The evidence based on PSG was not as conclusive as the studies that used surveys and clinical exam to diagnosis bruxism, when bruxism was related to TMD. Sleep bruxism could be associated with myofascial pain, arthralgia and joint pathology as disc displacement and joint noises. Although the evidence at present is inconclusive and does not provide information according to the type of bruxism (bruxism sleep and wakefulness), it is possible to suggest that bruxism would be associated with TMD.

Because of the heterogeneity of the design and methodology and the low quality of the articles reviewed, it is not possible to establish an association between CR-ICP discrepancy and TMD. The consequence of CR-ICP discrepancy on the presence of TMD requires further research, well-defined and validated diagnostic criteria and rigorous scientific methodologies. Longitudinal studies are needed to identify CR-ICP discrepancy as a possible risk factor for the presence of TMD.

Objective: The aim of this study was to evaluate the amount of micromotion of dental implants under immediate loading supported by Titanium (Ti) and Cobalt-Chrome (Co-Cr) superstructures. Material and methods:A model of tridimensional half-edentulous maxilla with three dental implants was made using the Finite Element Analysis (FEA). Two standard and one zygomatic implants were connected to a superstructure with an elliptic section of 6x 3 mm (mm). Two study models were established. Model A: Titanium (Ti) alloy superstructure; Model B: Cobalt-Chrome (Co-Cr) alloy superstructure. To simulate an immediate-loading situation, a friction coefficient of 0.71 was applied between the implant and the bone surface. An axial load of 252.04 [N] was applied on standard and zygomatic implants.Results: The Micromotion of dental implants was similar in both superstructure situations. The amount of micromotion was slightly higher in B1 and B3 models (Co-Cr alloy-superstructure) compared with A1 and A3 models (Titanium alloy superstructure). The micromotion values in two groups were greater than 150 μm in the incisive region (standard implant) and molar region (zygomatic). In general, the micromotion was higher on the implant that received the load with respect to the other implants.The greater difference was observed when the load was applied on the standard implant A1 (Model A1 = 189.12 μm) compared with standard implant B1(Model B1 = 263.25 μm).Conclusions: Within the limits of present study, all implants on different load application points showed micromotion; in general, the amount of micromotion was slightly higher in the implants connected with Co-Cr alloy superstructure.

The quality of evidence available is insufficient to establish definitive conclusions, since the studies were very heterogeneous and presented a high risk of bias. However, it is suggested that the use of orthopaedic appliances to correct class II and III malocclusion in growing patients would not be considered as a risk factor for the development of TMD. High-quality RCTs are required to draw any definitive conclusions.

Objective To evaluate the validity of craniofacial growth predictors in class II and III malocclusion. Material and methods An electronic search was conducted until August 2020 in PubMed, Cochrane Library, Embase, EBSCOhost, ScienceDirect, Scopus, Bireme, Lilacs and Scielo including all languages. The articles were selected and analyzed by two authors independently and the selected studies was assessed using the 14‐item Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS‐2). The quality of evidence and strength of recommendation was assessed by the GRADE tool. Results In a selection process of two phases, 10 articles were included. The studies were grouped according to malocclusion growth predictor in (1) class II (n = 4); (2) class III (n = 5) and (3) class II and III (n = 1). The predictors were mainly based on data extracted from cephalometries and characterized by: equations, structural analysis, techniques and computer programs among others. The analyzed studies were methodologically heterogeneous and had low to moderate quality. For class II malocclusion, the predictors proposed in the studies with the best methodological quality were based on mathematical models and the Fishman system of maturation assessment. For class III malocclusion, the Fishman system could provide adequate growth prediction for short‐ and long‐term. Conclusions Because of the heterogeneity of the design, methodology and the quality of the articles reviewed, it is not possible to establish only a growth prediction system for class II and III malocclusion. High‐quality cohort studies are needed, well defined data extraction from cephalometries, radiographies and clinical characteristics are required to design a reliable predictor.