Prediabetes and poorly controlled type-2 diabetes as risk indicators for peri-implant diseases:A systematic review and meta-analysis.

OBJECTIVE: The study answers the PECO question: "In adults with dental implants (P), do subjects suffering from type-2 diabetes or prediabetes (E) have worse peri-implant conditions (O) than subjects without type-2 diabetes and prediabetes (C)?". Prediabetes (5.7-6.4 % HbA1c), and the different qualities of glycemic control in type-2 diabetes; well-controlled (>8 % HbA1c), and poorly controlled (>8 % HbA1c) individuals; were classified according to the recommendations of the American Diabetes Association. DATA: Predefined search keys were used with search terms including: Dental implant, diabetes mellitus, glycemic control and HbA1c. SOURCES: An electronic search in the MEDLINE, Embase, and Cochrane libraries were conducted without any filters or language restrictions. Additionally, manual search of the reference lists were carried out to identify all relevant articles. STUDY SELECTION: Eligibility criteria were cohort, case-control and cross-sectional studies that answerd our PECO question with at least 1 year of follow-up. From a total of 2660 records, 35 articles (1761 individuals) were included in the analysis. Meta-analytic difference in means for crestal bone loss was 1.2 mm [95 % CI=0.4; 2.1] in patients with prediabetes, 1.8 mm [CI=1.0; 2.7] in poorly controlled patients, whereas 0.4 mm [CI=-0.3; 1.1] in well-controlled individuals. Meta-regression showed that 1 % increase in HbA1c increased crestal bone loss by 0.24 mm. CONCLUSIONS: Within the limitations of the study, patients with poorly controlled type-2 diabetes or prediabetes may have worse peri-implant conditions compared to patients without diabetes and well-controlled type-2 diabetes. Well-controlled type-2 diabetes is not a risk indicator for peri-implant diseases. CLINICAL SIGNIFICANCE: Clinicians should measure blood HbA1c levels when planning implant-supported restorations, thus patients with undiagnosed or poorly controlled type-2 diabetes can be identified, that allows for glycemic level adjustment prior to dental implant surgery, ensuring peri-implant health. PROTOCOL REGISTRATION NUMBER: (CRD42022375263).

Advancing accuracy in guided implant placement: A comprehensive meta-analysis: Meta-Analysis evaluation of the accuracy of available implant placement Methods.

OBJECTIVES: This meta-analysis aimed to determine the accuracy of currently available computer-assisted implant surgery (CAIS) modalities under in vitro conditions and investigate whether these novel techniques can achieve clinically acceptable accuracy. DATA: In vitro studies comparing the postoperative implant position with the preoperative plan were included. Risk of bias was assessed using the Quality Assessment Tool For In Vitro Studies (QUIN Tool) and a sensitivity analysis was conducted using funnel plots. SOURCES: A systematic search was performed on April 18, 2023, using the following three databases: MEDLINE (via PubMed), EMBASE, and Cochrane Central Register of Controlled Trials. No filters or restrictions were applied during the search. RESULTS: A total of 5,894 studies were included following study selection. Robotic- and static CAIS (sCAIS) had the most accurate and clinically acceptable outcomes. sCAIS was further divided according to the guidance level. Among the sCAIS groups, fully guided implant placement had the greatest accuracy. Augmented reality-based CAIS (AR-based CAIS) had clinically acceptable results for all the outcomes except for apical global deviation. Dynamic CAIS (dCAIS) demonstrated clinically safe results, except for horizontal apical deviation. Freehand implant placement was associated with the greatest number of errors. CONCLUSIONS: Fully guided sCAIS demonstrated the most predictable outcomes, whereas freehand sCAIS demonstrated the lowest accuracy. AR-based and robotic CAIS may be promising alternatives. CLINICAL SIGNIFICANCE: To our knowledge, this is the first meta-analysis to evaluate the accuracy of robotic CAIS and investigate the accuracy of various CAIS modalities.

Teledentistry: A Future Solution in the Diagnosis of Oral Lesions: Diagnostic Meta-Analysis and Systematic Review.

Introduction: Teledentistry (TD) can offer a wide range of possibilities in the field of oral medicine. Oral potentially malignant disorders (OPMDs) are hard to detect, and even harder to diagnose correctly. With the help of TD, OPMDs can be detected and diagnosed by a remote specialist. Our aim was to investigate whether TD could provide a reliable diagnostic method compared with clinical oral examination (COE) in the diagnosis of OPMDs. Methods: A systematic search was conducted in three databases (Medline, EMBASE, CENTRAL) until November 2021. We included studies that compared telediagnosis and COE, both made by experts. Pooled specificity and sensitivity were calculated and visualized on a two-dimensional plot. Risk of bias was assessed using the QUADAS-2 tool, and the level of evidence is shown with the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) tool. Results: Of the 7,608 studies, 13 were included in the qualitative and 9 in the quantitative synthesis. Using TD tools in the detection of oral lesions (OLs) showed high specificity (0.92 confidence interval [95% CI] = 0.59-0.99) and sensitivity (0.93 95% CI = 0.17-1.00). In the differential diagnosis of lesions, we found high sensitivity and specificity (0.942 95% CI = 0.826-0.982 and 0.982 95% CI = 0.913-0.997), respectively. We summarized the available data on time-effectiveness, screening person, referral decision, and technical settings. Conclusion: Detecting OLs with TD tools might lead to earlier diagnosis, treatment, and stricter follow-up of OPMD. TD may offer a great substitution for COE in the diagnosis of OLs, and thus, fewer referrals could be made to special care, resulting in a greater number of treated OPMDs.

Use of collaborative learning as atool to evaluate syndromic craniofacial anomalies / Uso da aprendizagem colaborativa como ferramenta para avaliar anomalias craniofaciais sindrômicas

Almost 30% of oral cleftsare associated with other structural abnormalities.However, little is known on orofacial characteristics related tothese cases since they are not systematically reported. To close this gap, we developed a collaborative learning approach supported by an interprofessional team aiming to systematicallydescribe oral findings and impactthe training of future professionals that hopefully will incorporate these descriptionsintotheir clinical practice. The methodological proposal consisted of small group sessions focusing on a particular syndrome or group of syndromes followed by examiningpatients with those conditions. Twenty cases were examined and studied over one semester andaset of conditions to be identified in the orofacial regionwasdefined. Here, we present a guideline that we suggest that dentists and dental institutions use. We also present the advantages of using collaborative learning as a tool in the training of the clinician (AU).

Quase 30% das fissuras orais estão associadas a outras anormalidades estruturais. No entanto, pouco se sabe sobre as características orofaciais relacionadas a esses casos, uma vez que não são relatados de forma sistemática. Para fechar essa lacuna, desenvolvemos uma abordagem de aprendizagem colaborativa apoiada por uma equipe interprofissional com o objetivo de descrever sistematicamente os achados orais e impactar o treinamento de futuros profissionais que, esperançosamente, irão incorporar essas descrições em sua prática clínica. A proposta metodológica consistia em sessões de pequenos grupos enfocando uma determinada síndrome ou grupo de síndromes seguidas de exame de pacientes com essas condições. Vinte casos foram examinados e estudados ao longo de um semestre e foi definido um conjunto de condições a serem identificadas na região orofacial. Aqui, apresentamos uma diretriz que sugerimos que os dentistas e instituições odontológicas utilizem. Também apresentamos as vantagens de usar a aprendizagem colaborativa como uma ferramenta no treinamento do clínico (AU).