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Gender differences in pain reporting and prevalence have been demonstrated. As gender of examiner also affects reporting of pain on palpation, the aim of this study was to evaluate the effects of examiner gender on palpation performance using three different palpation methods. Examiners of both genders were instructed on the correct technique for each palpation method by either a female or male instructor. The target was to achieve a pressure of 100 kPa, corresponding to the 1 kg of force for muscle palpation described in the diagnostic criteria for temporomandibular disorders (DC/TMD). All examiners performed traditional palpation with the index finger, palpation with a palpometer, and a novel bimanual palpation with visual feedback, in a randomized order. The examiner's gender, and its interaction with the gender of the instructor did not significantly affect magnitude, accuracy, or precision of the pressure applied. The method of palpation was the only factor that significantly impacted all metrics. The palpometer achieved the lowest palpation magnitude (mean pressure applied = 113.7  kPa, 95% CI: 109.8-117.6), the highest accuracy (absolute difference = 15.7  kPa, 95% CI: 12.3-19.1), and the highest precision (mean coefficient of variation = 6.8, 95% CI: 6.0-7.6), followed by bimanual palpation and traditional palpation. The results suggest that gender differences in pain reporting in patients are not likely to be a result of the technical aspects associated with the gender of the examiner. Instead, these differences may be attributed to other factors, such as sociocultural influences.

Objective: The purpose of this randomized, double-blind study was to evaluate the anesthetic efficacy of lidocaine-ketorolac administration by Inferior Alveolar Nerve Block (IANB) in patients with irreversible pulpitis.

Methods: Eighty-eight adult patients received a combination of either one cartridge of “2% lidocaine with 1: 80.000 epinephrine” (Li) plus one cartridge of a mixture of 0.8 mL of the same solution and 1mL ketorolac tromethamine (KT)(30 mg/mL), or one cartridge of Li solution plus one cartridge of a mixture of the same solution and saline. Endodontic access was prepared after fifteen minutes. Anesthetic success was defined as no or mild pain [less than 54 mm on the Heft-Parker visual analog scale (HP-VAS)] during access cavity preparation and initial file insertion. Chi-square test was used for data analysis, and the level of significance was set at 0.05 (P=0.05).

Results: Results showed that the success rates were 34.1% and 27.3% for Li-KT and Li-Saline groups, respectively, with no significant difference between the two groups (P=0.48). However, significant decrease of baseline mean VAS pain score of the participants in both groups was found during access cavity preparation or initial file insertion (P<0.05).Conclusion: Mixed Li-KT solution did not increase the success rate of IANB injection significantly. (EEJ-2019-09-097)

Objective: This article reviews the applications of Finite Element Models (FEMs) in personalized dentistry, focusing on treatment planning, material selection, and CAD-CAM processes. It also discusses the challenges and future directions of using finite element analysis (FEA) in dental care.

Data: This study synthesizes current literature and case studies on FEMs in personalized dentistry, analyzing research articles, clinical reports, and technical papers on the application of FEA in dental biomechanics.

Sources: Sources for this review include peer-reviewed journals, academic publications, clinical case studies, and technical papers on dental biomechanics and finite element analysis. Key databases such as PubMed, Scopus, Embase, and ArXiv were used to identify relevant studies.

Study selection: Studies were selected based on their relevance to the application of FEMs in personalized dentistry. Inclusion criteria were studies that discussed the use of FEA in treatment planning, material selection, and CAD-CAM processes in dentistry. Exclusion criteria included studies that did not focus on personalized dental treatments or did not utilize FEMs as a primary tool.

Conclusions: FEMs are essential for personalized dentistry, offering a versatile platform for in-silico dental biomechanics modeling. They can help predict biomechanical behavior, optimize treatment outcomes, and minimize clinical complications. Despite needing further advancements, FEMs could help significantly enhance treatment precision and efficacy in personalized dental care.

Clinical significance: FEMs in personalized dentistry hold the potential to significantly improve treatment precision and efficacy, optimizing outcomes and reducing complications. Their integration underscores the need for interdisciplinary collaboration and advancements in computational techniques to enhance personalized dental care.