth and width of the hard palate, tongue position, and flaccidity of the floor of mouth. Considering that this is a preliminary study, the data should be carefully verified and not generalized.

Moderate to severe OSA screening based on support vector machine of the Chinese population faciocervical measurements dataset: a cross-sectional study

OBJECTIVES

Obstructive sleep apnoea (OSA) has received much attention as a risk factor for perioperative complications and 68.5% of OSA patients remain undiagnosed before surgery. Faciocervical characteristics may screen OSA for Asians due to smaller upper airways compared with Caucasians. Thus, our study aimed to explore a machine-learning model to screen moderate to severe OSA based on faciocervical and anthropometric measurements.

DESIGN

A cross-sectional study.

SETTING

Data were collected from the Shanghai Jiao Tong University School of Medicine affiliated Ruijin Hospital between February 2019 and August 2020.

PARTICIPANTS

A total of 481 Chinese participants were included in the study. PRIMARY AND SECONDARY OUTCOME: (1) Identification of moderate to severe OSA with apnoea-hypopnoea index 15 events/hour and (2) Verification of the machine-learning model.

RESULTS

Sex-Age-Body mass index (BMI)-maximum Interincisal distance-ratio of Height to thyrosternum distance-neck Circumference-waist Circumference (SABIHC2) model was set up. The SABIHC2 model could screen moderate to severe OSA with an area under the curve (AUC)=0.832, the sensitivity of 0.916 and specificity of 0.749, and performed better than the STOP-BANG (snoring, tiredness, observed apnea, high blood pressure, BMI, age, neck circumference, and male gender) questionnaire, which showed AUC=0.631, the sensitivity of 0.487 and specificity of 0.772. Especially for asymptomatic patients (Epworth Sleepiness Scale <10), the SABIHC2 model demonstrated better predictive ability compared with the STOP-BANG questionnaire, with AUC (0.824 vs 0.530), sensitivity (0.892 vs 0.348) and specificity (0.755 vs 0.809).

CONCLUSION

The SABIHC2 machine-learning model provides a simple and accurate assessment of moderate to severe OSA in the Chinese population, especially for those without significant daytime sleepiness.

Estimation of Apnea-Hypopnea Index using Deep Learning on 3D Craniofacial Scans

Obstructive sleep apnea (OSA) is characterized by decreased breathing events that occur through the night, with severity reported as the apnea-hypopnea index (AHI), which is associated with certain craniofacial features. In this study, we used data from 1366 patients collected as part of Stanford Technology Analytics and Genomics in Sleep (STAGES) across 11 US and Canadian sleep clinics and analyzed 3D craniofacial scans with the goal of predicting AHI, as measured using gold standard nocturnal polysomnography (PSG). First, the algorithm detects pre-specified landmarks on mesh objects and aligns scans in 3D space. Subsequently, 2D images and depth maps are generated by rendering and rotating scans by 45-degree increments. Resulting images were stacked as channels and used as input to multi-view convolutional neural networks, which were trained and validated in a supervised manner to predict AHI values derived from PSGs. The proposed model achieved a mean absolute error of 11.38 events/hour, a Pearson correlation coefficient of 0.4, and accuracy for predicting OSA of 67% using 10-fold cross-validation. The model improved further by adding patient demographics and variables from questionnaires. We also show that the model performed at the level of three sleep medicine specialists, who used clinical experience to predict AHI based on 3D scan displays. Finally, we created topographic displays of the most important facial features used by the model to predict AHI, showing importance of the neck and chin area. The proposed algorithm has potential to serve as an inexpensive and efficient screening tool for individuals with suspected OSA.

The predictive value of photogrammetry for obstructive sleep apnea

STUDY OBJECTIVES

The aim of this study was to develop a prediction model for obstructive sleep apnea (OSA) based on photographic measurements of upper airway structures and to compare this to the model based on general physical examination.

METHODS

Participants with suspected OSA were recruited consecutively. General physical examination and photography of the oropharyngeal structures were performed prior to polysomnography. Logistic regression analysis was used to establish the prediction models.

RESULTS

A total of 197 eligible participants were included, and 74% were confirmed with OSA. The logistic regression model consisted of 4 photographic measurements (tongue area, uvula area, frenulum length, and retroposition distance) that classified 82.7% of the participants correctly and had 85.6% (95% confidence interval, 78.9-90.9%) sensitivity and 84.3% (95% confidence interval, 71.4-93.0%) specificity at the best cutoff point (0.71). The area under the receiver operating characteristics curve of the model was 0.90, which was higher than that of the model based on general physical measurements alone (area under the curve 0.80). The prediction performance further improved when photographic and general physical measurements were combined (area under the curve 0.93).

CONCLUSIONS

Detailed abnormality data of upper airway structures in OSA could be provided by photogrammetry. Prediction models comprising photographic measurements could be useful in the prediction of OSA.

CLINICAL TRIAL REGISTRATION

Registry: Chinese Clinical Trial Registry; Name: Mechanisms of cessation of respiratory events in patients with different phenotypes of obstructive sleep apnea; URL: http://www.chictr.org.cn/historyversionpuben.aspx?regno=ChiCTR2000031748; Identifier: ChiCTR2000031748.

Simple and Unbiased OSA Prescreening: Introduction of a New Morphologic OSA Prediction Score

PURPOSE

An early prescreening in suspected obstructive sleep apnea (OSA) patients is desirable to expedite diagnosis and treatment. However, the accuracy and applicability of current prescreening tools is insufficient. We developed and tested an unbiased scoring system based solely on objective variables, which focuses on the diagnosis of severe OSA and exclusion of OSA.

PATIENTS AND METHODS

The OSA prediction score was developed (n = 150) and validated (n = 50) within German sleep center patients that were recruited as part of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Six objective variables that were easy to assess and highly correlated with the apnea-hypopnea index were chosen for the score, including some known OSA risk factors: body-mass index, neck circumference, waist circumference, tongue position, male gender, and age (for women only). To test the predictive ability of the score and identify score thresholds, the receiver-operating characteristics (ROC) and curve were calculated.

RESULTS

A score ≥8 for predicting severe OSA resulted in an area under the ROC curve (ROC-AUC) of 90% (95% confidence interval: 84%, 95%), test accuracy of 82% (75%, 88%), sensitivity of 82% (65%, 93%), specificity of 82% (74%, 88%), and positive likelihood ratio of 4.55 (3.00, 6.90). A score ≤5 for predicting the absence of OSA resulted in a ROC-AUC of 89% (83%, 94%), test accuracy of 80% (73%, 86%), sensitivity of 72% (55%, 85%), specificity of 83% (75%, 89%), and positive likelihood ratio of 4.20 (2.66, 6.61). Performance characteristics were comparable in the small validation sample.

CONCLUSION

We introduced a novel prescreening tool combining easily obtainable objective measures with predictive power and high general applicability. The proposed tool successfully predicted severe OSA (important due to its high risk of cardiovascular disease) and the exclusion of OSA (rarely a feature of previous screening instruments, but important for better differential diagnosis and treatment).

The short evaluation of orofacial myofunctional protocol (ShOM) and the sleep clinical record in pediatric obstructive sleep apnea

INTRODUCTION

Multiple anatomic and functional risk factors contribute to Obstructive Sleep Apnea (OSA) in children, most of the screening tools only evaluate clinical symptoms. The aim was to describe the evaluation of the short orofacial myofunctional protocol (ShOM) in OSA children, and to analyze if the inclusion of orofacial myofunctional aspects would influence the screening sensitivity/specificity of the Sleep Clinical Record (SCR).

METHODS

Children from Brazil and Italy with sleep disordered breathing were evaluated by full night polygraphy, the SCR and the ShOM. For the analysis of the correlations, we normalized the distribution of the children based on the percentiles of the Apnea and Hypopnea Index (AHI). The children were divided in: Group1: first percentile AHI up to25% (cut-off value: AHI≤1.9); Group 2: second percentile from 25% to 75% (cut-off values: 1.9˂AHI≤7.9); Group3: third percentile AHI˃75% (cut = off value: AHI˃7.9). The findings of SCR and ShOM were compared for each group. ROC curve of the sensitivity and specificity of OSA diagnosis were compared for SCR alone and the combined results of SCR plus ShOM.

RESULTS

86 children, 47 girls, 4-11 years, were included, 34 children were obese and 20 overweight. OSA severity and obesity showed a positive correlation (p = 0.04). Mean ShOM score was 5.64 ± 2.27, with a positive correlation to the SCR (p = 0.002). In Group1, the SCR showed more nasal obstruction, arched palate and OSAS score/positive Brouilette questionnaire and the ShOM scored more alterations to breathing mode, breathing type (p = 0.01) and lip competence. In Group 3, we found more tonsillar hypertrophy, Friedman tongue position alteration (p < 0.001), malocclusion and obesity at SCR and more alterations in tongue resting position, tongue deglutition position and malocclusion at ShOM.

CONCLUSIONS

The myofuntional evaluation contributed to the screening of OSA in children, while alterations of the tongue (resting and deglutition position) were observed in children with the highest AHI percentile. The combination of SCR and ShOM improved the sensitivity and specificity for the identification of pediatric OSA when compared to SCR alone.

Predictive anatomical factors of lung aerosol deposition in obese individuals. Would modified mallampati score be relevant? Clinical trial

BACKGROUND

Obesity is a highly prevalent condition worldwide that aggravates symptoms of already existing conditions such as asthma and COPD. The limited effectiveness of inhaled medications in these individuals may be related to anatomic characteristics of their upper airways, mainly due to compressive factors.

METHODS

Controlled clinical trial with obese and nonobese individuals. The following variables were evaluated: anthropometric characteristics, Lung and airway deposition of radiolabeled aerosol (pulmonary scintigraphy), upper airways anatomy (CT scans), and modified Mallampati score.

RESULTS

29 subjects (17 nonobese and 12 obese) participated. Obese volunteers presented 30% lower aerosol lung deposition compared to nonobese. Moreover, obese subjects Mallampati classification of 4 presented an aerosol lung deposition two times lower than nonobese subjects (p = 0.021). The cross-sectional area of the retropalatal region and retroglossal region were lower in obese patients (p < 0.05), but no correlation to aerosol lung deposition was observed. BMI was associated with 32% of the variance of lung deposition (p < 0.001; β -0.28; 95% CI -0.43 to -0.11).

CONCLUSION

High BMI correlated to reduced percentage lung deposition. Also, modified Mallampati class 4 was even more detrimental to aerosol delivery into the lungs. Obese subjects have narrower upper airways, compared to nonobese, but this is not reflected in higher radiolabeled aerosol impaction into their oropharynx and does not predict the percentage of lung deposition in this group.

CLINICAL TRIAL REGISTRATION

NCT03031093 (clinicaltrials.org).

Defining Extreme Phenotypes of OSA Across International Sleep Centers

BACKGROUND

Extreme phenotypes of OSA have not been systematically defined.

RESEARCH QUESTION

This study developed objective definitions of extreme phenotypes of OSA by using a multivariate approach. The utility of these definitions for identifying characteristics that confer predisposition toward or protection against OSA is shown in a new prospective sample.

STUDY DESIGN AND METHODS

In a large international sample, race-specific liability scores were calculated from a weighted logistic regression that included age, sex, and BMI. Extreme cases were defined as individuals with an apnea-hypopnea index (AHI) ≥ 30 events/hour but low likelihood of OSA based on age, sex, and BMI (liability scores > 90th percentile). Similarly, extreme controls were individuals with an AHI < 5 events/hour but high likelihood of OSA (liability scores < 10th percentile). Definitions were applied to a prospective sample from the Sleep Apnea Global Interdisciplinary Consortium, and differences in photography-based craniofacial and intraoral phenotypes were evaluated.

RESULTS

This study included retrospective data from 81,338 individuals. A total of 4,168 extreme cases and 1,432 extreme controls were identified by using liability scores. Extreme cases were younger (43.1 ± 14.7 years), overweight (28.6 ± 6.8 kg/m²), and predominantly female (71.1%). Extreme controls were older (53.8 ± 14.1 years), obese (34.0 ± 8.1 kg/m²), and predominantly male (65.8%). These objective definitions identified 29 extreme cases and 87 extreme controls among 1,424 Sleep Apnea Global Interdisciplinary Consortium participants with photography-based phenotyping. Comparisons suggest that a greater cervicomental angle increases risk for OSA in the absence of clinical risk factors, and smaller facial widths are protective in the presence of clinical risk factors.

INTERPRETATION

This objective definition can be applied in sleep centers throughout the world to consistently define OSA extreme phenotypes for future studies on genetic, anatomic, and physiologic pathways to OSA.

Demographic, clinical, and biomarker predictors of apnea-hypopnea index from polysomnography in Midwestern sleep clinic patients

BACKGROUND

To examine if selected demographic (age, gender), clinical (diabetes, coronary artery disease, hyperlipidemia, myocardial infarction, stroke, lung disease, smoking history, alcohol intake), and biomarker [blood pressure (BP), heart rate, body mass index (BMI), neck circumference, Mallampati score] variables are predictors of apnea-hypopnea index (AHI) from polysomnography (PSG).

METHODS

This cross-sectional study recruited a sample of adults (N = 170) who were being evaluated for OSA. Participants completed self-reported demographic and clinical questionnaires, and then completed PSG (n = 142). Multi-collinearity was assessed. Confounding factors, correlations, and potential interactions were explored.

RESULTS

The final regression model was performed on 130 participants; 61 (46.9%) had an AHI ≥ 15. Systolic and diastolic BPs were highly correlated. Interactions were tested between gender and other variables (high cholesterol, BMI, neck circumference, systolic BP) and between systolic BP and other variables (high cholesterol, BMI, neck circumference, and lung disease). No interactions occurred between gender or systolic BP and other variables, meaning that the effects of the variables on AHI levels from PSG did not vary depending on gender or systolic BP. BMI, systolic BP, and absence of lung disease were predictors for AHI levels ≥ 15 from PSG.

CONCLUSIONS

BMI and systolic BP were significant predictors of OSA in this study. The absence of lung disease as a significant predictor was unique and may be due to the small number of participants who self-reported lung disease. To our knowledge, this is the first study to report this combination of variables to predict AHI levels ≥ 15 from PSG.

Utility of the modified Mallampati grade and Friedman tongue position in the assessment of obstructive sleep apnea

STUDY OBJECTIVES

The modified Mallampati (MM) grade and Friedman tongue position (FTP) are commonly used scales that assess the oropharynx during evaluation for obstructive sleep apnea (OSA). Though used by many practitioners, there is controversy in the literature regarding their practical utility. The goal of this review will be to review the history of how the MM and FTP were developed, to discuss current evidence for their usefulness in the workup of OSA, and to provide future direction to better understand their utility in the workup of OSA.

METHODS

We searched the literature (PubMed) for the terms "modified Mallampati" and "Friedman tongue position." Articles were selected based on our study objectives emphasizing articles discussing the utility of MM and FTP in managing OSA.

CONCLUSIONS

MM and FTP have the potential to be useful assessment tools in the evaluation of OSA. When performing this examination, it is important for physicians and other medical providers to understand the pitfalls of the MM and FTP including the potential difficulty in performing the exam and the lack of consistency between examiners in both the terminology and execution of this physical exam finding. Better methods to standardize the assessment are necessary to ensure consistent evaluation among individual examiners while at the same time keeping the method simple and convenient for wide use as a clinical screening tool.

A Screening Algorithm for Obstructive Sleep Apnea in Pregnancy

Rationale: Obstructive sleep apnea (OSA) is common in pregnancy and associated with maternal and fetal complications. Early detection of OSA may have important implications for maternal-fetal well-being. A screening tool combining several methods of assessment may better predict OSA among pregnant women compared with tools that rely solely on self-reported information.Objectives: To develop a screening tool combining subjective and objective measures to predict OSA in pregnant women.Methods: This study is a secondary analysis using data collected from a completed cohort of pregnant women (n = 121 during the first and n = 87 during the third trimester). Participants underwent full polysomnography and completed the Multivariable Apnea Prediction Questionnaire. The Obstructive Sleep Apnea/Hypopnea Syndrome Score and Facco apnea predictive model were obtained. Logistic regression analysis and area under the curve (AUC) were used to identify models predicting OSA risk.Results: Participants' mean age was 27.4 ± 7.0 years. The prevalence of OSA during the first and third trimester was 10.7% and 24.1%, respectively. The final model predicting OSA risk consisted of body mass index, age, and presence of tongue enlargement. During the first trimester, the AUC was 0.86 (95% confidence interval [CI], 0.76-0.96). During the third trimester, the AUC was 0.87 (95% CI, 0.77-0.96). When the first-trimester data were used to predict third-trimester OSA risk, the AUC was 0.87 (95% CI, 0.77-0.97). This model had high sensitivity and specificity when used during both trimesters. The negative posttest probabilities (probability of OSA given a negative test result) ranged from 0.03 to 0.07.Conclusions: A new model consisting of body mass index, age, and presence of tongue enlargement provided accurate screening of OSA in pregnant women, particularly African-Americans. This tool can be easily and rapidly administered in busy clinical practices without depending on patients' awareness of experiencing apnea symptoms.

More Than the Sum of the Respiratory Events: Personalized Medicine Approaches for Obstructive Sleep Apnea

Traditionally, the presence and severity of obstructive sleep apnea (OSA) have been defined by the apnea-hypopnea index (AHI). Continuous positive airway pressure is generally first-line therapy despite low adherence, because it reliably reduces the AHI when used, and the response to other therapies is variable. However, there is growing appreciation that the underlying etiology (i.e., endotype) and clinical manifestation (i.e., phenotype) of OSA in an individual are not well described by the AHI. We define and review the important progress made in understanding and measuring physiological mechanisms (or endotypes) that help define subtypes of OSA and identify the potential use of genetics to further refine disease classification. This more detailed understanding of OSA pathogenesis should influence clinical treatment decisions as well as help inform research priorities and clinical study design. In short, treatments could be individualized on the basis of the underlying cause of OSA; patients could better understand which symptoms and outcomes will respond to OSA treatment and by how much; and researchers could select populations most likely to benefit from specific treatment approaches for OSA.

Further Development of P4 Approach to Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a heterogeneous disorder. Cluster analysis has identified different physiologic subtypes with respect to symptoms. A difference exists in cardiovascular risk from OSA between the 7 subtypes identified. There are 3 basic subtypes replicated in multiple studies: (a) a group where insomnia is the main symptom; (b) an asymptomatic group; (c) a group with marked excessive sleepiness. The symptomatic benefit from treatment with nasal CPAP varies between these 3 subtypes. Data from the Sleep Heart Health Study reveal that the increased risk of cardiovascular disease from OSA occurs only in the excessively sleepy group.

A Global Comparison of Anatomic Risk Factors and Their Relationship to Obstructive Sleep Apnea Severity in Clinical Samples

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is a global health issue and is associated with obesity and oropharyngeal crowding. Global data are limited on the effect of ethnicity and sex on these relationships. We compare associations between the apnea-hypopnea index (AHI) and these risk factors across ethnicities and sexes within sleep clinics.

METHODS

This is a cross-sectional, multicenter study of patients with OSA from eight sleep centers representing the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Four distinct ethnic groups were analyzed, using a structured questionnaire: Caucasians (Australia, Iceland, Germany, United States), African Americans (United States), Asians (Taiwan), and South Americans (Brazil). Regression analyses and interaction tests were used to assess ethnic and sex differences in relationships between AHI and anthropometric measures (body mass index [BMI], neck circumference, waist circumference) or Mallampati score.

RESULTS

Analyses included 1,585 individuals from four ethnic groups: Caucasian (60.6%), African American (17.5%), Asian (13.1%), and South American (8.9%). BMI was most strongly associated with AHI in South Americans (7.8% increase in AHI per 1 kg/m² increase in BMI; P < .0001) and most weakly in African Americans (1.9% increase in AHI per 1 kg/m² increase in BMI; P = .002). In Caucasians and South Americans, associations were stronger in males than females. Mallampati score differed between ethnicities but did not influence AHI differently across groups.

CONCLUSIONS

We demonstrate ethnic and sex variations in associations between obesity and OSA. For similar BMI increases, South American patients show greatest AHI increases compared to African Americans. Findings highlight the importance of considering ethnicity and sex in clinical assessments of OSA risk.

From CPAP to tailored therapy for obstructive sleep Apnoea

Obstructive Sleep Apnoea (OSA) is a common sleep disorder that is associated with daytime symptoms and a range of comorbidity and mortality. Continuous Positive Airway Pressure (CPAP) therapy is highly efficacious at preventing OSA when in use and has long been the standard treatment for newly diagnosed patients. However, CPAP therapy has well recognised limitations in real world effectiveness due to issues with patient acceptance and suboptimal usage. There is a clear need to enhance OSA treatment strategies and options. Although there are a range of alternative treatments (e.g. weight loss, oral appliances, positional devices, surgery, and emerging therapies such as sedatives and oxygen), generally there are individual differences in efficacy and often OSA will not be completely eliminated. There is increasing recognition that OSA is a heterogeneous disorder in terms of risk factors, clinical presentation, pathophysiology and comorbidity. Better characterisation of OSA heterogeneity will enable tailored approaches to therapy to ensure treatment effectiveness. Tools to elucidate individual anatomical and pathophysiological phenotypes in clinical practice are receiving attention. Additionally, recognising patient preferences, treatment enhancement strategies and broader assessment of treatment effectiveness are part of tailoring therapy at the individual level. This review provides a narrative of current treatment approaches and limitations and the future potential for individual tailoring to enhance treatment effectiveness.

Craniofacial Phenotyping in Chinese and Caucasian Patients With Sleep Apnea: Influence of Ethnicity and Sex

STUDY OBJECTIVES

Craniofacial abnormalities are a risk factor for obstructive sleep apnea (OSA). We have previously shown that phenotypic information derived from craniofacial photographs predict OSA in sleep clinic populations. However, there are likely ethnic and sex differences in craniofacial phenotypes related to OSA. We aimed to assess the use of craniofacial photography to identify interactions between OSA, ethnicity, and sex in craniofacial phenotype.

METHODS

Frontal and profile craniofacial photographs were analyzed from two sleep clinic populations of different ethnicity (Hong Kong Chinese, Australian Caucasians). OSA was defined as apnea-hypopnea index (AHI) > 10 events/h. Ten craniofacial measurements (three angles relating to jaw position and seven ratios describing proportions of the face) were examined for interactions between OSA status and sex or ethnicity) using factorial analysis of variance.

RESULTS

A total of 363 subjects (25% female) were included (n = 200 Chinese, n = 163 Caucasian), of which 33% were controls. There were two-way interactions for OSA with both sex (mandibular plane angle [F = 7.0, P = .009], face / eye width ratio [F = 4.7, P = .032], maxillary / mandibular volume ratio [F = 9.2, P = .003]) and ethnicity (face / nose width ratio [F = 4.0, P = .045], mandibular width / length ratio [F = 5.1, P = .024], maxillary / mandibular volume ratio [F = 11.0, P = .001]).

CONCLUSIONS

We provide evidence of ethnic and sex differences in facial phenotype related to OSA. Furthermore, we demonstrate that craniofacial photography can be used as a phenotypic tool to assess these differences and allow investigation of OSA phenotypes in large samples. This has relevance to personalizing OSA recognition strategies across different populations.

Does the Medical Comorbidity Profile of Obstructive Sleep Apnea Patients Treated With Maxillomandibular Advancement Differ From That of Obstructive Sleep Apnea Patients Managed Nonsurgically?

PURPOSE

Obstructive sleep apnea (OSA) patients with retrognathia and measurable anatomic airway determinants may represent a subset of OSA patients and have distinct comorbidity profiles. Our aim was to compare the medical comorbidities of OSA patients managed surgically with maxillomandibular advancement with those of nonsurgical patients.

PATIENTS AND METHODS

In this cross-sectional retrospective study, patients for both cohorts were identified through the Massachusetts General Hospital oral and maxillofacial surgery data registry and the Massachusetts General Hospital Research Patient Data Registry. The inclusion criteria consisted of clinical records documenting body mass index (BMI), apnea-hypopnea index, respiratory disturbance index, and/or oxygen nadir. The primary predictor variable was the treatment modality chosen: surgical (maxillomandibular advancement) or nonsurgical. Demographic information and OSA parameters were evaluated. The primary outcome variable was the number of documented comorbidities in each group. Two-sample t tests were used for continuous variables, whereas χ² or Fisher exact tests were used for categorical variables.

RESULTS

The nonsurgical cohort consisted of 71 patients (67.6% men), and the surgical cohort consisted of 51 patients (84.3% men). Comparison of descriptive characteristics showed that the nonsurgical cohort had a higher average age (49 ± 9.4 years) than the surgical cohort (41 ± 10.7 years, P < .001). In addition, a higher average BMI was present in the nonsurgical group (42.3 ± 11.9 in nonsurgical group vs 29.7 ± 5.5 in surgical group, P < .001). Polysomnogram parameters were comparable with the exception of a higher Epworth Sleepiness Scale score in the surgical cohort (15.5 ± 5.30 in surgical group vs 9.90 ± 6.80 in nonsurgical group, P = .005). The nonsurgical cohort had a higher total number of comorbidities (7 ± 4 in nonsurgical group vs 4 ± 3 in surgical group, P < .001). Hypertension, cardiovascular disease, hyperlipidemia, pulmonary hypertension, obstructive pulmonary disease, and type 2 diabetes mellitus had higher prevalences within the nonsurgical group.

CONCLUSIONS

The results of this study suggest that nonsurgically managed OSA patients tend to have more complex medical comorbidity profiles than those managed surgically. Obesity (BMI >30) was more prevalent in the nonsurgical cohort, which may be contributory. The additive contribution of OSA needs to be further elucidated.