The objective of this review was to evaluate the effect of mandibular advancement appliances (MAAs) for obstructive sleep apnea (OSA) in children. To this end, several electronic databases (PubMed, EMBASE, Cochrane Library) were systematically searched until 18 June 2018. Randomized and non-randomized clinical trials were included. Articles of high-quality were included for the meta-analysis. Data extraction and quality assessment were conducted by two independent reviewers. Four randomized controlled trials (RCTs) and three non-RCTs were finally included in the review; of these, two RCTs of high-quality were included in the meta-analysis. The mean difference in apnea-hypopnea index (AHI) change for mandibular advancement group compared with control group was -1.75 events/h (95% confidence interval (CI) -2.07, -1.44), p < 0.00001. Sensitivity analysis including the quasi-randomized RCT and non-RCTs showed stable favorable results for MAAs. The meta-analysis showed supportive evidence for MAA treatment in pediatric OSA patients. Subgroup analysis suggested that MAA can be effective for mild to severe patients before the end of the pubertal peak. Long-term treatment (at least six months) may be more effective than short-term treatment.

Background: When analyzing the relationship between adenotonsillar hypertrophy and craniofacial morphology, researchers generally regarded hypertrophied adenoids and tonsils as a whole. It remains unclear whether different enlarged sites of pharyngeal lymphoid tissue would correlate with multiple craniofacial subtypes. We hypothesized there would be craniofacial subtypes correlated with different locations of hypertrophied adenoid and tonsil. Methods: Lateral cephalometric radiographs were obtained from 466 children (171 boys and 295 girls, aged 12.27 ± 2.69 years). They were divided into four groups according to different sites of enlarged pharyngeal lymphoid tissue: adenoid hypertrophy group (AG, n = 126), tonsillar hypertrophy group (TG, n = 59), adenotonsillar hypertrophy group (ATG, n = 69) and control group (CG, n = 212). Five commonly used angles for cephalometric measurements were investigated: SNA (Sella-Nasion-Point A), SNB (Sella-Nasion-Point B), ANB (Point A-Nasion-Point B), mandibular plane angle (MP/SN) and Y-axis angle (SGn/FH). Results: Children with isolated tonsillar hypertrophy correlated with increased SNA (unstandardized regression coefficient B = 1.38, p = 0.009) and SNB (B = 1.99, p = 0.001) compared with controls. However, children with isolated adenoid hypertrophy correlated with decreased SNB (B=-0.94, p = 0.036), increased ANB (B = 0.74, p = 0.014) and increased MP/SN (B = 2.22, p < 0.001). Similarly, children with adenotonsillar hypertrophy correlated with decreased SNB (B=-1.36, p = 0.015), increased ANB (B = 1.35, p < 0.001) and increased MP/SN (B = 2.64, p = 0.001). Conclusions: Isolated adenoid hypertrophy correlated with a retrognathic mandible, an increased maxillo-mandibular sagittal discrepancy, and an increased mandibular plane angle. Isolated tonsillar hypertrophy correlated with maxillary and mandibular protrusion. Adenotonsillar hypertrophy did not show a superimposed craniofacial pattern of the above two but showed the same craniofacial pattern as isolated adenoid hypertrophy.

Objectives: This study aimed to develop a fully automated artificial intelligence-aided cervical vertebral maturation (CVM) classification method based on convolutional neural networks (CNNs) to provide an auxiliary diagnosis for orthodontists. Methods: This study consisted of cephalometric images from patients aged between 5 and 18 years. After grouping them into six cervical stages (CSs) by orthodontists, a data set was constructed for analyzing CVM using CNNs. The data set was divided into training, validation, and test sets in the ratio of 70, 15, and 15%. Four CNN models namely, VGG16, GoogLeNet, DenseNet161, and ResNet152 were selected as the candidate models. After training and validation, the models were evaluated to determine which of them is most suitable for CVM analysis. Heat maps were analyzed for a deeper understanding of what the CNNs had learned. Results: The final classification accuracy ranking was ResNet152>DenseNet161>GoogLeNet>VGG16, as evaluated on the test set. ResNet152 proved to be the best model among the four models for CVM classification with a weighted κ of 0.826, an average AUC of 0.933 and total accuracy of 67.06%. The F1 score rank for each subgroup was: CS6>CS1>CS4>CS5>CS3>CS2. The area of the third (C3) and fourth (C4) cervical vertebrae were activated when CNNs were assessing the images. Conclusion: CNN models proved to be a convenient, fast and reliable method for CVM analysis. CNN models have the potential to provide automatic auxiliary diagnostic tools in the future.

Summary: Background: Tongue plays an important part in oral and maxillofacial system. Measurement of tongue pressure helps to evaluate the performance of tongue movement.Objectives: To establish a system for measuring tongue pressure against hard palate and to preliminarily explore pressure distribution of individual normal occlusions and the relationship with dental arch form.Methods: A total of 19 volunteers of individual normal occlusions out of 189 dental students met inclusion criteria (nine males, ten females, aged 25.53 ± 0.96 years). A force‐sensing resistor device was used to measure tongue pressure at rest and functional state (swallowing). We observed tongue pressure of four channel (anterior, posterior and lateral sides of hard palate) in sitting, supine position and swallowing. We analysed pressure differences according to gender and explored correlation relationship between tongue pressure and dental arch width and length using 3D digital maxillary image.Results: In rest, tongue pressure against hard palate increased from front to back in both sitting and supine position, without gender differences. When swallowing saliva, the pressure at lateral sides of females was found significantly higher than that of males. Bivariate correlation analysis revealed duration of swallowing was positively correlated with BMI and weight at posterior region and positively correlated with palatal length at anterior palate. The greater the dental arch width, the smaller the pressure of swallowing in the anterior and lateral region.Conclusion: In rest, there was consistent pressure of tongue against hard palate. The pressure increased significantly during swallowing, especially in females. Tongue pressure was related to dental arch length, width, BMI and weight.

Purpose: Microorganisms contribute to the pathogenesis of obstructive sleep apnea (OSA)-associated hypertension (HTN), while more studies focus on intestinal microbiome. However, the relationship between oral microbiota and OSA-associated HTN has yet to be elucidated. This study aimed to identify differences in salivary microbiota between patients with OSA comorbid HTN compared with OSA patients, and furthermore evaluate the relationship between oral microbiome changes and increased blood pressure in patients with OSA. Patients and Methods: This study collected salivary samples from 103 participants, including 27 healthy controls, 27 patients with OSA, 23 patients with HTN, and 26 patients with OSA comorbid HTN, to explore alterations of the oral microbiome using 16S rRNA gene V3-V4 high-throughput sequencing. And ultra-high-performance liquid chromatography was used for metabolomic analysis. Results: Alpha- and beta-diversity analyses revealed a substantial difference in community structure and diversity in patients with OSA comorbid HTN compared with patients with OSA or HTN. The relative abundance of the genus Actinomyces was significantly decreased in patients with HTN compared with healthy controls, and those with OSA concomitant HTN compared with the patients in OSA, but was not significantly different between patients with OSA and healthy controls. Linear discriminant analysis effect size and variance analysis also indicated that the genera Haemophilus, Neisseria, and Lautropia were enriched in HTN. In addition, Oribacterium was an unique taxa in the OSA comorbid HTN group compared with the control group. Metabolomic analysis of saliva identified compounds associated with cardiovascular disease in patients with OSA comorbid HTN.2-hydroxyadenine, was significantly increased in the group of patients with OSA compared with controls, and L-carnitine was significantly decreased in patients with OSA comorbid HTN compared with OSA patients. Conclusion: This study highlighted noninvasive biomarkers for patients with OSA comorbid HTN. As the first study to find alterations of the salivary microbiome in patients with OSA comorbid HTN, it may provide a theoretical foundation for clinical diagnosis and treatment of this condition.