Seminars in Orthodontics最新文献

Orthognathic surgery corrects dentofacial deformities by repositioning maxillary and mandibular bones. This review examined whether orthognathic surgery changes temporomandibular (TM) disk position. Databases searched on November 30, 2023 included Web of Science, PubMed, Scopus, Embase, Cochrane, and Google Scholar. Inclusion criteria were studies of orthognathic surgery in individuals with maxillomandibular deformities reporting on TM disk position. Risk of bias was assessed using Cochrane Risk of Bias 2 and Newcastle-Ottawa scales. From 948 retrieved articles, 31 were included. Bilateral sagittal split osteotomy (BSSO) was the most common mandibular osteotomy technique and largely maintained disk position post-operatively. Intraoral vertical ramus osteotomy (IVRO) appeared to improve disk position, though studied less extensively. Overall, surgery had conflicting effects on disk position; quantitative methods showed little change. Limitations were small sample sizes and lack of standardization in assessing disk position. In conclusion, orthognathic surgery does not consistently alter TM disk position, though IVRO may confer some benefit. Larger, standardized studies are needed to better understand effects on TM joint status.

The maxillofacial region is an extremely important region of the body from birth, which is responsible for various functions such as sucking, swallowing, chewing, breathing and pronunciation. It has a complex structure and involves a variety of biological substances from the organ level to the molecular level. Since olden times, clinicians and basic researchers have been interested in the structural changes that occur when function is impaired, and numerous studies have been conducted. Nonetheless, the opposite direction, i.e., how structural disturbances, or malocclusion in orthodontics, affect function, has been less well understood. This is probably because of the methodological difficulties involved. In this review, we will first summarize the old question of whether dysfunction affects occlusion, focusing on masticatory function, especially jaw function, and then, based on this, we will outline a new concept, the proposition of whether malocclusion affects function, focusing on the "substances" that serve as the interface between structure and function.

Artificial Intelligence based systems are exerting tremendous influence in the way we practice and render care to our patients. Improvements in computing capacities, decreasing costs of computing, availability of data from a wide range of sources, and societal push towards embracing innovations have changed the fundamental landscape of healthcare. Like in all specialties, Orthodontics has witnessed a burgeoning interest in research in the artificial intelligence realm. We undertook this narrative review to examine some of the contemporaneous issues that our specialty is facing with regards to implementing artificial intelligence based systems in our research and clinical practice. We present a high level overview of some common applications of artificial intelligence based systems in the field of Orthodontics and challenges in interpreting the models and implementing them in everyday clinical practice.

The introduction of reporting checklists such as CONSORT aimed to enhance the clarity and transparency of the reporting of Randomised Clinical Trials (RCTs). A benefit of clear reporting is to allow healthcare clinicians to assess both the study quality and trial findings and determine its applicability in the treatment of their patients. Despite this global initiative, the reporting of Randomised Clinical Trials (RCTs) undertaken in both dentistry and orthodontics has been reported to sub-optimal in relation to several domains affecting the validity of the trial. Within the literature the adequacy of the statistical analysis undertaken in a trial has been questioned. The aim of this narrative review is to provide clinicians with an overview of the common statistical errors evident in published orthodontic Clinical Trials and to highlight the potential consequences on the interpretation of the trial findings.

Missing data are a common issue in medical research. We aim to explain in non-technical language the issues and concepts around missing data, as well as discuss common methods for handling missing data. Specifically, our objectives are to answer the following questions: (1) What are missing data and why should we care about them? (2) What are the missingness mechanisms and how do they impact statistical analysis? (3) How can we explore missing values in our datasets? (4) What are ad-hoc methods for dealing with missing values and are they valid? (5) What is multiple imputation? (6) What should we consider when conducting a multiple imputation analysis? (7) Is multiple imputation always needed? (8) How should we report an analysis with missing data? We illustrate discussions with examples from an orthodontic study.

Network meta-analysis has been widely used to address the limitations of traditional pairwise meta-analysis. Network meta-analysis incorporates all available evidence into a general statistical framework for comparing multiple treatments. The original Bayesian approach offers a statistical framework to address heterogeneity in the evidence and complexity in the data structure when clinical trials with more than two treatment groups are included. Alternative frequentist approaches have been developed and implemented in commonly used statistical software. The aim of this article is to provide a non-technical introduction to the statistical models and assumptions of network meta-analysis, such as consistency and transitivity, for the orthodontics and dental research community. An example was used to demonstrate how to conduct a network meta-analysis and how to use GRADE and CINeMA tools for placing confidence in the NMA effect estimates in a network meta-analysis. The statistical theory behind network meta-analysis is complex, so we strongly encourage close collaboration between orthodontists and experienced statisticians when planning and conducting a network meta-analysis. Network meta-analysis has been proven to be a very useful tool for evidence synthesis because it improves the efficiency of comparative effectiveness research and the quality of decision-making.

It is essential to conduct a reliability examination even if the method was considered reliable in the past, as it may not be reliable in a new study conducted by different researchers using different materials. The current article highlights the importance of reliability examination in orthodontic studies and explains which assessment methods are more appropriate than others. Several fallacies in reporting and interpreting reliability are also discussed. In addition, the article presents examples of reliability examination for one-, two-, and three-dimensional data using graphic visualization in a tutorial format.