BackgroundThis study aimed to explore the association between feeding habits, non-nutritive sucking habits, and malocclusions in deciduous dentition.MethodsA cross-sectional observational survey was carried out in 275 children aged 3 to 6 years and included clinical evaluations of malocclusions and structured interviews. Statistical significance for the association between feeding habits and the development of malocclusion was determined using chi-square and Fisher’s exact tests. In addition, odds ratio (OR) calculations were used for intergroup comparisons. Controlling for confounders was adjusted by excluding children with non-nutritive sucking habits.ResultsThe results indicated that there were no significant relationships between exclusive breastfeeding or bottlefeeding and the presence of any type of malocclusion (p > 0.05). There was also no significant association between breastfeeding or bottlefeeding duration and malocclusion (p > 0.05). In addition, it was observed that exclusive breastfeeding had a protective effect and diminished the risk of acquiring non-nutritive sucking habits (p = 0.001).ConclusionsThere was no association between feeding habits and malocclusions in the deciduous dentition in this sample of children. Exclusive breastfeeding reduced the risk of acquiring non-nutritive sucking habits.

Objectives: To evaluate the prevalence of dental agenesis and its possible association with other developmental dental anomalies and systemic entities. Setting and Sample Population: Descriptive transversal study, for which 1518 clinical records, of patients visited by the Odontological Service of the Primary Health Centre of Cassà de la Selva (Girona-Spain) between December 2002 and February 2006 were reviewed. The data were recorded in relation to the oral and dental anomalies and the associated systemic entities, between the ones referred as concomitant in literature. Results: Values of 9.48% (7.25% excluding the third molars) for dental agenesis and 0.39% for oligodontia were obtained. The presence of dental agenesis concomitant with some other forms of oral and dental anomalies was observed. Attention must be drawn to the fact that a greater number of concomitant systemic entities were observed in those patients that presented a severe phenotypical pattern of dental agenesis. Conclusions: The results of the present study do not differ from the ones reported in studies of similar characteristics among Occidental and Spanish populations. The relationship observed between certain systemic entities and developmental dental anomalies suggest a possible common genetic etiology.

Varying the wavelength with a reasonable dose in the target zone leads to obtaining the desired biological effect and achieving a reduction of the orthodontic treatment time, although there are studies that do not demonstrate any benefit according to their values.

Objective This scoping review aims to determine the applications of Artificial Intelligence (AI) that are extensively employed in the field of Orthodontics, to evaluate its benefits, and to discuss its potential implications in this speciality. Recent decades have witnessed enormous changes in our profession. The arrival of new and more aesthetic options in orthodontic treatment, the transition to a fully digital workflow, the emergence of temporary anchorage devices and new imaging methods all provide both patients and professionals with a new focus in orthodontic care. Materials and methods This review was performed following the Preferred Reporting Items for Systematic reviews and Meta‐Analyses extension for Scoping Reviews (PRISMA‐ScR) guidelines. The electronic literature search was performed through MEDLINE/PubMed, Scopus, Web of Science, Cochrane and IEEE Xplore databases with a 11‐year time restriction: January 2010 till March 2021. No additional manual searches were performed. Results The electronic literature search initially returned 311 records, and 115 after removing duplicate references. Finally, the application of the inclusion criteria resulted in 17 eligible publications in the qualitative synthesis review. Conclusion The analysed studies demonstrated that Convolution Neural Networks can be used for the automatic detection of anatomical reference points on radiological images. In the growth and development research area, the Cervical Vertebral Maturation stage can be determined using an Artificial Neural Network model and obtain the same results as expert human observers. AI technology can also improve the diagnostic accuracy for orthodontic treatments, thereby helping the orthodontist work more accurately and efficiently.