Insights and networks: methodological assessment and scientometric analysis of economic evaluations in dentistry.

INTRODUCTION: Assessing the methodological quality of economic evaluations (EEs) is crucial for evidence-based decision-making. The study aimed to evaluate EEs in restorative dentistry and endodontics, while also analyzing the scientific landscape of researchers and publications through co-authorship and citation network analysis providing an insight into the distribution of scientific expertise. METHODOLOGY: A systematic search for relevant articles from 2012 to 2022 was conducted using PubMed, Scopus, and EBSCO. The ten-point Drummond checklist was used to appraise the methodological quality of included studies. Bibliometric data for network analysis were extracted from the Dimensions database and visualized using VOSviewer software. RESULTS: Of the 37 articles, 81.08% scored good, 16.21% average, and 2.7% poor on the methodological rating scale. Most of the included studies were in Q1 journals, with limited representation in Q2 and Q3 journals. Compliance was highest in Q2 journals (95%), followed by Q1 (88.36%), while it dropped to 40% for Q3 journals. Co-authorship analysis revealed a dense network of researchers, with Prof. Falk Schwendicke V. having a significant influence. Moreover, the Journal of Dentistry had the highest impact, followed by Journal of Endodontics and BMC Oral Health. CONCLUSIONS: Despite a diverse scientific landscape, participation from developing countries was limited emphasizing the need for inclusivity and diversity in the scientific network. While the quantity of good-quality studies was encouraging, the overall quality of evidence remains paramount for decision-making in healthcare policy and practice. Therefore, continuous efforts to improve methodological rigor and reporting practices are essential to contribute robust evidence.

Restoration of endodontically treated teeth: A cost-effectiveness analysis of an endocrown versus a complete crown.

STATEMENT OF PROBLEM: Endocrowns have been proposed as an alternative to post-and-core retained complete crowns for structurally compromised endodontically treated teeth. However, an analysis of their cost-effectiveness is lacking. PURPOSE: The purpose of this simulation study was to assess the cost-effectiveness of an endocrown versus a complete crown as a definitive restoration for structurally compromised endodontically treated teeth. MATERIAL AND METHODS: A Markov simulation model was constructed with endodontically treated permanent molar teeth using TreeAge Pro Healthcare (2023) as a starting point for an 18-year-old patient. Costs were extrapolated from the ADA dental survey based on the United States healthcare, and the probabilities of transition were derived from existing literature. The cost-effectiveness was determined by using Monte Carlo microsimulations. A sensitivity analysis was performed to validate the model internally, whereas an experienced health expert and an endodontist performed the face validation. RESULTS: The complete crown was associated with additional health benefits (1.36 and 0.9 more years over a period of 5 years and lifetime, respectively) but at an increased cost (an additional 1143 USD and 1535 USD over a period of 5 years and lifetime, respectively). Moreover, the endocrown was cost-effective at lower Willingness-To-Pay (WTP) values (92% acceptable at 250 USD for 5 years and 73% acceptable at 250 USD for the lifetime of an individual), whereas at increased WTP threshold values, the complete crown was a cost-effective restoration (98.6% acceptable at 1250 USD for 5 years and 99.5% acceptable at 8000 USD over an individual's lifetime). CONCLUSIONS: The endocrown was a cost-effective restorative option at lower WTP values. However, at an increased WTP threshold, the complete crown became a more cost-effective restoration.

Research and application of artificial intelligence in dentistry from lower-middle income countries - a scoping review.

Artificial intelligence (AI) has been integrated into dentistry for improvement of current dental practice. While many studies have explored the utilization of AI in various fields, the potential of AI in dentistry, particularly in low-middle income countries (LMICs) remains understudied. This scoping review aimed to study the existing literature on the applications of artificial intelligence in dentistry in low-middle income countries. A comprehensive search strategy was applied utilizing three major databases: PubMed, Scopus, and EBSCO Dentistry & Oral Sciences Source. The search strategy included keywords related to AI, Dentistry, and LMICs. The initial search yielded a total of 1587, out of which 25 articles were included in this review. Our findings demonstrated that limited studies have been carried out in LMICs in terms of AI and dentistry. Most of the studies were related to Orthodontics. In addition gaps in literature were noted such as cost utility and patient experience were not mentioned in the included studies.

Irreversible pulpitis in mature permanent teeth: a cost-effectiveness analysis of pulpotomy versus root canal treatment.

INTRODUCTION: Evidence-based dentistry suggests pulpotomy as a potential alternative to root canal treatment in mature permanent teeth with irreversible pulpitis. However, the evidence surrounding the cost-valuation and cost-efficacy of this treatment modality is not yet established. In this context, we adopted an economic modeling approach to assess the cost-effectiveness of pulpotomy versus root canal treatment, as this could aid in effective clinical decision-making. METHODS: A Markov model was constructed following a mature permanent tooth with irreversible pulpitis in an 18-year-old patient over a lifetime using TreeAge Pro Healthcare 2022. Transition probabilities were estimated based on existing literature. Costs were estimated based on the United States healthcare following a private-payer perspective and parameter uncertainties were addressed using Monte-Carlo simulations. The model was validated internally by sensitivity analyses, and face validation was performed by an experienced endodontist and health economist. RESULTS: In the base case scenario, root canal treatment was associated with additional health benefit but at an increased cost (1.08 more years with an incremental cost of 311.20 USD) over a period of an individual's lifetime. The probabilistic sensitivity analysis revealed pulpotomy to be cost-effective at lower Willingness-To-Pay (WTP) values (99.9% acceptable at 50 USD) whereas increasing the values of WTP threshold root canal treatment was a cost-effective treatment (99.9% acceptable at 550 USD). CONCLUSION: Based on current evidence, pulpotomy was a cost-effective treatment option at lower WTP values for the management of irreversible pulpitis in mature permanent teeth. However, by increasing the WTP threshold, root canal treatment became a more cost-effective treatment option over a period of lifetime of an individual.

Navigating challenges and opportunities: AI's contribution to Pakistan's sustainable development goals agenda - a narrative review.

Sustainable Developmental Goals (SDGs) were introduced by the United Nations to ensure the sustainable progress of mankind through various domains. Pakistan, a low-middle-income country, faces many challenges in achieving SDGs. Artificial Intelligence is a rapidly evolving technology presenting significant importance in achieving SDGs. Therefore, this narrative review aimed to evaluate the artificial intelligence technologies that have been utilized globally and nationally which can be implemented in Pakistan focusing on Goal 3 (Good Health and Well-being) of SDGs. AI has been utilized primarily in high-income countries aiming to improve healthcare, thereby progressing towards achieving different targets of Goal 3 of SDGs. Pakistan lacks such initiatives with modest to no improvement across different SDGs. Therefore, Pakistan can adapt initiatives undertaken by resourceful countries to achieve its own SDGs.

Comparative evaluation of ethanol versus citric acid in removal of oil-based calcium hydroxide from the apical third of root canal system.

Objectives: To evaluate the effectiveness of ethanol compared to citric acid in the removal of oil-based calcium hydroxide from the apical third of the root canal system using passive ultrasonic irrigation. METHODS: The in vitro study was conducted from September to October 2021 at the dental clinics of the Aga Khan University Hospital, Karachi, and comprised single-rooted teeth that were selected from institutional bank of extracted teeth. They were randomly divided into group A having 70% ethanol + passive ultrasonic irrigation, group B 10% citric acid + passive ultrasonic irrigation, group C positive controls and group D negative controls. The specimens were sectioned at 1mm and 3mm from the apex and examined under a dental operating microscope. A single examiner scored the specimens on two different occasions. Data was analysed using SPSS 25. RESULTS: Of the 90 teeth, there were 40(44.4%) in each of the 2 experimental groups and 5(5.5%) in each of the 2 control groups. At 3mm apical sections, ethanol was significantly more effective in the removal of oil-based calcium hydroxide (p=0.01). However, at 1mm from the apex, there was no significant difference between the experimental groups (p=0.064). Intragroup comparison showed that for groups A and B, residual medicament at 1mm sections was significantly greater than at 3mm sections (p<0.001, p=0.003). CONCLUSIONS: Neither irrigant showed complete removal at 1mm and 3mm from the apex. However, at 3mm apical sections, 70% ethanol was significantly more effective compared to 10% citric acid.

Analysis of impact of consumption of proton pump inhibitor on osseo integration of dental implants to the alveolar bone: A systematic critical appraisal.

Proton pump inhibitors are one of the most frequently prescribed medicines primarily for reducing the production of gastric acid. Every medicine has some adverse effects associated with it, including effects on the bone tissues. Dental implant is one of the most preferred options for teeth replacement. The current literature review was planned to evaluate the association between intake of proton pump inhibitors and its impact on the bone around the dental implant. Literature review entailed search on Google Scholar, Web of Science and PubMed databases using a range of search terms. Chronic intake of proton pump inhibitors has been associated with decrease in the density of bone, which eventually leads to increased risk of dental implant failure. However, since limited studies have been carried out, further research is required, especially clinical trials, to evaluate the relationship between the intake of proton pump inhibitors and the failure of dental implants.

An Artificial Intelligence model for implant segmentation on periapical radiographs.

OBJECTIVE: To segment dental implants on PA radiographs using a Deep Learning (DL) algorithm. To compare the performance of the algorithm relative to ground truth determined by the human annotator. Methodology: Three hundred PA radiographs were retrieved from the radiographic database and consequently annotated to label implants as well as teeth on the LabelMe annotation software. The dataset was augmented to increase the number of images in the training data and a total of 1294 images were used to train, validate and test the DL algorithm. An untrained U-net was downloaded and trained on the annotated dataset to allow detection of implants using polygons on PA radiographs. RESULTS: A total of one hundred and thirty unseen images were run through the trained U-net to determine its ability to segment implants on PA radiographs. The performance metrics are as follows: accuracy of 93.8%, precision of 90%, recall of 83%, F-1 score of 86%, Intersection over Union of 86.4% and loss = 21%. CONCLUSIONS: The trained DL algorithm segmented implants on PA radiographs with high performance similar to that of the humans who labelled the images forming the ground truth.

An artificial intelligence model for instance segmentation and tooth numbering on orthopantomograms.

AIM: To develop a deep learning (DL) artificial intelligence (AI) model for instance segmentation and tooth numbering on orthopantomograms (OPGs). MATERIALS AND METHODS: Forty OPGs were manually annotated to lay down the ground truth for training two convolutional neural networks (CNNs): U-net and Faster RCNN. These algorithms were concurrently trained and validated on a dataset of 1280 teeth (40 OPGs) each. The U-net algorithm was trained on OPGs specifically annotated with polygons to label all 32 teeth via instance segmentation, allowing each tooth to be denoted as a separate entity from the surrounding structures. Simultaneously, teeth were also numbered according to the Fédération Dentaire Internationale (FDI) numbering system, using bounding boxes to train Faster RCNN. Consequently, both trained CNNs were combined to develop an AI model capable of segmenting and numbering all teeth on an OPG. RESULTS: The performance of the U-net algorithm was determined using various performance metrics including precision = 88.8%, accuracy = 88.2%, recall = 87.3%, F-1 score = 88%, dice index = 92.3%, and Intersection over Union (IoU) = 86.3%. The performance metrics of the Faster RCNN algorithm were determined using overlap accuracy = 30.2 bounding boxes (out of a possible of 32 boxes) and classifier accuracy of labels = 93.8%. CONCLUSIONS: The instance segmentation and tooth numbering results of our trained AI model were close to the ground truth, indicating a promising future for their incorporation into clinical dental practice. The ability of an AI model to automatically identify teeth on OPGs will aid dentists with diagnosis and treatment planning, thus increasing efficiency.

The Dilemma Of Management Of Cystic Lesions; An Uncertain Way Forward: A Case Report.

Periapical diseases ranges from mild granulomatous lesions to large cystic ones, with the treatments corresponding to their respective pre-operative diagnoses. However, the determination of cause of periapical radiolucency is impossible on pre-operative clinical and radiographic examinations. We present a case highlighting the difficulties encountered in treating a periapical cyst using the current evidence in literature. It demonstrates the uncertainty involved in treating such lesions, owing to the impossible nature of determining the histopathological nature of the cyst, i.e., being either true cysts or pocket cysts. This case includes orthograde re-treatment; decompression of the cystic lesion, followed by peri-apical surgery of two teeth over a course of three years; and the uncertain outcomes encountered after each phase of the treatment.

Navigating through our history in research: An altmetric analysis for publications by the full-time operative dentistry faculty at the Aga Khan University Hospital in the past decade.

OBJECTIVE: To analyse the social dissemination of publications by fulltime faculty at a tertiary care facility. METHODS: The retrospective study was conducted at the Aga Khan University Hospital, Karachi, and comprised publication records of the fulltime Operative Dentistry faculty members between July 2011 till July 2021. The search was done on Google Scholar, Altmetric Explorer and PubMed electronic databases. After final screening, all the publications in PubMed-indexed journals, including in vitro studies, randomised controlled trials, original research articles, case reports and letters to the editor, for which the Altmetric Attention Score was available were included. RESULTS: Of the 225 publications identified, 34 (15%) formed the final sample. The cumulative citation count for the publications was 617 and Altmetric Attention Score was 158. There were 16 Facebook mentions and 163 tweets. CONCLUSION: The social impact of publications by the Operative Dentistry faculty over a decade was not convincing in terms of Altmetric Attention Score.

Understanding deep learning - challenges and prospects.

The developments in Artificial Intelligence have been on the rise since its advent. The advancements in this field have been the innovative research area across a wide range of industries, making its incorporation in dentistry inevitable. Artificial Intelligence techniques are making serious progress in the diagnostic and treatment planning aspects of dental clinical practice. This will ultimately help in the elimination of subjectivity and human error that are often part of radiographic interpretations, and will improve the overall efficiency of the process. The various types of Artificial Intelligence algorithms that exist today make the understanding of their application quite complex. The current narrative review was planned to make comprehension of Artificial Intelligence algorithms relatively straightforward. The focus was planned to be kept on the current developments and prospects of Artificial Intelligence in dentistry, especially Deep Learning and Convolutional Neural Networks in diagnostic imaging. The narrative review may facilitate the interpretation of seemingly perplexing research published widely in dental journals.

Aesthetic rehabilitation with immediate implant placement in anterior maxilla after traumatic avulsive injury: A case report.

Traumatic oral injuries present their own unique restorative challenges to the clinician due to their variable clinical presentation. In such cases, achieving optimum aesthetics and function in the maxillary aesthetic zone is challenging. This case report describes the rehabilitation of a patient with immediate implant placement after suffering trauma to the oral cavity resulting in a complete loss (avulsion) of a permanent central incisor tooth. In order to preserve the existing soft and hard tissue and to achieve predictable and aesthetically pleasing results, we decided to place an immediate implant as opposed to replantation of the avulsed tooth. Flapless implant surgery was planned and a dental implant (Bio horizons Implant Systems, Inc.) was placed following non-submerged protocol. At six year follow-up, the clinical and radiographic examination revealed a well osseo-integrated implant with an intact buccal cortical plate. No clinical and radiographic signs of peri-implant disease were noted on follow-up. This case report supports the fact that immediate implant placement for missing teeth in the aesthetic zone results in favourable outcomes both in terms of function and aesthetics.

Inculcating research curriculum in Operative Dentistry - Endodontics residency programme: Experience and outcomes.

Incorporating research education and training in residency curriculum increases the understanding of evidence-based decision-making among doctors in training. Evidence suggests that the addition of research is linearly associated with improvement in clinical competence, and encourages the residents to shape their career as clinical investigators. The current paper was planned to share the experience of adding research into the core curriculum of Operative Dentistry-Endodontics residency programme at a tertiary care university hospital, and to evaluate the outcome achieved with that change.

Orthograde apical plug in a traumatized tooth with necrotic pulp and immature apex using calcium silicate cement: A case report.

This case report describes dental management of a 15- year-old boy, undergoing treatment for Thalassaemia Major and Acute Myeloid Leukaemia with bone marrow transplant and immuno-suppressants. During the course of his treatment the patient developed a swelling in anterior maxilla and therefore was referred by the primary physician for evaluation. This case report highlights the management of medically compromised patients in a tertiary care hospital in which apexification was carried out in a permanent immature tooth utilizing MTA as an immediate apical plug.

Cochrane systematic reviews in dentistry: an Altmetric and network analysis.

Introduction Cochrane systematic reviews (CSRs) play an important role in evidence-based decision-making. Therefore, the present study aimed to determine the social impact of CSRs in dentistry and the inclusivity and diversity of researchers contributing to one of the largest databases in health care research.Methodology The Altmetric and bibliometric data for CSRs in dentistry were obtained through Altmetric Explorer and the Dimensions database and were analysed to determine the trends. Furthermore, the correlation between the number of citations and the Altmetric Attention Score (AAS) was identified using Spearman's correlation co-efficient.Results Mendeley was found to be the most active Altmetric resource, followed by Twitter. The tweets were more popular among the members of the public (65.5%) and had a diverse geographic spread. The co-authorship network analysis revealed an overall dense network of researchers. In the co-citation network analysis, the Journal of Community Dentistry had the greatest influence. Moreover, a weaker correlation was noticed between the citation counts and AAS (rs=0.325; p <0.01).Conclusion CSRs had a modest social impact in terms of AAS; however, the social network of contributing researchers was diverse and the researchers affiliated with the University of Manchester, UK were found to have the strongest link.

Generative artificial intelligence: synthetic datasets in dentistry.

INTRODUCTION: Artificial Intelligence (AI) algorithms, particularly Deep Learning (DL) models are known to be data intensive. This has increased the demand for digital data in all domains of healthcare, including dentistry. The main hindrance in the progress of AI is access to diverse datasets which train DL models ensuring optimal performance, comparable to subject experts. However, administration of these traditionally acquired datasets is challenging due to privacy regulations and the extensive manual annotation required by subject experts. Biases such as ethical, socioeconomic and class imbalances are also incorporated during the curation of these datasets, limiting their overall generalizability. These challenges prevent their accrual at a larger scale for training DL models. METHODS: Generative AI techniques can be useful in the production of Synthetic Datasets (SDs) that can overcome issues affecting traditionally acquired datasets. Variational autoencoders, generative adversarial networks and diffusion models have been used to generate SDs. The following text is a review of these generative AI techniques and their operations. It discusses the chances of SDs and challenges with potential solutions which will improve the understanding of healthcare professionals working in AI research. CONCLUSION: Synthetic data customized to the need of researchers can be produced to train robust AI models. These models, having been trained on such a diverse dataset will be applicable for dissemination across countries. However, there is a need for the limitations associated with SDs to be better understood, and attempts made to overcome those concerns prior to their widespread use.

A bibliometric analysis of scientific literature in digital dentistry from low- and lower-middle income countries.

OBJECTIVE: Bibliometric analysis and citation counts help to acknowledge influence of publications. The aim of this study was to conduct bibliometric and citation analysis of top-cited articles, from low- and lower-middle income countries, on use and application of digital technology in dentistry. METHODOLOGY: A search strategy based on "Digital Dentistry", "Low Income Countries", and "Lower-Middle Income Countries" was used in October 2023 using Scopus database to retrieve articles relevant to digital dentistry, with citation count of 10 or more. From 44 included articles, bibliometric information was analyzed on SPSS version 23. Network analysis based on co-citations, keywords, and number of citations was conducted on VOS software (version 1.6.20). RESULTS: Most relevant articles were published in 2021 (n = 8), with 52.3% original articles, out of which 40.9% were in vitro studies. India had the highest number of articles (n = 24), with most publications in The Journal of Indian Prosthodontic Society (n = 4), and in the domain of General Dentistry (n = 15, 34.1%). Co-authorship network analysis was not significant, but country-wise co-authorship analysis revealed India with the greatest link strength (4.0). Highest occurring keyword was 3D printing (link strength 5.0), and the citation analysis revealed Journal of Prosthetic Dentistry with the most number of published documents (3), having a citation count of 275. Bibliographic coupling for sources revealed Journal of Indian Prosthodontic Society to have the highest link strength of 15.33. CONCLUSION: This analysis uncovers interesting bibliometric and citation based information including key thematic trends, emphasizing crucial role of technologies like 3D printing, CAD/CAM, and CBCT in digital dentistry. The study underscores the imperative for increased original research efforts in low- and lower middle-income countries.