Impulse Oscillometry Combined to FeNO in Relation to Asthma Control Among Preschool Children.

Objective: We aimed to observe and analyze the differences in impulse oscillometry (IOS) and fractional expiratory nitric oxide (FeNO) in relation to asthma control among preschool children, and to explore the predictive value of IOS combined with FeNO for uncontrolled asthma. Methods: This study enrolled 171 preschool children with asthma and 30 healthy preschool children between June 2022 and June 2023. We categorized the asthmatic children as having controlled asthma (n=85) and uncontrolled asthma (n=86) after a 3-month follow-up. IOS and FeNO were collected on the first visit at baseline. Differences in metrics were compared between controlled asthma, uncontrolled asthma and healthy control groups. The area under the receiver operating characteristic curve (AUROC) was utilized to explore the discriminative ability of IOS and FeNO, alone or in combination, against uncontrolled asthma. Results: Compared to the controlled asthma group, the IOS values of R5, X5, R5-R20, and Fres were significantly higher in the uncontrolled asthma group, except for R20. R5 and R5-R20 had the highest area under the curve (AUC), which could reach 0.74 (95% CI 0.66-0.82) and 0.72 (95% CI 0.64-0.80). R20 had the lowest AUC of 0.59. The AUC for FeNO alone was 0.88 (95% CI 0.84-0.93) with a cutoff value of 17.50 ppb, sensitivity and specificity of 0.73 and 0.89. The AUCs of all IOS metrics combined with FeNO were significantly higher, with the highest AUC of 0.92 (95% CI 0.87-0.96) for R5-R20+FeNO, and with a sensitivity and specificity of 0.88 and 0.84. Conclusion: There were significant differences in IOS and FeNO in relation to asthma control among preschooler children. FeNO might be the best predictor of asthma control, and adding any of IOS metrics increased moderately the predictive value.

Beyond the Bite: Exploring Mental Health of Dental Faculty in Pakistan- a multi-institutional study.

INTRODUCTION: Mental health issues are being reported increasingly amongst healthcare staff and students globally. The aim of this study was to investigate the frequency of common mental health issues amongst dental faculty members at multiple institutions in Pakistan. METHODS: Following approval from the institutional ethics review board, dental faculty members at 14 dental institutions were invited to participate in an online survey based on globally validated scales for mental health problems including the Patient Health Questionnaire (PHQ-9), and the Depression, Anxiety, and Stress Scale (DASS-21). Two open-ended questions were included in the survey to identify perceived factors contributing to poor mental health and recommendations for improving institutional support. RESULTS: A total of 200 faculty members out of provided their responses to the survey questionnaire but complete responses were provided by 183 participants which included 120 (65.57%) females, and 63 (34.43%) males. The total number of faculty members at the participating institutions was 426 and 183 responses translated into an overall response rate of 43%. Most participants were in the 31-40 years age-group (n = 81, 44.26%) followed by 25-30 year (n = 51, 22.87%) and 41-50 years (n = 40, 21.86%). The mean score on PHQ-9 was 6.51 (SD ± 5.4) while the mean DASS-21 score was 13.04 (SD ± 10.95). PHQ-9 Depression, and DASS-21 Depression, Anxiety, and Stress scores were all significantly positively correlated for the whole sample, and within each subgroup of each demographic factor. Job-related workload, lack of institutional support, financial limitations, and poor work life balance were identified as the main factors contributing adversely to the mental health of the participants. DISCUSSION: This study provides useful insights into the scale of mental health status amongst dental faculty members at 14 institutions in Pakistan. Underlying factors affecting the mental health of faculty members adversely were identified and recommendations are provided to address these challenges.

Evaluation of mental health of students in healthcare education programs at Qatar University.

Introduction: Mental health issues among undergraduate health-care students are a growing concern. This research aims to explore the frequency of mental health issues among health-care students in medicine, dentistry, pharmacy, nutrition, biomedical sciences, nursing, and public health at Qatar University. Methods: Ethics approval was obtained from the institutional review board. A total of 1,378 health-care students were invited to participate. Data were collected online using two validated questionnaires including the Patient Health Questionnaire (PHQ-9) to assess symptoms of depression, and Depression, Anxiety, and Stress Scale (DASS-21), and two open-ended questions investigating risk factors and recommendations for enhancing institutional support. Results: A total of 270 health-care students completed the survey; 227 female, and 43 male students. According to PHQ-9 cut-off values, 37.7% of students had mild depression symptoms, 25.5% moderate, 14.8% moderately severe and 10% severe symptoms. DASS-21 responses revealed 34.7% displayed severe to extremely severe anxiety symptoms, 15.4% severe to extremely severe stress symptoms and 21% severe to extremely severe depression symptoms. Students aged 18-21 years had significantly higher depression (p=0.03) and stress scores (p=0.05). Qatari students had significantly higher anxiety scores (p=0.05). Responses to open-ended questions were categorized into sub-themes and grouped together into broader themes. Most students reported exam stress and workload as key factors contributing to their negative mental health. Participants' recommendations included reducing academic workload through better curricular planning, providing training to faculty to better support students with mental health issues, and improving mental health services. Conclusion: This study showed a significant percentage of respondents reported symptoms of stress, anxiety, and depression during undergraduate studies. Participants represent the future healthcare force for the country and there is a need to identify and support students with mental health issues through close monitoring, and work with all stakeholders to improve student support services.

Designing Entrustable Professional Activities for Treatment Planning of Oral Cancer by Maxillofacial Surgery Residents: A Modified Delphi Study.

Purpose: The aim of this study was to develop a competency framework based on entrustable professional activities (EPAs) in oral cancer management by postgraduate trainees in oral and maxillofacial surgery through expert consensus. Materials and Methods: The study design was based on a modified Delphi technique and involved iterative online surveys with two rounds of data collection and analysis. Initial development of the questionnaire identified five EPAs based on 42 competencies along with supervision level and assessment strategies. The first Delphi round involved administration of the survey questionnaire online to maxillofacial surgeons meeting the inclusion criteria for experts. Consensus was achieved on five EPAs and 36 competencies (≥80% response rate). Six competencies were rephrased and sent again in the Round 2 questionnaire to achieve a consensus. Results: A total of 45 experts participated in Round 1 followed by input from 27 experts in Round 2 of the Delphi panel. Following two iterative rounds of online surveys and feedback, expert consensus was achieved to develop an EPA framework in five EPA domains focused on the management of oral cancer by postgraduate trainees in maxillofacial surgery including 38 specific competencies, supervision level, and assessment strategies. High content validity of the study was established through a comprehensive literature search, and expert feedback was evidenced by an excellent response rate (93.34%, and 64.28%) and a stringent criteria of response agreement amongst experts (≥80%). Conclusion: In conclusion, this study employed expert consensus to identify five EPAs with 38 competencies along with the required supervision level of postgraduate maxillofacial trainees for the management of oral cancer. This EPA framework provides a roadmap for training supervisors to map the learning outcomes in oral oncology for postgraduate trainees in oral and maxillofacial surgery.

Artificial Intelligence and Deep Learning in Revolutionizing Brain Tumor Diagnosis and Treatment: A Narrative Review.

The emergence of artificial intelligence (AI) in the medical field holds promise in improving medical management, particularly in personalized strategies for the diagnosis and treatment of brain tumors. However, integrating AI into clinical practice has proven to be a challenge. Deep learning (DL) is very convenient for extracting relevant information from large amounts of data that has increased in medical history and imaging records, which shortens diagnosis time, that would otherwise overwhelm manual methods. In addition, DL aids in automated tumor segmentation, classification, and diagnosis. DL models such as the Brain Tumor Classification Model and the Inception-Resnet V2, or hybrid techniques that enhance these functions and combine DL networks with support vector machine and k-nearest neighbors, identify tumor phenotypes and brain metastases, allowing real-time decision-making and enhancing preoperative planning. AI algorithms and DL development facilitate radiological diagnostics such as computed tomography, positron emission tomography scans, and magnetic resonance imaging (MRI) by integrating two-dimensional and three-dimensional MRI using DenseNet and 3D convolutional neural network architectures, which enable precise tumor delineation. DL offers benefits in neuro-interventional procedures, and the shift toward computer-assisted interventions acknowledges the need for more accurate and efficient image analysis methods. Further research is needed to realize the potential impact of DL in improving these outcomes.

Case-based learning in undergraduate orthodontic education: A cross sectional study.

Introduction: Student centric learning approaches have been reported to be effective in introducing higher order cognitive skills required by the health professionals. However, learners' perceptions must be constructively aligned with new learning interventions to achieve a positive impact on their learning. The aim of this study was to explore the learning experiences of undergraduate dental students with case-based learning in orthodontics. Methods: A case-based learning model was introduced on orthodontic diagnosis and treatment planning for final year students on a Bachelor of Dentistry programme toward the end of their academic year. A survey was conducted to explore the perceptions and experiences of the participants. The research instrument was based on a previously validated questionnaire and included information on demographics and consisted of 12 items aimed at evaluating the benefits and challenges of cased based learning. Results: All 67 students in the final-year cohort participated in study, yielding a response rate of 100 percent. Participants across the board perceived CBL to be an effective strategy to learn the subject content and helpful in improving the students' skills in orthodontic diagnosis, treatment planning and team-working. CBL did not pose any significant challenges or barriers to student learning. Conclusion: Participants reported high acceptance of CBL in orthodontic teaching and learning and a positive impact on their educational experiences. CBL was perceived to be an appropriate strategy to enhance the diagnostic, treatment planning and team-working skills of dental students.

Three layered sparse dictionary learning algorithm for enhancing the subject wise segregation of brain networks.

Independent component analysis (ICA) and dictionary learning (DL) are the most successful blind source separation (BSS) methods for functional magnetic resonance imaging (fMRI) data analysis. However, ICA to higher and DL to lower extent may suffer from performance degradation by the presence of anomalous observations in the recovered time courses (TCs) and high overlaps among spatial maps (SMs). This paper addressed both problems using a novel three-layered sparse DL (TLSDL) algorithm that incorporated prior information in the dictionary update process and recovered full-rank outlier-free TCs from highly corrupted measurements. The associated sequential DL model involved factorizing each subject's data into a multi-subject (MS) dictionary and MS sparse code while imposing a low-rank and a sparse matrix decomposition restriction on the dictionary matrix. It is derived by solving three layers of feature extraction and component estimation. The first and second layers captured brain regions with low and moderate spatial overlaps, respectively. The third layer that segregated regions with significant spatial overlaps solved a sequence of vector decomposition problems using the proximal alternating linearized minimization (PALM) method and solved a decomposition restriction using the alternating directions method (ALM). It learned outlier-free dynamics that integrate spatiotemporal diversities across brains and external information. It differs from existing DL methods owing to its unique optimization model, which incorporates prior knowledge, subject-wise/multi-subject representation matrices, and outlier handling. The TLSDL algorithm was compared with existing dictionary learning algorithms using experimental and synthetic fMRI datasets to verify its performance. Overall, the mean correlation value was found to be 26 % higher for the TLSDL than for the state-of-the-art subject-wise sequential DL (swsDL) technique.

Readiness for clinical practice: Self-perceived confidence of final year dental students in Turkey - A multi-institutional study.

Introduction: The primary aim of undergraduate dental education is to prepare dental students for independent dental practice and to enable them to provide safe and effective dental care. This study aimed to investigate the self-perceived preparedness of senior dental undergraduate students in Turkey. Methods: Purposive sampling was used to recruit final-year dental students from 10 dental institutions offering undergraduate dental programs in Turkey. Student preparedness was assessed using a previously validated dental preparedness assessment scale based on 50 items encompassing core clinical skills, cognitive attributes, and behavioral skills. The research instrument was then translated into Turkish. The R statistical environment for Windows was used for the data analysis. Results: Responses were provided by 272 students (156 women and 116 men; 57% and 43%, respectively) across 10 different universities. The mean score of the participants was 75.68 with slightly higher scores for men compared to women (77.35 vs. 74.46 respectively). However, independent t-tests showed that the scores did not differ significantly between women and men. Conclusions: This study evaluated the self-perceived preparedness for dental practice of final-year students from 10 universities in Turkey. Although the results showed several areas of weakness, the scores of self-perceived preparedness of Turkish students were comparable to those reported in Europe and Asia. These findings can be used to inform future curriculum development to support students in consolidating their learning in perceived areas of weakness.

The impact of virtual reality haptic simulators in pre-clinical restorative dentistry: a qualitative enquiry into dental students' perceptions.

PURPOSE: In the realm of restorative dentistry, the integration of virtual reality haptic simulation (VRHS) for learning operative skills has garnered varied perceptions among dental students. Therefore, the aim of this study was to delve deep into undergraduates dental students' perceptions related to the impact of VRHS in pre-clinical restorative dentistry. METHODS: A homogeneous purposive sampling method was utilized to gather data from third-year undergraduate dental students (n = 23) at the College of Dental Medicine, Qatar University, to thoroughly investigate their views on the impact of VRHS on their learning experience in preparing a standard class I cavity. An explorative qualitative method using face-to-face focus group sessions were conducted in English during 2023. Focus group sessions were recorded and transcribed using Microsoft Teams. Two authors independently read the transcripts, coded the text, and manually analyzed text using an inductive thematic approach. RESULTS: A total of 21 (91.3%) students participated in this study. Analysis of 3 focus group interviews revealed five primary themes summarized with the term "MASTR" (M = manual dexterity, A = assessment, S = sequence, T = training, and R = realism). Based on frequency of reported themes, students perceived realism/ lifelike nature of VRHS requiring further enhancement to achieve the desired learning objective. CONCLUSION: Although, VRHS play a crucial role in modern dental education, offering innovative solutions for training, evaluation, and feedback, the need to enhance their ability to simulate real-life dental procedures and learning environment (realism), coupled with interactive and immersive learning experiences were the most frequently raised theme by students. In terms of curriculum design and learning pedagogies, dental educators should consider the appropriate sequence when integrating VRHS within the undergraduate curricula.

Research Advances of Lipid Nanoparticles in the Treatment of Colorectal Cancer.

Colorectal cancer (CRC) is a common type of gastrointestinal tract (GIT) cancer and poses an enormous threat to human health. Current strategies for metastatic colorectal cancer (mCRC) therapy primarily focus on chemotherapy, targeted therapy, immunotherapy, and radiotherapy; however, their adverse reactions and drug resistance limit their clinical application. Advances in nanotechnology have rendered lipid nanoparticles (LNPs) a promising nanomaterial-based drug delivery system for CRC therapy. LNPs can adapt to the biological characteristics of CRC by modifying their formulation, enabling the selective delivery of drugs to cancer tissues. They overcome the limitations of traditional therapies, such as poor water solubility, nonspecific biodistribution, and limited bioavailability. Herein, we review the composition and targeting strategies of LNPs for CRC therapy. Subsequently, the applications of these nanoparticles in CRC treatment including drug delivery, thermal therapy, and nucleic acid-based gene therapy are summarized with examples provided. The last section provides a glimpse into the advantages, current limitations, and prospects of LNPs in the treatment of CRC.

Compatibility and performance study of electrohydrodynamic printing using zinc oxide inkjet ink.

The demand for modern electronics and semiconductors has increased throughout the years, which has enabled the innovation and exploration of solution-processed deposition. Solution-based processes have gained a lot of interest due to the low-cost fabrication and the large fabrication areas without the need for high-vacuum equipment. In this study, we utilized the ZnO ink for inkjet printer ink to fabricate a thin film via Electrohydrodynamic printing. Three different ink solutions were prepared for experimentation. The EHD printing technique demonstrated the ink's compatibility with and without the modifications. The outcomes of the EHD printed materials were comparable with the spin-coated thin films. The EHD-printed films demonstrated better results in comparison to spin-coated films. Ra and Rq of the EHD film measured at 3.651 nm and 4.973 nm, respectively. It improved the absorbance up to two-fold at 360 nm wavelength and electrical conductivity up to 40% compared to the spin-coated films. Furthermore, the optimization of the printing parameters can lead to the improved morphology and thickness of the EHD thin films.

Using AI-Based Virtual Companions to Assist Adolescents with Autism in Recognizing and Addressing Cyberbullying.

Social media platforms and online gaming sites play a pervasive role in facilitating peer interaction and social development for adolescents, but they also pose potential threats to health and safety. It is crucial to tackle cyberbullying issues within these platforms to ensure the healthy social development of adolescents. Cyberbullying has been linked to adverse mental health outcomes among adolescents, including anxiety, depression, academic underperformance, and an increased risk of suicide. While cyberbullying is a concern for all adolescents, those with disabilities are particularly susceptible and face a higher risk of being targets of cyberbullying. Our research addresses these challenges by introducing a personalized online virtual companion guided by artificial intelligence (AI). The web-based virtual companion's interactions aim to assist adolescents in detecting cyberbullying. More specifically, an adolescent with ASD watches a cyberbullying scenario in a virtual environment, and the AI virtual companion then asks the adolescent if he/she detected cyberbullying. To inform the virtual companion in real time to know if the adolescent has learned about detecting cyberbullying, we have implemented fast and lightweight cyberbullying detection models employing the T5-small and MobileBERT networks. Our experimental results show that we obtain comparable results to the state-of-the-art methods despite having a compact architecture.

Taxonomic discordance of immersive realities in dentistry: A systematic scoping review.

OBJECTIVES: This review aimed to map taxonomy frameworks, descriptions, and applications of immersive technologies in the dental literature. DATA: The Preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) guidelines was followed, and the protocol was registered at open science framework platform (https://doi.org/10.17605/OSF.IO/H6N8M). SOURCES: Systematic search was conducted in MEDLINE (via PubMed), Scopus, and Cochrane Library databases, and complemented by manual search. STUDY SELECTION: A total of 84 articles were included, with 81 % between 2019 and 2023. Most studies were experimental (62 %), including education (25 %), protocol feasibility (20 %), in vitro (11 %), and cadaver (6 %). Other study types included clinical report/technique article (24 %), clinical study (9 %), technical note/tip to reader (4 %), and randomized controlled trial (1 %). Three-quarters of the included studies were published in oral and maxillofacial surgery (38 %), dental education (26 %), and implant (12 %) disciplines. Methods of display included head mounted display device (HMD) (55 %), see through screen (32 %), 2D screen display (11 %), and projector display (2 %). Descriptions of immersive realities were fragmented and inconsistent with lack of clear taxonomy framework for the umbrella and the subset terms including virtual reality (VR), augmented reality (AR), mixed reality (MR), augmented virtuality (AV), extended reality, and X reality. CONCLUSIONS: Immersive reality applications in dentistry are gaining popularity with a notable surge in the number of publications in the last 5 years. Ambiguities are apparent in the descriptions of immersive realities. A taxonomy framework based on method of display (full or partial) and reality class (VR, AR, or MR) is proposed. CLINICAL SIGNIFICANCE: Understanding different reality classes can be perplexing due to their blurred boundaries and conceptual overlapping. Immersive technologies offer novel educational and clinical applications. This domain is fast developing. With the current fragmented and inconsistent terminologies, a comprehensive taxonomy framework is necessary.

Energy Efficiency Optimisation of Joint Computational Task Offloading and Resource Allocation Using Particle Swarm Optimisation Approach in Vehicular Edge Networks.

With the progression of smart vehicles, i.e., connected autonomous vehicles (CAVs), and wireless technologies, there has been an increased need for substantial computational operations for tasks such as path planning, scene recognition, and vision-based object detection. Managing these intensive computational applications is concerned with significant energy consumption. Hence, for this article, a low-cost and sustainable solution using computational offloading and efficient resource allocation at edge devices within the Internet of Vehicles (IoV) framework has been utilised. To address the quality of service (QoS) among vehicles, a trade-off between energy consumption and computational time has been taken into consideration while deciding on the offloading process and resource allocation. The offloading process has been assigned at a minimum wireless resource block level to adapt to the beyond 5G (B5G) network. The novel approach of joint optimisation of computational resources and task offloading decisions uses the meta-heuristic particle swarm optimisation (PSO) algorithm and decision analysis (DA) to find the near-optimal solution. Subsequently, a comparison is made with other proposed algorithms, namely CTORA, CODO, and Heuristics, in terms of computational efficiency and latency. The performance analysis reveals that the numerical results outperform existing algorithms, demonstrating an 8% and a 5% increase in energy efficiency.

Predictive Value of Impulse Oscillometry Combined with Fractional Expiratory Nitric Oxide Test for Asthma in Preschool Children.

Objective: Prediction of asthma in preschool children is challenging and lacks objective indicators. The aim is to observe and analyze the variances between impulse oscillometry (IOS) and fractional expiratory nitric oxide (FeNO) in preschool children with wheezing, establish a joint prediction model, and explore the diagnostic value of combining IOS with FeNO in diagnosing asthma among preschool children. Patients and methods: This study enrolled children aged 3-6 years with wheezing between June 2021 and June 2022. They were categorized as asthmatic (n=104) or non-asthmatic (n=109) after a 1-year follow-up. Clinical data, along with IOS and FeNO measurements from both groups, underwent univariate regression and multiple regression analyses to identify predictive factors and develop the most accurate model. The prediction model was built using the stepwise (stepAIC) method. The receiver operating characteristic curve (ROC), calibration curve, Hosmer-Lemeshow test, and decision curve analysis (DCA) were employed to validate and assess the model. Results: During univariate analysis, a history of allergic rhinitis, a history of eczema or atopic dermatitis, and measures including FeNO, R5, X5, R20, Fres, and R5-R20 were found to be associated with asthma diagnosis. Subsequent multivariate analysis revealed elevated FeNO, R5, and X5 as independent risk factors. The stepAIC method selected five factors (history of allergic rhinitis, history of eczema or atopic dermatitis, FeNO, R5, X5) and established a prediction model. The combined model achieved an AUROC of 0.94, with a sensitivity of 0.89 and specificity of 0.88, surpassing that of individual factors. Calibration plots and the HL test confirmed satisfactory accuracy. Conclusion: This study has developed a prediction model based on five factors, potentially aiding clinicians in early identification of asthma risk among preschool children.

Effectiveness of H-files and Pro-Taper universal systems in removing Gutta-percha during endodontic retreatment: A comparative study.

Objective: This research was aimed at assessing the effectiveness of manual H-files versus a combination of a Pro-Taper universal rotary canal preparation system and retreatment system in removing gutta-percha (GP) during endodontic retreatment, by using a digital radiography technique. Methods: This ex vivo study used a non-probability consecutive sampling technique. The study sample comprised 60 extracted anterior permanent teeth, each with one root with a straight root canal (RC). After preparation, RCs were obturated with GP and sealer. Subsequently, teeth were stored for 2 weeks in a humid environment at 37 °C. Thirty teeth each were randomly assigned to the control (group I), and experimental (group II) groups. GP removal was performed with H-files {group I) or a combination of a Pro-Taper universal rotary canal preparation system and retreatment system (group 2). Digital radiographs were acquired with Carestream digital radiovisiography software (Kodak; version-VER.6.10.8.3-A), and the presence of residual GP was analyzed. AutoCAD (2006) software was used to demarcate the RC and residual root filling. The residual GP in both groups was compared with independent sample t-tests. Results: The remaining root filling did not significantly differ when GP was removed with conventional Hedstrom files versus a combination of Pro-Taper Universal preparation and retreatment file systems. The residual GP was confined to the apical third of the canals in both groups. Conclusions: Pro-Taper Universal preparation and retreatment file systems have similar effectiveness to manual H-files in GP removal in straight canals.

Emerging Trends in Virtual Surgical Planning for Orthognathic Surgery: A Global Overview of Research and Publication Patterns.

PURPOSE: Anticipating trends and pursuing innovative ideas are imperative for the advancement of science. The objective of this study was to conduct a bibliometric analysis of 3-dimensional virtual simulation in orthognathic surgery, explore its implications for clinical practice, and identify future publication trends through digital tools. METHODS: This study employed a retrospective bibliometric analysis using data obtained from the Web of Science database. The search strategy focused on articles related to orthognathic surgery and virtual simulation techniques. RStudio and bibliometrix tools were used to data mining. The independent variables retrieved from digital analysis were the emerging themes related to virtual planning in orthognathic surgery. The trends that we identified were facial esthetics, digital workflow, personalized treatments, and complex cases. The primary outcome variable was the number of publications dedicated to virtual simulation in orthognathic surgery, along with secondary outcomes such as citation rates, language of publication, country of origin, institutional affiliations, and emerging research themes. Covariates included variables related to publication characteristics, author affiliations, and geographic distribution of publications. Publication analyses over time involved descriptive statistics, regression analysis, Pearson correlation tests, and graphical representation techniques. Statistical significance was set at a 95% confidence interval (P value < .05). RESULTS: A comprehensive analysis of 987 articles reveals the impact of included authors, with a mean h-index of 62 (SD = 18.4). The analysis further illuminates a discernible upward trend in publications on this subject, showcasing a linear pattern with a notable R2 value of 0.88 (P = .021). English remains the predominant language of publication, accounting for 97.97% of articles, while contributions hailed from a diverse spectrum of 56 countries. Interestingly, a moderate correlation emerges between publication numbers and gross domestic product per capita (r = 0.30, P = .044) and total area (r = 0.30, P = .032), whereas a more substantial correlation is evident with total population (r = 0.61, P = .034). Notably, the most cited article amassed 254 citations. Furthermore, a Pearson correlation coefficient of 0.97 underscores the correlation between citation density and the year of publication. CONCLUSION: The bibliometric indicators provided insights for evaluating research productivity and the quality of research output. Emerging themes included facial esthetics, 3-dimensional printing, and the utilization of custom-made templates and implants. This study holds relevance for maxillofacial surgeons, academics, and researchers alike.