Introduction: People with special care needs often face significant barriers in accessing dental care due to physical and cognitive limitations, leading to high rates of dental issues like caries. Despite the growing recognition of these challenges, unmet dental care needs remain prevalent. This review aims to explore the global landscape of special care dentistry to identify gaps and opportunities for improving dental services for this population. Methodology: A systematic search was conducted across three online databases—PubMed, Embase, and Scopus—to identify relevant articles from their inception through May 2024. Reference lists of the selected studies were also screened for additional sources. A thematic synthesis approach was applied to derive both descriptive and analytical themes. The scoping review was guided by the Arksey and O’Malley framework to examine the scope and nature of studies and documents related to dental care for individuals with special care needs. Furthermore, a Google search was performed to include accessible theses and official government documents from various countries. Results: A total of 49 studies from 11 countries were reviewed, all centered on providing dental care for people with special needs. The analysis revealed three main themes: Human resources, care delivery model, and management. Within these, nine subthemes emerged: Mid-level oral care providers, dentists, special care dentistry as a specialty, tele-dentistry, mobile dentistry, hospital care, levels of healthcare provision, financial support, and education. These themes and subthemes highlight essential areas for enhancing services for those people. Conclusions: A holistic approach is essential to enhance dental care for people with special needs. Critical strategies, including the involvement of mid-level oral care providers, the adoption of tele-dentistry and mobile units, and the availability of hospital-based services for complex cases, are crucial. To truly transform care for those people, each country must adapt these strategies to its specific context, aligning resources and policies to create an inclusive, accessible, and effective system.

Objectives: To evaluate and compare the rates of antibiotic prescribing by dental practitioners across the constituent countries of the United Kingdom between March 2020 and August 2023 and to estimate the total ‘excess’ prescribing that occurred during this interval beyond the rates predicted based upon trends between March 2016 and February 2020.Methods: Retrospective pharmacoepidemiological study of dental practitioners' antibiotic prescribing, by secondary analysis of population‐level National Health Service dispensing data from England, Scotland, Wales and Health and Social Care dispensing data from Northern Ireland.Results: Effective August 2023, the antibiotic items dispensed rate for each country remained in excess of that predicted based upon pre‐pandemic trends. Between March 2020 and August 2023, those rates were 175.6, 227.2, 195.0 and 321.8 antibiotic items per 1000 population for England, Scotland, Wales and Northern Ireland, respectively. Those represented estimated total ‘excesses’ of 27.7% (95% confidence limit [CL], 14.8, 43.7), 43.3% (95% CL, 29.9, 60.0), 33.2% (95% CL, 20.4, 49.0) and 42.9% (95% CL, 27.6, 62.3). Pairwise comparisons showed statistically significant differences between England and Scotland, England and Northern Ireland, and Wales and Northern Ireland (p < 0.001), Scotland and Wales (p = 0.001), and Scotland and Northern Ireland (p = 0.009). There was no statistically significant difference between England and Wales.Conclusions: With shared prescribing guidelines and a single professional regulatory framework, it was unsurprising that similar antibiotic prescribing trends were found across the United Kingdom. Further research is required to investigate the reasons for the differences.

Data sources: Three databases (MEDLINE, Cochrane Library, and Scopus) were searched in December 2021 for 16 Randomised Clinical Trials (RCTs). Study selection: Three reviewers reviewed the articles on oral antibiotic prophylaxis (ABP) for the prevention of surgical site infection (SSI) and dry socket (DS) after lower third molar (L3M) extraction using the PICO framework. From 1999 to 2021, RCTs involving healthy patients undergoing L3M extraction with ABP, placebo, or no therapy were included. Adverse effects (AEs) associated with antibiotic usage, along with the main outcomes (DS and SSI), were also documented. Data extraction and synthesis: Three independent investigators selected articles based on pre-established inclusion criteria, with any disagreements resolved by consensus or additional researchers. PRISMA guidelines were followed, involving initial title and abstract screening, followed by full-text evaluation. Exclusion reasons were documented, and the most recent report was included when multiple reports on the same patients were found, with no language restrictions applied. Two investigators evaluated studies quality and quality of evidence respectively using the Cochrane Collaboration tool and GRADEpro GDT. They independently extracted data, focusing on the type of extraction and the number of extracted L3M. They also detailed the use of antibiotics, including dosage, dosage regimen, timing, and duration. Among 16 articles, 15 used a parallel arm design, while one used a crossover design. The antibiotics studied included Amoxicillin+Clavulanic acid (7 articles), Amoxicillin (6), Metronidazole (2), Azithromycin (1), and Clindamycin (2), all compared with no treatment or placebo. A pairwise meta-analysis was used to combine studies with equivalent treatment (direct estimation), and a network meta-analysis compared outcome variables across different treatments (indirect comparison). Results: Two included articles had a low risk of bias and the level of evidence was low according to GRADE. Pooled results supported the use of antibiotics to reduce DS and SSI following L3M extraction with a number needed to treat 25 and 18, respectively. Conclusions: Despite the fact that ABP reduces the risk of DS and SSI, it is recommended to consider systemic conditions and individual patient risk factors before prescribing antibiotics, due to global health threat.

Introduction Electronic Health Records (EHRs) are vital repositories of patient information for medical research, but the prevalence of missing data presents an obstacle to the validity and reliability of research. This study aimed to review and category ise methods for handling missing data in EHRs, to help researchers better understand and address the challenges related to missing data in EHRs. Materials and Methods This study employed scoping review methodology. Through systematic searches on EMBASE up to October 2023, including review articles and original studies, relevant literature was identified. After removing duplicates, titles and abstracts were screened against inclusion criteria, followed by full-text assessment. Additional manual searches and reference list screenings were conducted. Data extraction focused on imputation techniques, dataset characteristics, assumptions about missing data, and article types. Additionally, we explored the availability of code within widely used software applications. Results We reviewed 101 articles, with two exclusions as duplicates. Of the 99 remaining documents, 21 underwent full-text screening, with nine deemed eligible for data extraction. These articles introduced 31 imputation approaches classified into ten distinct methods, ranging from simple techniques like Complete Case Analysis to more complex methods like Multiple Imputation, Maximum Likelihood, and Expectation-Maximization algorithm. Additionally, machine learning methods were explored. The different imputation methods, present varying reliability. We identified a total of 32 packages across the four software platforms (R, Python, SAS, and Stata) for imputation methods. However, it’s significant that machine learning methods for imputation were not found in specific packages for SAS and Stata. Out of the 9 imputation methods we investigated, package implementations were available for 7 methods in all four software platforms. Conclusions Several methods to handle missing data in EHRs are available. These methods range in complexity and make different assumptions about the missing data mechanisms. Knowledge gaps remain, notably in handling non-monotone missing data patterns and implementing imputation methods in real-world healthcare settings under the Missing Not at Random assumption. Future research should prioritize refining and directly comparing existing methods.

Background & Aim : Down syndrome is a common genetic disorder in which, due to the high prevalence of developmental, anatomical, and functional disorders associated with the oral cavity, it causes problems in maintaining oral hygiene. This study aimed to investigate the barriers to students' oral health with Down syndrome from the ...