UNASSIGNED: To assess the utility of wearable cameras in medical examinations, we created a physician-view video-based examination question and explanation, and the survey results indicated that these cameras can enhance the evaluation and educational capabilities of medical examinations.

The dental treatment of patients with oral cavity and oropharyngeal squamous cell carcinoma (OOPSCC) may be challenging for dentists. This study aimed to characterize systemic changes in patients with OOPSCC undergoing dental treatment prior to cancer therapy, with a specific focus on laboratory assessments. The primary objectives included identifying potential adverse events, such as infections or bleeding, resulting from dental procedures. Additionally, the study aimed to correlate baseline patient characteristics with treatment-related toxicities. This was a prospective cohort study that included 110 OOPSCC patients referred to the Dental Oncology Service at São Paulo State Cancer Institute, Brazil, between November/2019 and December/2020. Comorbidities, sociodemographic data, medication in use, cancer treatment-related toxicities, and altered laboratory tests results were correlated. The most common comorbidities and altered laboratory results were hypertension, dyslipidemia, diabetes, as well as elevated levels of C-reactive protein, hemoglobin, and hematocrit. Toxicities exhibited a progressive pattern over time, encompassing oral mucositis (OM), xerostomia, dysphagia, dysgeusia, trismus, and radiodermatitis. No correlation between comorbidities and cancer treatment-related toxicities, a positive correlation between medications in use and OM, and a negative correlation between medications and dysgeusia were found. OM was associated with altered thyroxine (T4) and free thyroxine (FT4), calcium, urea, creatinine, alkaline phosphatase, and syphilis. Family income and housing were OM predictors. Altered T4/FT4/urea/calcium/alkaline phosphatase/creatinine/syphilis may be useful clinical predictors of OM. Despite the elevated prevalence of comorbidities and abnormal laboratory findings, dental treatment prior to cancer treatment yielded no adverse events.

BACKGROUND: Large language models like ChatGPT have revolutionized the field of natural language processing with their capability to comprehend and generate textual content, showing great potential to play a role in medical education. This study aimed to quantitatively evaluate and comprehensively analysis the performance of ChatGPT on three types of national medical examinations in China, including National Medical Licensing Examination (NMLE), National Pharmacist Licensing Examination (NPLE), and National Nurse Licensing Examination (NNLE).
METHODS: We collected questions from Chinese NMLE, NPLE and NNLE from year 2017 to 2021. In NMLE and NPLE, each exam consists of 4 units, while in NNLE, each exam consists of 2 units. The questions with figures, tables or chemical structure were manually identified and excluded by clinician. We applied direct instruction strategy via multiple prompts to force ChatGPT to generate the clear answer with the capability to distinguish between single-choice and multiple-choice questions.
RESULTS: ChatGPT failed to pass the accuracy threshold of 0.6 in any of the three types of examinations over the five years. Specifically, in the NMLE, the highest recorded accuracy was 0.5467, which was attained in both 2018 and 2021. In the NPLE, the highest accuracy was 0.5599 in 2017. In the NNLE, the most impressive result was shown in 2017, with an accuracy of 0.5897, which is also the highest accuracy in our entire evaluation. ChatGPT\'s performance showed no significant difference in different units, but significant difference in different question types. ChatGPT performed well in a range of subject areas, including clinical epidemiology, human parasitology, and dermatology, as well as in various medical topics such as molecules, health management and prevention, diagnosis and screening.
CONCLUSIONS: These results indicate ChatGPT failed the NMLE, NPLE and NNLE in China, spanning from year 2017 to 2021. but show great potential of large language models in medical education. In the future high-quality medical data will be required to improve the performance.

BACKGROUND: ChatGPT is among the most popular large language models (LLMs), exhibiting proficiency in various standardized tests, including multiple-choice medical board examinations. However, its performance on otolaryngology-head and neck surgery (OHNS) certification examinations and open-ended medical board certification examinations has not been reported.
OBJECTIVE: We aimed to evaluate the performance of ChatGPT on OHNS board examinations and propose a novel method to assess an AI model\'s performance on open-ended medical board examination questions.
METHODS: Twenty-one open-ended questions were adopted from the Royal College of Physicians and Surgeons of Canada\'s sample examination to query ChatGPT on April 11, 2023, with and without prompts. A new model, named Concordance, Validity, Safety, Competency (CVSC), was developed to evaluate its performance.
RESULTS: In an open-ended question assessment, ChatGPT achieved a passing mark (an average of 75% across 3 trials) in the attempts and demonstrated higher accuracy with prompts. The model demonstrated high concordance (92.06%) and satisfactory validity. While demonstrating considerable consistency in regenerating answers, it often provided only partially correct responses. Notably, concerning features such as hallucinations and self-conflicting answers were observed.
CONCLUSIONS: ChatGPT achieved a passing score in the sample examination and demonstrated the potential to pass the OHNS certification examination of the Royal College of Physicians and Surgeons of Canada. Some concerns remain due to its hallucinations, which could pose risks to patient safety. Further adjustments are necessary to yield safer and more accurate answers for clinical implementation.

BACKGROUND: ChatGPT has gained global attention recently owing to its high performance in generating a wide range of information and retrieving any kind of data instantaneously. ChatGPT has also been tested for the United States Medical Licensing Examination (USMLE) and has successfully cleared it. Thus, its usability in medical education is now one of the key discussions worldwide.
OBJECTIVE: The objective of this study is to evaluate the performance of ChatGPT in medical biochemistry using clinical case vignettes.
METHODS: The performance of ChatGPT was evaluated in medical biochemistry using 10 clinical case vignettes. Clinical case vignettes were randomly selected and inputted in ChatGPT along with the response options. We tested the responses for each clinical case twice. The answers generated by ChatGPT were saved and checked using our reference material.
RESULTS: ChatGPT generated correct answers for 4 questions on the first attempt. For the other cases, there were differences in responses generated by ChatGPT in the first and second attempts. In the second attempt, ChatGPT provided correct answers for 6 questions and incorrect answers for 4 questions out of the 10 cases that were used. But, to our surprise, for case 3, different answers were obtained with multiple attempts. We believe this to have happened owing to the complexity of the case, which involved addressing various critical medical aspects related to amino acid metabolism in a balanced approach.
CONCLUSIONS: According to the findings of our study, ChatGPT may not be considered an accurate information provider for application in medical education to improve learning and assessment. However, our study was limited by a small sample size (10 clinical case vignettes) and the use of the publicly available version of ChatGPT (version 3.5). Although artificial intelligence (AI) has the capability to transform medical education, we emphasize the validation of such data produced by such AI systems for correctness and dependability before it could be implemented in practice.

BACKGROUND: ChatGPT has shown impressive performance in national medical licensing examinations, such as the United States Medical Licensing Examination (USMLE), even passing it with expert-level performance. However, there is a lack of research on its performance in low-income countries\' national licensing medical examinations. In Peru, where almost one out of three examinees fails the national licensing medical examination, ChatGPT has the potential to enhance medical education.
OBJECTIVE: We aimed to assess the accuracy of ChatGPT using GPT-3.5 and GPT-4 on the Peruvian National Licensing Medical Examination (Examen Nacional de Medicina [ENAM]). Additionally, we sought to identify factors associated with incorrect answers provided by ChatGPT.
METHODS: We used the ENAM 2022 data set, which consisted of 180 multiple-choice questions, to evaluate the performance of ChatGPT. Various prompts were used, and accuracy was evaluated. The performance of ChatGPT was compared to that of a sample of 1025 examinees. Factors such as question type, Peruvian-specific knowledge, discrimination, difficulty, quality of questions, and subject were analyzed to determine their influence on incorrect answers. Questions that received incorrect answers underwent a three-step process involving different prompts to explore the potential impact of adding roles and context on ChatGPT\'s accuracy.
RESULTS: GPT-4 achieved an accuracy of 86% on the ENAM, followed by GPT-3.5 with 77%. The accuracy obtained by the 1025 examinees was 55%. There was a fair agreement (κ=0.38) between GPT-3.5 and GPT-4. Moderate-to-high-difficulty questions were associated with incorrect answers in the crude and adjusted model for GPT-3.5 (odds ratio [OR] 6.6, 95% CI 2.73-15.95) and GPT-4 (OR 33.23, 95% CI 4.3-257.12). After reinputting questions that received incorrect answers, GPT-3.5 went from 41 (100%) to 12 (29%) incorrect answers, and GPT-4 from 25 (100%) to 4 (16%).
CONCLUSIONS: Our study found that ChatGPT (GPT-3.5 and GPT-4) can achieve expert-level performance on the ENAM, outperforming most of our examinees. We found fair agreement between both GPT-3.5 and GPT-4. Incorrect answers were associated with the difficulty of questions, which may resemble human performance. Furthermore, by reinputting questions that initially received incorrect answers with different prompts containing additional roles and context, ChatGPT achieved improved accuracy.

UNASSIGNED: As the novel coronavirus 2019 (COVID-19) continues its pandemic surge globally along with its social distancing norms, the physical conduction of practical examinations for medical graduates and postgraduates has become difficult. Software-based systems and social media platforms could provide alternatives for ensuring regular medical education and exam-oriented assessments. In this context, we evaluated our own experience with virtual conduction of semester practical exams for medical graduates.
UNASSIGNED: This prospective study was conducted in Gynaecology and Obstetrics department. We employed live streaming educational video conferencing software for virtual consultation between medical students, patients (case presentations), internal and external examiners. The outcomes were evaluated in terms of conduction of various components of practical examination-Viva, case presentations, instruments, slides, specimen examination. Statistical analysis was performed by descriptive statistics through Microsoft Excel sheet.
UNASSIGNED: Virtual conduction examination/evaluation was performed on 150 medical students by examiners from a distant location. No problems occurred except few short duration (less than 5 min) interruptions due to internet connectivity issues. 125/150 (83.5%) of medical students and all examiners (2 internal and 2 external) expressed satisfaction with virtual medical evaluation.
UNASSIGNED: 83.5% of medical students and all examiners expressed satisfaction with virtual medical evaluation during this COVID pandemic. Our findings suggest that virtual conduction of practical annual medical exams through virtual video conferencing platform appears to be an optimal alternative during COVID pandemic.

BACKGROUND: Medical examination of the adult population is aimed at diagnosing chronic noncommunicable diseases and their risk factors. The unreasonable choice of screening methods and information processing can lead to the unjustified waste of resources, with little benefit or even damage to the health of population and to the distortion of the statistic information.
OBJECTIVE: To evaluate the quality of medical examinations for chronic noncommunicable diseases among the adult population of the Irkutsk region from 2013 to 2017.
METHODS: We analyzed the Adult Clinical Examination report N 131 using comparative and statistical methods. It was selected for this study because it provides a summary of the findings from the Chronic Non-Communicable Diseases surveys from 2013 to 2017 and thus precluded unnecessary investment of time and labor. The report comprises sections 1000 to 7000, which provided medical examination data, such as demographic information and statistics on various diseases, including neoplasms.
RESULTS: The years 2016 and 2017 were notable for the emergence of 567 new cancers, which accounted for 12.9% of total diagnoses. In 2017, there were 115 192 patients with cardiovascular diseases, a fivefold increase from 2013. Among the neurological dysfunctions, 0.9% were ischemia attacks and related syndromes. The remaining 99.1% were not highlighted in the report. The respiratory system diseases were pneumonia, bronchitis, chronic obstructive pulmonary disease (COPD), asthma, asthmatic status, and bronchiectasis. These diseases made up 68.3% of all pathologies of the respiratory system. The remaining 11 327 cases were not classified nosologically.
CONCLUSIONS: Every section of the N 131 report showed significant inconsistencies among the summary survey results for both the Irkutsk Region and Russia. This could result in a misunderstanding of disease prevalence and, consequently, in improper decision making. At this point, approaches to statistical analysis of health surveys must be reconsidered on a national scale.

OBJECTIVE: Custody conditions in police cells are often demeaning and considered inappropriate for human beings. The detention of young adolescents in police custody has received little attention. Our study aimed to describe the characteristics of adolescents under 18 detained in custody.
METHODS: We studied all arrestees aged 13-17 examined in 1 year (January 01-December 31, 2014) in a suburban district near Paris. We evaluated the proportion of adolescents under 18 among all arrestees detained in custody and their medical history, addictive behaviors, perceived health status, and opinion on custody.
RESULTS: Arrestees aged 13-17 accounted for 1859 individuals. They were predominantly males (94%) and accounted for 19% of all examinations in custody. Nearly half of the arrestees aged 13-15 (42%), and two thirds of those aged 16-17 (65%) had been previously detained in police cells. Somatic and psychiatric disorders were reported by 7% and 4%, respectively, of arrestees aged 13-17. Alcohol, tobacco, and cannabis consumption were reported by 5%, 24%, and 12%, respectively, of arrestees aged 13-15. These proportions were lower than the 16%, 50%, and 35%, respectively, reported by arrestees aged 16-17 (p < 0.0001). Assaults were reported by 18% of arrestees aged 13-17. They had a fair, bad, or very bad opinion on custody in 43% of cases.
CONCLUSIONS: The detention of adolescents in police stations is commonly associated with assaults at the time of arrest. High proportions of adolescent arrestees smoke tobacco or cannabis. We suggest that the medical examination in custody could be an opportunity for adolescents to initiate access to health care.

BACKGROUND: Little information is available regarding the medical status and health care needs of female arrestees. Our objective was to evaluate the perceived health and somatic or psychiatric disorders reported by female arrestees in police cells.
METHODS: We conducted an observational study in a regional reference department of forensic medicine in France. We studied female arrestees examined in police cells (01/01/2013-06/30/2013). Data were collected regarding individuals\' medical characteristics, addictive behaviours, and perceived health status, as well as reported assaults or recent traumatic injuries. We recorded medical decisions regarding fitness for detention in police cells.
RESULTS: A total of 438 women (median age, 29; range, 13-67) accounted for 5% of the 7408 examined arrestees. Females considered their overall health as good or very good in 314/395 cases (70%). Women reported chronic somatic or psychiatric disorders more frequently than men (89/379, 23% vs. 757/6,135, 12%, p < 0.001 and 59/379, 15% vs. 392/6319, 6%, p < 0.001, respectively). Daily tobacco consumption and cannabis use were reported by 255/403 (63%) and 98/438 female arrestees (22%), respectively. Physical assaults were reported in 113/415 cases (27%). Female arrestees were considered fit for detention in 92% of cases. Among 24 pregnant arrestees, 6 (25%) were unfit for detention, 2 (8%) were fit for custody during daytime only and 16 (67%) were fit for detention if certain conditions were met.
CONCLUSIONS: Detention in police custody involves a minority of females. Females are older and report somatic or psychiatric disorders more frequently than males.