Comparison of knowledge, attitude and concern about HIV/AIDS patients among dental students: A cross sectional survey

HIV/AIDS has taken a pandemic form affecting 40 million people around the world. The present study aimed to determine the knowledge, attitude, and concerns of dental students towards HIV/AIDS infected individuals. A cross sectional study was conducted among 224 subjects, among them 112 final year (FY) students and 112 interns. Subjects were selected from 10 dental colleges in Bangalore city, India. Data was collected through a self-administered questionnaire. The mean knowledge score of FY students and interns was 73.66+5.9 and 80.4+7.2 respectively; the mean attitude score was 71.25+1.707 and 87.75+1.8 and the mean concern score was 92+2.645 and 97.75+3.171 respectively. Differences in the mean score were significant. Dental interns had slightly higher knowledge, attitude, and concern than the FY students. There is a need to add HIV/AIDS patient’s infection control measures in the dental curriculum.   Le VIH/SIDA a pris une forme pandémique touchant 40 millions de personnes dans le monde. La présente étude visait à déterminer les connaissances, l'attitude et les préoccupations des étudiants en médecine dentaire envers les personnes infectées par le VIH/SIDA. Une étude transversale a été menée auprès de 224 sujets, dont 112 étudiants de dernière année (FY) et 112 stagiaires. Les sujets ont été sélectionnés dans 10 collèges dentaires de la ville de Bangalore, en Inde. Les données ont été recueillies au moyen d'un questionnaire auto-administré. Le score de connaissance moyen des étudiants et des stagiaires FY était respectivement de 73,66+5,9 et 80,4+7,2 ; le score moyen d'attitude était de 71,25+1,707 et 87,75+1,8 et le score moyen de préoccupation était respectivement de 92+2,645 et 97,75+3,171. Les différences dans le score moyen étaient significatives. Les stagiaires dentaires avaient des connaissances, une attitude et des préoccupations légèrement plus élevées que les étudiants de l'AF. Il est nécessaire d'ajouter les mesures de contrôle de l'infection des patients atteints du VIH/SIDA dans le programme d'études dentaires

Dental Students’ Experience, Impact, and Response to Patient Aggression in Saudi Arabia: A Nationwide Study

Patient aggression and violence comprise a wide range of behaviors and actions that may include verbal aggression and physical aggression. The aim of this study is to report dental students’ experience with, impact from, and response to patient aggression in Saudi Arabia. A cross-sectional analytical study was conducted among dental students from various health universities representing each region of Saudi Arabia. Data were collected using a self-administered, structured and validated questionnaire. A total of 375 participants responded to the questionnaire and 121 (32.3%) study participants reported experiencing patient aggression. Out of those, 91 (75.21%) experienced patients displaying anger or raising their voice toward them, 37 (30.58%) reported being insulted by a patient, 22 (18.18%) reported being threatened, 12 (6.2%) had experienced sexual harassment, and 65 (50.41%) had experienced verbal harassment. Furthermore, 91 (75.21%) participants reported being abandoned by patients because they were students. A total of 55 (45.45%) participants stated that aggressive patient behavior had an impact on their clinical performance, and 44 (36.36%) considered themselves stressed out. A total of 24 (19.83%) participants took time off due to incidents and 22 (18.18%) thought about quitting dentistry. Prevalence of patient aggression was significant among dental students in Saudi Arabia. These episodes of patient aggression negatively impacted students’ academic performance and wellbeing, necessitating urgent attention. Educational institutions should conduct periodic workshops for students in order to address these issues. Policymakers should develop better policies in order to reduce violence and aggression against health care providers

Performance of Artificial Intelligence Models Designed for Diagnosis, Treatment Planning and Predicting Prognosis of Orthognathic Surgery (OGS)—A Scoping Review

The technological advancements in the field of medical science have led to an escalation in the development of artificial intelligence (AI) applications, which are being extensively used in health sciences. This scoping review aims to outline the application and performance of artificial intelligence models used for diagnosing, treatment planning and predicting the prognosis of orthognathic surgery (OGS). Data for this paper was searched through renowned electronic databases such as PubMed, Google Scholar, Scopus, Web of science, Embase and Cochrane for articles related to the research topic that have been published between January 2000 and February 2022. Eighteen articles that met the eligibility criteria were critically analyzed based on QUADAS-2 guidelines and the certainty of evidence of the included studies was assessed using the GRADE approach. AI has been applied for predicting the post-operative facial profiles and facial symmetry, deciding on the need for OGS, predicting perioperative blood loss, planning OGS, segmentation of maxillofacial structures for OGS, and differential diagnosis of OGS. AI models have proven to be efficient and have outperformed the conventional methods. These models are reported to be reliable and reproducible, hence they can be very useful for less experienced practitioners in clinical decision making and in achieving better clinical outcomes

Developments and Performance of Artificial Intelligence Models Designed for Application in Endodontics: A Systematic Review

Technological advancements in health sciences have led to enormous developments in artificial intelligence (AI) models designed for application in health sectors. This article aimed at reporting on the application and performances of AI models that have been designed for application in endodontics. Renowned online databases, primarily PubMed, Scopus, Web of Science, Embase, and Cochrane and secondarily Google Scholar and the Saudi Digital Library, were accessed for articles relevant to the research question that were published from 1 January 2000 to 30 November 2022. In the last 5 years, there has been a significant increase in the number of articles reporting on AI models applied for endodontics. AI models have been developed for determining working length, vertical root fractures, root canal failures, root morphology, and thrust force and torque in canal preparation; detecting pulpal diseases; detecting and diagnosing periapical lesions; predicting postoperative pain, curative effect after treatment, and case difficulty; and segmenting pulp cavities. Most of the included studies (n = 21) were developed using convolutional neural networks. Among the included studies. datasets that were used were mostly cone-beam computed tomography images, followed by periapical radiographs and panoramic radiographs. Thirty-seven original research articles that fulfilled the eligibility criteria were critically assessed in accordance with QUADAS-2 guidelines, which revealed a low risk of bias in the patient selection domain in most of the studies (risk of bias: 90%; applicability: 70%). The certainty of the evidence was assessed using the GRADE approach. These models can be used as supplementary tools in clinical practice in order to expedite the clinical decision-making process and enhance the treatment modality and clinical operation

Developments and Performance of Artificial Intelligence Models Designed for Application in Endodontics: A Systematic Review

Technological advancements in health sciences have led to enormous developments in artificial intelligence (AI) models designed for application in health sectors. This article aimed at reporting on the application and performances of AI models that have been designed for application in endodontics. Renowned online databases, primarily PubMed, Scopus, Web of Science, Embase, and Cochrane and secondarily Google Scholar and the Saudi Digital Library, were accessed for articles relevant to the research question that were published from 1 January 2000 to 30 November 2022. In the last 5 years, there has been a significant increase in the number of articles reporting on AI models applied for endodontics. AI models have been developed for determining working length, vertical root fractures, root canal failures, root morphology, and thrust force and torque in canal preparation; detecting pulpal diseases; detecting and diagnosing periapical lesions; predicting postoperative pain, curative effect after treatment, and case difficulty; and segmenting pulp cavities. Most of the included studies (n = 21) were developed using convolutional neural networks. Among the included studies. datasets that were used were mostly cone-beam computed tomography images, followed by periapical radiographs and panoramic radiographs. Thirty-seven original research articles that fulfilled the eligibility criteria were critically assessed in accordance with QUADAS-2 guidelines, which revealed a low risk of bias in the patient selection domain in most of the studies (risk of bias: 90%; applicability: 70%). The certainty of the evidence was assessed using the GRADE approach. These models can be used as supplementary tools in clinical practice in order to expedite the clinical decision-making process and enhance the treatment modality and clinical operation

Application and Performance of Artificial Intelligence Technology in Detection, Diagnosis and Prediction of Dental Caries (DC)—A Systematic Review

Evolution in the fields of science and technology has led to the development of newer applications based on Artificial Intelligence (AI) technology that have been widely used in medical sciences. AI-technology has been employed in a wide range of applications related to the diagnosis of oral diseases that have demonstrated phenomenal precision and accuracy in their performance. The aim of this systematic review is to report on the diagnostic accuracy and performance of AI-based models designed for detection, diagnosis, and prediction of dental caries (DC). Eminent electronic databases (PubMed, Google scholar, Scopus, Web of science, Embase, Cochrane, Saudi Digital Library) were searched for relevant articles that were published from January 2000 until February 2022. A total of 34 articles that met the selection criteria were critically analyzed based on QUADAS-2 guidelines. The certainty of the evidence of the included studies was assessed using the GRADE approach. AI has been widely applied for prediction of DC, for detection and diagnosis of DC and for classification of DC. These models have demonstrated excellent performance and can be used in clinical practice for enhancing the diagnostic performance, treatment quality and patient outcome and can also be applied to identify patients with a higher risk of developing DC

Performance of Artificial Intelligence Models Designed for Diagnosis, Treatment Planning and Predicting Prognosis of Orthognathic Surgery (OGS)—A Scoping Review

The technological advancements in the field of medical science have led to an escalation in the development of artificial intelligence (AI) applications, which are being extensively used in health sciences. This scoping review aims to outline the application and performance of artificial intelligence models used for diagnosing, treatment planning and predicting the prognosis of orthognathic surgery (OGS). Data for this paper was searched through renowned electronic databases such as PubMed, Google Scholar, Scopus, Web of science, Embase and Cochrane for articles related to the research topic that have been published between January 2000 and February 2022. Eighteen articles that met the eligibility criteria were critically analyzed based on QUADAS-2 guidelines and the certainty of evidence of the included studies was assessed using the GRADE approach. AI has been applied for predicting the post-operative facial profiles and facial symmetry, deciding on the need for OGS, predicting perioperative blood loss, planning OGS, segmentation of maxillofacial structures for OGS, and differential diagnosis of OGS. AI models have proven to be efficient and have outperformed the conventional methods. These models are reported to be reliable and reproducible, hence they can be very useful for less experienced practitioners in clinical decision making and in achieving better clinical outcomes

Dental Students’ Experience, Impact, and Response to Patient Aggression in Saudi Arabia: A Nationwide Study

Patient aggression and violence comprise a wide range of behaviors and actions that may include verbal aggression and physical aggression. The aim of this study is to report dental students’ experience with, impact from, and response to patient aggression in Saudi Arabia. A cross-sectional analytical study was conducted among dental students from various health universities representing each region of Saudi Arabia. Data were collected using a self-administered, structured and validated questionnaire. A total of 375 participants responded to the questionnaire and 121 (32.3%) study participants reported experiencing patient aggression. Out of those, 91 (75.21%) experienced patients displaying anger or raising their voice toward them, 37 (30.58%) reported being insulted by a patient, 22 (18.18%) reported being threatened, 12 (6.2%) had experienced sexual harassment, and 65 (50.41%) had experienced verbal harassment. Furthermore, 91 (75.21%) participants reported being abandoned by patients because they were students. A total of 55 (45.45%) participants stated that aggressive patient behavior had an impact on their clinical performance, and 44 (36.36%) considered themselves stressed out. A total of 24 (19.83%) participants took time off due to incidents and 22 (18.18%) thought about quitting dentistry. Prevalence of patient aggression was significant among dental students in Saudi Arabia. These episodes of patient aggression negatively impacted students’ academic performance and wellbeing, necessitating urgent attention. Educational institutions should conduct periodic workshops for students in order to address these issues. Policymakers should develop better policies in order to reduce violence and aggression against health care providers

Combination of Levamisole with Prednisone in Treating Recurrent Major Aphthous Ulcer in a Young Boy: A Case Report

Recurrent aphthous stomatitis (RAS) is an oral condition characterized by painful oral ulcerations. While the clinical features of this disease are easily defined, the etiology remains unclear. Thus, existing treatments are still unsatisfactory in reducing the severity, healing, and recurrence rate; however, there is no permanent and definitive treatment. Effective treatment for aphthous stomatitis is not available, and those treatments available mainly focus on suppressing its symptoms. We are reporting a case of a 17-year-old boy who presented with a 3-year history of multiple recurrent major ulcers in the oral cavity. Levamisole with steroids has been used in many clinical trials to treat aphthous ulcers, showing an improvement in pain, discomfort, healing time, and reduction in the number of ulcers. The same method was used to treat our patient, who showed promising results, with no recurrence for one year. Levamisole is a safe, easily tolerable and promising drug for the treatment of RAS

Use of YouTube as a Learning Modality for Clinical Procedures among Dental Students in Riyadh, Saudi Arabia—A Cross-Sectional Study

Social media like YouTube are increasingly used by students as a learning tool. The aim of this study was to examine the use of YouTube videos as a means of learning clinical procedures among dental students in Riyadh, Saudi Arabia. A cross-sectional observational study was conducted among dental students from six dental colleges in Riyadh, Saudi Arabia. Among the total of 331 dental students who responded to this survey, 93.9% (n = 308) reported that they had used YouTube for dental learning. A total of 65.30% (n = 201) of the respondents strongly agreed that they find videos of clinical procedures on YouTube helpful as a learning tool. A total of 54.40% (n = 180) agreed that they always refer to YouTube videos to prepare for a clinical procedure that they have never done before. A total of 75.3% (n = 232) reported that they most commonly watched clinical procedures related to restorative dentistry, 67.2% (n = 207) for fixed prosthodontics procedures, 65.3% (n = 201) for endodontic clinical procedures, and 62.3% (n = 192) for removable prosthodontics videos. A total of 50.60% (n = 156) strongly agreed that YouTube videos are helpful in relating theoretical knowledge with clinical knowledge. A total of 50.30% (n = 155) reported that it is important to have faculty guidance regarding useful YouTube videos on dental procedures. A total of 91.90% (n = 283) participants would like their dental school to post tutorials or videos for clinical procedures on YouTube. Even after increased availability of online videos, a majority of dental students felt that YouTube videos suggested by faculty were more valuable than videos identified through normal searching