Multi-perspective clustering of obstructive sleep apnea towards precision therapeutic decision including craniofacial intervention.

Kim SJ ，Alnakhli WM ，Alfaraj AS ，Kim KA ，Kim SW ，Liu SY ... -  《-》

Craniofacial abnormalities in Chinese patients with obstructive and positional sleep apnea.

Chang ET ，Shiao GM 《SLEEP MEDICINE》

Clustering-based characterization of clinical phenotypes in obstructive sleep apnoea using severity, obesity, and craniofacial pattern.

To identify and characterize the phenotypes of adult obstructive sleep apnoea (OSA) patients based on clustering using OSA severity, obesity, and craniofacial pattern. The samples consisted of 89 adult OSA patients whose polysomnography and lateral cephalogram were available. With cluster analysis using apneahypopnea index (AHI, events/hour), body mass index (BMI, kg/m2), ANB (degree), and mandibular plane angle (MPA, degree), three clusters were identified. Cephalometric variables including craniofacial, soft palate, hyoid bone, and pharyngeal space compartments were compared among clusters by one-way analysis of variance or Kruskal-Wallis test. Multivariable linear regression analysis was performed to find contributing factors to OSA severity within each cluster. Cluster-1 (obesity type; 49.4 per cent) exhibited moderate OSA, obesity, and normal sagittal and vertical skeletal pattern (AHI, 22.4; BMI, 25.5; ANB, 3.2 degrees; MPA, 26.3 degrees) without significant upper airway abnormality. Cluster-2 (skeletal type; 33.7 per cent) was characterized by moderate OSA, severe skeletal Class II hyperdivergent pattern with narrow pharyngeal airway spaces, without obesity (AHI, 27.9; BMI, 23.5; ANB, 7.5 degrees; MPA, 36.6 degrees). Cluster-3 (complex type; 16.8 per cent) included severe OSA, obesity, skeletal Class II hyperdivergent pattern (AHI, 52.8; BMI, 28.0; ANB, 4.5 degrees; MPA, 32.2 degrees), with posteriorly displaced hyoid and retroclined soft palate. The main contributing factors to AHI were obesity in Cluster-1; hyperdivergent vertical pattern with narrow pharyngeal space in Cluster-2; and hyperdivergent pattern, obesity, displaced hyoid, and soft palate in Cluster-3. Three OSA phenotypes resulted from this study provide a clinical guideline for differential diagnosis and orthodontic intervention in the interdisciplinary treatment for OSA patients.

An HJ ，Baek SH ，Kim SW ，Kim SJ ，Park YG ... -  《-》

The interaction between hypertension and obstructive sleep apnea on subjective daytime sleepiness.

Hypertension is one of the most common chronic cardiovascular diseases in adults while obstructive sleep apnea (OSA) is the most common type of sleep apnea. It was recently reported that the mean Epworth Sleepiness Scale (ESS) score, measuring subjective daytime sleepiness, was significantly higher in non-hypertensive subjects than the hypertensive counterparts with moderate to severe obstructive sleep apnea. In the current study, the authors investigated the interaction between hypertension and OSA on daytime sleepiness among 280 subjects recruited from a sleep study. OSA was evaluated with the Apnea-Hypopnea Index (AHI), and daytime sleepiness was measured with the ESS. Significantly higher mean ESS scores were found for subjects without than those with hypertension (11.3 vs 9.4, P = 0.003) but only a marginally significant difference was discerned for the ESS scores between subjects with AHI ≥15/h and AHI <15/h (P = 0.075). A significant interaction between hypertension and OSA status on daytime sleepiness was observed from the analysis of variance (P = 0.02). The adjusted mean ESS score for the group of normotensive subjects with moderate to severe OSA (13.11) was significantly higher than the other three groups, namely, normotensive subjects with mild OSA (9.35), hypertensive subjects with mild OSA (9.70), and hypertensive subjects with moderate to severe OSA to (9.43). In conclusion, subjective daytime sleepiness of normotensive subjects with moderate to severe OSA was significantly more severe than other subjects.

Tam W ，Ng SS ，To KW ，Ko FW ，Hui DS ... -  《-》

Multidimensional assessment and cluster analysis for OSA phenotyping.

Obstructive sleep apnea (OSA) is a heterogeneous disease with varying phenotype. A cluster analysis based on multidimensional disease characteristics, including symptoms, anthropometry, polysomnography, and craniofacial morphology, in combination with auto-continuous positive airway pressure titration response and comorbidity profiles, was conducted within a well-characterized cohort of patients with OSA, with the aim to refine the current phenotypic expressions of OSA with clinical implications. Two hundred ninety-one patients with a new diagnosis of moderate to severe OSA referred for auto-continuous positive airway pressure titration to the sleep center were included for analysis. In-laboratory polysomnography and craniofacial computed tomography scanning were performed, followed by an auto-continuous positive airway pressure titration. The symptom of excessive daytime sleepiness was assessed using the Epworth Sleepiness Scale. Three patient phenotypes-normal weight, nonsleepy, moderate OSA; obese, nonsleepy, severe OSA; and obese, sleepy, very severe OSA with craniofacial limitation-were identified. Among the polysomnography parameters, only percentage of N3 time of total sleep time (N3%) and mean pulse oxygen saturation were found to be associated with the Epworth Sleepiness Scale score, and they only explained a small fraction of the variation (R2 = .136). Neck circumference and craniofacial limitation were associated with the more severe phenotype, which had a higher prevalence of hypertension and metabolic syndrome, greater diurnal blood gas abnormalities, and worse positive airway pressure titration response. Three OSA phenotypes were identified according to multiple aspects of clinical features in patients with moderate to severe OSA, who differed in their prevalence of hypertension, metabolic syndrome, diurnal blood gas parameters, and continuous positive airway pressure titration response. Self-reported excessive daytime sleepiness was not related with the severity of sleep breathing disturbance, and craniofacial limitation was associated with the more severe phenotype. These findings highlight the necessity of integrating multiple disease characteristics into phenotyping to achieve a better understanding of the clinical features of OSA. Zhang XL, Zhang L, Li YM, et al. Multidimensional assessment and cluster analysis for OSA phenotyping. J Clin Sleep Med. 2022;18(7):1779-1788.

Zhang XL ，Zhang L ，Li YM ，Xiang BY ，Han T ，Wang Y ，Wang C ... -  《-》