Prevalence of malocclusion in Turkish children and adolescents: A systematic review and meta-analysis

OBJECTIVES

The aim of this article is to establish a comprehensive nationwide prevalence of malocclusion traits on the sagittal, vertical, and transverse planes of space in the Turkish population.

MATERIAL AND METHODS

A systematic search of PubMed, Scopus, and Web of Science was supplemented by manual searches of Google Scholar and the reference lists of included studies. Original Turkish health studies of any age were included. Strengthening the Reporting of Observational Studies in Epidemiology assessed study quality and bias (STROBE). Sagittal, vertical, and transverse malocclusion features were retrieved and gathered.

RESULTS

Eleven studies were selected from 434 titles. Two studies showed a high risk of bias, eight low and one moderate. Thirteen thousand two hundred seventy-one individuals were investigated from early childhood to late adulthood. Most studies were sampled from universities and dental (nonorthodontic) clinics. The pooled malocclusion prevalence was 56% for Class I (95% confidence interval (CI): 44-68%), 31% for Class II (CI: 6-42%), and 11% for Class III (CI: 21-37%). The other common types of malocclusions were crowding (41%, CI: 18-65%), overjet (34%, CI: 21-50%), negative overjet (13%, CI: 7-20%), and crossbite (11%, CI: 7-15%). Additionally, there was no significant difference in Class I (relative risk [RR] = 1.00, [0.96-1.05]), Class II ([RR] = 0.97, [0.92-1.03]), and Class III ([RR] = 1.08, [0.96-1.225]) malocclusion by gender.

CONCLUSIONS

This study showed Class I malocclusion has a high prevalence among the Turkish population followed by Class II and Class III malocclusions. In addition, crowding and overjet were the most prevalent malocclusions among Turkish individuals. There were no significant differences in the prevalence of malocclusions between males and females.

Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic review and meta-analysis

Introduction

Cephalometry is the study of skull measurements for clinical evaluation, diagnosis, and surgical planning. Machine learning (ML) algorithms have been used to accurately identify cephalometric landmarks and detect irregularities related to orthodontics and dentistry. ML-based cephalometric imaging reduces errors, improves accuracy, and saves time.

Method

In this study, we conducted a meta-analysis and systematic review to evaluate the accuracy of ML software for detecting and predicting anatomical landmarks on two-dimensional (2D) lateral cephalometric images. The meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for selecting and screening research articles. The eligibility criteria were established based on the diagnostic accuracy and prediction of ML combined with 2D lateral cephalometric imagery. The search was conducted among English articles in five databases, and data were managed using Review Manager software (v. 5.0). Quality assessment was performed using the diagnostic accuracy studies (QUADAS-2) tool.

Result

Summary measurements included the mean departure from the 1-4-mm threshold or the percentage of landmarks identified within this threshold with a 95% confidence interval (CI). This meta-analysis included 21 of 577 articles initially collected on the accuracy of ML algorithms for detecting and predicting anatomical landmarks. The studies were conducted in various regions of the world, and 20 of the studies employed convolutional neural networks (CNNs) for detecting cephalometric landmarks. The pooled successful detection rates for the 1-mm, 2-mm, 2.5-mm, 3-mm, and 4-mm ranges were 65%, 81%, 86%, 91%, and 96%, respectively. Heterogeneity was determined using the random effect model.

Conclusion

In conclusion, ML has shown promise for landmark detection in 2D cephalometric imagery, although the accuracy has varied among studies and clinicians. Consequently, more research is required to determine its effectiveness and reliability in clinical settings.

Onset of Mucormycosis in Patients with COVID-19: A Systematic Review on Patients' Characteristics

Mucormycosis has a significant impact on patients' standard of living and, therefore, a high clinical suspicion, prediagnosis, and rapid treatment are critical in easing patients' suffering and fast recovery. Our focus is to conduct an organized review based on various variables on the patients' characteristics having mucormycosis in severe novel coronavirus disease 2019 (COVID-19). We examined Embase, PubMed-Medline, LitCovid, Web of Science, Scopus, and the reference lists of included case reports up to September 20, 2021, using the Medical Subject Heading (MeSH) phrases and other keywords related to this topic. Subsequently, we investigated associated comorbidities, patient characteristics, position of mucormycosis, steroids use, body involvements, and outcomes. Overall, 77 studies were conducted and among these, 72 studies mentioned that the patients' age to be 48.13±14.33 (mean±standard deviation [SD]) years. Diabetes mellitus (DM) was reported in 77.9% (n=60) of cases. Studies showed that central nervous system (CNS) and bone involvement were reported in 62.3 (n=48) and 53.2% (n=41), respectively. More fatalities were observed in patients with mucormycosis with the active form of COVID-19. Also, men infected with mucormycosis significantly affected by COVID-19. In the end, mortality was higher in males with mucormycosis. As a result, a solid investigation into the root cause of mucormycosis, especially in COVID-19, should be included in the study plan. If the patient is COVID-19-positive and immunosuppressed, this opportunistic pathogen diagnostic test should not be overlooked.

Seroepidemiological Analysis of Leptospiral infection using MAT in Stray Dogs in Alborz, Iran

Leptospirosis is a zoonotic disease with global importance, and the animals are the source of transmission of this disease through shedding in their urine. Accordingly, it is essential to conduct epidemiological studies of leptospirosis in order to diagnose this disease in dogs and reduce the risk of transmission to humans. This study aimed to perform a seroepidemiological analysis of Leptospiral infection in stray dogs in Alborz, Iran, using the Microscopic Agglutination Test (MAT). In total, 110 blood samples were collected from stray dogs to detect the antibodies against leptospira interrogans serovarsby the MAT. The prevalence rate of positive MAT tests in stray dogs was estimated at 21.84%. The following protocol confirmed that the most common titers were 1:200 (50%) and 1:400 (25%). In addition, the most prevalent Leptospira serovars were L. Canicola (33.33%), and the lowest belonged to L. Pomona (4.1%). Moreover, no significant difference was observed between the age and gender of the dogs regarding their MAT titer (P>0.05). The results also showed a high prevalence of leptospirosis in stray dogs of Koohsar in Alborz province, Iran. Since Leptospirosis is a zoonosis disease, it should be studied continuously in humans and animals, especially dogs.

3D and 4D printing in dentistry and maxillofacial surgery: Printing techniques, materials, and applications

3D and 4D printing are cutting-edge technologies for precise and expedited manufacturing of objects ranging from plastic to metal. Recent advances in 3D and 4D printing technologies in dentistry and maxillofacial surgery enable dentists to custom design and print surgical drill guides, temporary and permanent crowns and bridges, orthodontic appliances and orthotics, implants, mouthguards for drug delivery. In the present review, different 3D printing technologies available for use in dentistry are highlighted together with a critique on the materials available for printing. Recent reports of the application of these printed platformed are highlighted to enable readers appreciate the progress in 3D/4D printing in dentistry.