Virtual Objective Structured Clinical Examination (OSCE) Training in the Pandemic Era: Feasibility, Satisfaction, and the Road Ahead.

INTRODUCTION: Objective Structured Clinical Examinations (OSCEs) are essential assessments for evaluating the clinical competencies of medical students. The COVID-19 pandemic caused a significant disruption in medical education, prompting institutions to adopt virtual formats for academic activities. This study analyzes the feasibility, satisfaction, and experiences of pediatric board candidates and faculty during virtual or electronic OSCE (e-OSCE) training sessions using Zoom video communication (Zoom Video Communications, Inc., San Jose, USA). METHODS: This is a post-event survey assessing the perceptions of faculty and candidates and the perceived advantages and obstacles of e-OSCE. RESULTS: A total of 142 participants were invited to complete a post-event survey, and 105 (73.9%) completed the survey. There was equal gender representation. More than half of the participants were examiners. The overall satisfaction with the virtual e-OSCE was high, with a mean score of 4.7±0.67 out of 5. Most participants were likely to recommend e-OSCE to a friend or colleague (mean score 8.84±1.51/10). More faculty (66.1%) than candidates (40.8%) preferred e-OSCE (P=0.006). CONCLUSION: Transitioning to virtual OSCE training during the pandemic proved feasible, with high satisfaction rates. Further research on virtual training for OSCE in medical education is recommended to optimize its implementation and outcomes.

The scientific knowledge of three large language models in cardiology: multiple-choice questions examination-based performance.

Background: The integration of artificial intelligence (AI) chatbots like Google's Bard, OpenAI's ChatGPT, and Microsoft's Bing Chatbot into academic and professional domains, including cardiology, has been rapidly evolving. Their application in educational and research frameworks, however, raises questions about their efficacy, particularly in specialized fields like cardiology. This study aims to evaluate the knowledge depth and accuracy of these AI chatbots in cardiology using a multiple-choice question (MCQ) format. Methods: The study was conducted as an exploratory, cross-sectional study in November 2023 on a bank of 100 MCQs covering various cardiology topics that was created from authoritative textbooks and question banks. These MCQs were then used to assess the knowledge level of Google's Bard, Microsoft Bing, and ChatGPT 4.0. Each question was entered manually into the chatbots, ensuring no memory retention bias. Results: The study found that ChatGPT 4.0 demonstrated the highest knowledge score in cardiology, with 87% accuracy, followed by Bing at 60% and Bard at 46%. The performance varied across different cardiology subtopics, with ChatGPT consistently outperforming the others. Notably, the study revealed significant differences in the proficiency of these chatbots in specific cardiology domains. Conclusion: This study highlights a spectrum of efficacy among AI chatbots in disseminating cardiology knowledge. ChatGPT 4.0 emerged as a potential auxiliary educational resource in cardiology, surpassing traditional learning methods in some aspects. However, the variability in performance among these AI systems underscores the need for cautious evaluation and continuous improvement, especially for chatbots like Bard, to ensure reliability and accuracy in medical knowledge dissemination.

Transforming Virtual Healthcare: The Potentials of ChatGPT-4omni in Telemedicine.

The introduction of OpenAI's ChatGPT-4omni (GPT-4o) represents a potential advancement in virtual healthcare and telemedicine. GPT-4o excels in processing audio, visual, and textual data in real time, offering possible enhancements in understanding natural language in both English and non-English contexts. Furthermore, the new "Temporary Chat" feature may improve privacy and data confidentiality during interactions, potentially increasing integration with healthcare systems. These innovations promise to enhance communication clarity, facilitate the integration of medical images, and increase data privacy in online consultations. This editorial explores some future implications of these advancements for telemedicine, highlighting the necessity for further research on reliability and the integration of advanced language models with human expertise.

Art or Artifact: Evaluating the Accuracy, Appeal, and Educational Value of AI-Generated Imagery in DALL·E 3 for Illustrating Congenital Heart Diseases.

Artificial Intelligence (AI), particularly AI-Generated Imagery, has the potential to impact medical and patient education. This research explores the use of AI-generated imagery, from text-to-images, in medical education, focusing on congenital heart diseases (CHD). Utilizing ChatGPT's DALL·E 3, the research aims to assess the accuracy and educational value of AI-created images for 20 common CHDs. In this study, we utilized DALL·E 3 to generate a comprehensive set of 110 images, comprising ten images depicting the normal human heart and five images for each of the 20 common CHDs. The generated images were evaluated by a diverse group of 33 healthcare professionals. This cohort included cardiology experts, pediatricians, non-pediatric faculty members, trainees (medical students, interns, pediatric residents), and pediatric nurses. Utilizing a structured framework, these professionals assessed each image for anatomical accuracy, the usefulness of in-picture text, its appeal to medical professionals, and the image's potential applicability in medical presentations. Each item was assessed on a Likert scale of three. The assessments produced a total of 3630 images' assessments. Most AI-generated cardiac images were rated poorly as follows: 80.8% of images were rated as anatomically incorrect or fabricated, 85.2% rated to have incorrect text labels, 78.1% rated as not usable for medical education. The nurses and medical interns were found to have a more positive perception about the AI-generated cardiac images compared to the faculty members, pediatricians, and cardiology experts. Complex congenital anomalies were found to be significantly more predicted to anatomical fabrication compared to simple cardiac anomalies. There were significant challenges identified in image generation. Based on our findings, we recommend a vigilant approach towards the use of AI-generated imagery in medical education at present, underscoring the imperative for thorough validation and the importance of collaboration across disciplines. While we advise against its immediate integration until further validations are conducted, the study advocates for future AI-models to be fine-tuned with accurate medical data, enhancing their reliability and educational utility.

ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice.

Artificial intelligence (AI) chatbots, such as ChatGPT, have widely invaded all domains of human life. They have the potential to transform healthcare future. However, their effective implementation hinges on healthcare workers' (HCWs) adoption and perceptions. This study aimed to evaluate HCWs usability of ChatGPT three months post-launch in Saudi Arabia using the System Usability Scale (SUS). A total of 194 HCWs participated in the survey. Forty-seven percent were satisfied with their usage, 57 % expressed moderate to high trust in its ability to generate medical decisions. 58 % expected ChatGPT would improve patients' outcomes, even though 84 % were optimistic of its potential to improve the future of healthcare practice. They expressed possible concerns like recommending harmful medical decisions and medicolegal implications. The overall mean SUS score was 64.52, equivalent to 50 % percentile rank, indicating high marginal acceptability of the system. The strongest positive predictors of high SUS scores were participants' belief in AI chatbot's benefits in medical research, self-rated familiarity with ChatGPT and self-rated computer skills proficiency. Participants' learnability and ease of use score correlated positively but weakly. On the other hand, medical students and interns had significantly high learnability scores compared to others, while ease of use scores correlated very strongly with participants' perception of positive impact of ChatGPT on the future of healthcare practice. Our findings highlight the HCWs' perceived marginal acceptance of ChatGPT at the current stage and their optimism of its potential in supporting them in future practice, especially in the research domain, in addition to humble ambition of its potential to improve patients' outcomes particularly in regard of medical decisions. On the other end, it underscores the need for ongoing efforts to build trust and address ethical and legal concerns of AI implications in healthcare. The study contributes to the growing body of literature on AI chatbots in healthcare, especially addressing its future improvement strategies and provides insights for policymakers and healthcare providers about the potential benefits and challenges of implementing them in their practice.

Navigating Novel Uncertainties of COVID-19: The Rise of the JN.1 Variant.

In the shadow of the coronavirus disease 2019 (COVID-19) pandemic, the emergence of the JN.1 variant highlights the need for continued vigilance. This Editorial examines the characteristics of JN.1, derived from BA.2.86, and how it affects global public health. Despite its mutation on the spike protein and rapid spread, there has been no increase in disease severity, particularly in terms of ICU admissions, as evidenced by data from the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC). We emphasize the importance of continued surveillance, vaccine adaptation, and public health preparedness while advocating for a balanced response to effectively manage the post-pandemic era. It reflects on the resilience built through vaccination efforts and the need for international cooperation to navigate the way forward in the face of additional severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants.

The socioeconomic burden of spinal muscular atrophy in Saudi Arabia: a cross-sectional pilot study.

Background: Spinal muscular atrophy (SMA) is a rare debilitating condition with a significant burden for patients and society. However, little is known about how it affects Saudi Arabia's population. The socioeconomic and medical characteristics of affected SMA patients and their caregivers are lacking. Purpose: This study aimed to describe the socioeconomic and medical characteristics of SMA patients and caregivers in Saudi Arabia. Patients and methods: A cross-sectional questionnaire-based study was conducted using snowball sampling. Assessment tools including EuroQol (EQ-5D-5L) and visual analog scale (EQ-VAS), Generalized Anxiety Disorder 7-item (GAD-7), Patient Health Questionnaire (PHQ-9), and Costs for Patients Questionnaire (CoPaQ) were used to assess the quality of life (QoL), anxiety, depression, and out-of-pocket expenditures. Results: Sixty-four caregivers of SMA patients participated. Type I patients had higher sibling concordance, ICU hospitalization, and mechanical support needs. Type III patients had better QoL. Type I patients' caregivers had higher depression scores. Type III patients' caregivers had higher out-of-pocket expenditures. Forty-eight percent received supportive care, while others received SMA approved therapies. Conclusion: SMA imposes a significant socioeconomic burden on patients and caregivers, requiring more attention from the healthcare system. Access to innovative therapies varied across SMA types. Pre-marital screening and early detection are crucial to reduce disease incidence and ensure timely treatment.

Insight into prevalence, etiology, and modalities of pediatric chronic dialysis: a comprehensive nationwide analysis.

BACKGROUND: This study aimed to determine the prevalence and etiology of kidney failure (KF) among children below 15 years of age receiving chronic dialysis in Saudi Arabia and describe their dialysis modalities. METHODS: This cross-sectional descriptive study was conducted on 8 August 2022, encompassing all 23 pediatric dialysis centers in Saudi Arabia. Data gathered comprised patient demographics, causes of KF, and the dialysis methods employed. Collected data underwent analysis to determine prevalence of children undergoing chronic dialysis, discern underlying causes of KF, and evaluate distribution of patients across different dialysis modalities. RESULTS: The prevalence of children on chronic dialysis is 77.6 per million children living in Saudi Arabia, equating to 419 children. The predominant underlying cause of KF was congenital anomalies of the kidneys and urinary tract (CAKUT), representing a substantial 41% of cases. Following this, others or unknown etiologies accounted for a noteworthy 25% of cases, with focal segmental glomerulosclerosis (FSGS) comprising 13%, glomerulonephritis at 11%, and congenital nephrotic syndrome contributing 10% to etiological distribution. Regarding dialysis modalities employed, 67% of patients were on peritoneal dialysis (PD), while the remaining 33% were on hemodialysis (HD). CONCLUSIONS: This first nationwide study of pediatric chronic dialysis in Saudi Arabia sheds light on the prevalence of children undergoing chronic dialysis and underlying causes of their KF, thereby contributing to our understanding of clinical management considerations. This research serves as a stepping stone for the development of national registries.

Assessing Knowledge, Acceptance, and Anticipated Impact of Telepathology in Saudi Arabia: Insights From Healthcare Workers and Patients.

INTRODUCTION: Telepathology, a rapidly evolving field in modern healthcare, has the potential to significantly impact the diagnosis and management of diseases. This study aimed to assess the prevalence of acceptance and knowledge, the likelihood of future use, and the perceived advantages and disadvantages of telepathology among healthcare workers (HCWs) and patients in Saudi Arabia. METHODS: A cross-sectional study was conducted with 388 participants, including 179 HCWs and 209 adult patients across Saudi Arabia. Data were collected using a bilingual, self-administered, and anonymous computer-based questionnaire. The Statistical Package for Social Sciences (SPSS, IBM Corp., Armonk, NY) was employed for data analysis. RESULTS: The participants had an average knowledge rate of 80.3% (n=312) concerning telepathology. A substantial 88.16% (n=342) were inclined towards its acceptance, and an optimistic 89.97% (n=349) foresaw its potential utility. Among the respondents, 70% (n=272) pinpointed "expedited results" as the principal merit of telepathology. However, 60% (n=233) flagged "the necessity for costly infrastructure" as its chief limitation. CONCLUSIONS: The insights derived underscore a prominent knowledge and endorsement of telepathology among the Saudi population and HCWs. Despite certain drawbacks, participants believe that telepathology is feasible and offers numerous benefits that could greatly enhance the healthcare system in Saudi Arabia. Future research should focus on evaluating its practical implementation and efficacy within healthcare facilities.

Awareness, Attitudes, and Willingness: A Cross-Sectional Study of Organ Donation in Saudi Arabia.

BACKGROUND: Organ transplantation is inherently dependent on the availability of organ donors. There is a noticeable paucity of literature addressing the rates of organ donation registration and the awareness of Islamic regulations (Fatwa) regarding organ donation within Saudi Arabia. Our study aimed to evaluate the level of organ donation registration, awareness of Islamic regulations, and knowledge of the Saudi Center for Organ Transplantation (SCOT) within the Saudi society. METHODS: We conducted a cross-sectional survey from 30 March to 9 April 2023. This survey aimed to assess the awareness of Islamic (Fatwa) guidance on organ donation, the role of SCOT, and the rate of organ donation registration facilitated through the Tawakkalna app, the official health passport application in Saudi Arabia. RESULTS: Out of 2329 respondents, 21% had registered as potential deceased organ donors, despite 87% acknowledging the importance of organ donation. Awareness of the Islamic Fatwa regarding organ donation was reported by 54.7% of respondents, and 37% recognized the Fatwa's acceptance of brain death criteria. The likelihood of registration as organ donors was higher among Saudi citizens under 45 years of age, females, healthcare workers (HCWs), individuals with higher education, relatives of patients awaiting organ donations, those informed about the Islamic Fatwas, and those willing to donate organs to friends. Conversely, being over the age of 25, Saudi nationality, employment as an HCW, awareness of SCOT, and prior organ donation registration were predictive of a heightened awareness of Islamic Fatwas. However, perceiving the importance of organ donation correlated with a lower awareness of the Fatwas. Significant positive correlations were found between awareness of SCOT, awareness of Fatwas, and registration for organ donation. CONCLUSIONS: While the Saudi population exhibits a high regard for the importance of organ donation, this recognition is not adequately translated into registration rates. The discrepancy may be attributable to limited awareness of SCOT and the relevant Islamic Fatwas. It is imperative to initiate organ donation awareness campaigns that focus on religious authorization to boost organ donation rates and rectify prevalent misconceptions.

Outcomes of Cardiopulmonary Resuscitation in the Pediatric Intensive Care of a Tertiary Center.

Understanding the factors affecting survival and modifying the preventable factors may improve patient outcomes following cardiopulmonary resuscitation (CPR). The aim of this study was to assess the prevalence and outcomes of cardiac arrest and CPR events in a tertiary pediatric intensive care unit (PICU). Outcomes of interest were the return of spontaneous circulation (ROSC) lasting more than 20 minutes, survival for 24 hours post-CPR, and survival to hospital discharge. We analyzed data from the PICU CPR registry from January 1, 2011 to January 1, 2018. All patients who underwent at least 2 minutes of CPR in the PICU were included. CPR was administered in 65 PICU instances, with a prevalence of 1.85%. The mean patient age was 32.7 months. ROSC occurred in 38 (58.5%) patients, 30 (46.2%) achieved 24-hour survival, and 21 (32.3%) survived to hospital discharge. Younger age ( p < 0.018), respiratory cause ( p < 0.001), bradycardia ( p < 0.018), and short duration of CPR ( p < 0.001) were associated with better outcomes, while sodium bicarbonate, norepinephrine, and vasopressin were associated with worse outcome ( p < 0.009). The off-hour CPR had no impact on the outcome. The patients' cumulative predicted survival declined by an average of 8.7% for an additional 1 minute duration of CPR ( p = 0.001). The study concludes that the duration of CPR, therefore, remains one of the crucial factors determining CPR outcomes and needs to be considered in parallel with the guideline emphasis on CPR quality. The lower survival rate post-ROSC needs careful consideration during parental counseling. Better anticipation and prevention of CPR remain ongoing challenges.

Assessment of Knowledge, Perceptions, and Attitudes During the Global Mpox Outbreak in June 2022: A Cross-Sectional Study From the United Arab Emirates.

Objectives: To examine knowledge, worry, anxiety, and vaccine acceptance for mpox among UAE adults. Methods: An online survey, advertised on academic and social media platform in June 2022 collected data from 959 participants (aged 18 and above) on mpox beliefs, risks, knowledge, worry, anxiety, COVID-19 infection, vaccination, and willingness to receive the mpox vaccine. Bivariate and logistic regression analysis identified associations and predictors between variables. Results: 56% had optimal knowledge of mpox transmission and symptoms. 54% were worried, and 27% experienced anxiety related to the outbreak. Knowledge scores were higher among women, healthcare workers, and those with reliable information sources. High perceived infection risk, changes in precautionary measures, and belief in difficult treatment predicted more worry and anxiety. Higher worry and two or more doses of the COVID-19 vaccine predicted higher likelihood of taking the mpox vaccine. Conclusion: The UAE population showed low knowledge and high worry and anxiety during the global mpox outbreak. Increasing public awareness through targeted educational campaigns is vital. Promoting better understanding of infectious diseases, addressing concerns, and encouraging vaccine uptake can prepare for future outbreaks.

Healthcare's New Horizon With ChatGPT's Voice and Vision Capabilities: A Leap Beyond Text.

The integration of artificial intelligence (AI) in healthcare is responsible for a paradigm shift in medicine. OpenAI's recent augmentation of their Generative Pre-trained Transformer (ChatGPT) large language model (LLM) with voice and image recognition capabilities (OpenAI, Delaware) presents another potential transformative tool for healthcare. Envision a healthcare setting where professionals engage in dynamic interactions with ChatGPT to navigate the complexities of atypical medical scenarios. In this innovative landscape, practitioners could solicit ChatGPT's expertise for concise summarizations and insightful extrapolations from a myriad of web-based resources pertaining to similar medical conditions. Furthermore, imagine patients using ChatGPT to identify abnormalities in medical images or skin lesions. While the prospects are diverse, challenges such as suboptimal audio quality and ensuring data security necessitate cautious integration in medical practice. Drawing insights from previous ChatGPT iterations could provide a prudent roadmap for navigating possible challenges. This editorial explores some possible horizons and potential hurdles of ChatGPT's enhanced functionalities in healthcare, emphasizing the importance of continued refinements and vigilance to maximize the benefits while minimizing risks. Through collaborative efforts between AI developers and healthcare professionals, another fusion of AI and healthcare can evolve into enriched patient care and enhanced medical experience.

Increased blood immune regulatory cells in severe COVID-19 with autoantibodies to type I interferons.

The hallmark of severe COVID-19 is an uncontrolled inflammatory response, resulting from poorly understood immunological dysfunction. While regulatory T (Treg) and B (Breg) cells, as the main elements of immune homeostasis, contribute to the control of hyperinflammation during COVID-19 infection, we hypothesized change in their levels in relation to disease severity and the presence of autoantibodies (auto-Abs) to type I IFNs. Cytometric analysis of blood of 62 COVID-19 patients with different severities revealed an increased proportion of conventional (cTreg; CD25+FoxP3+) and unconventional (uTreg; CD25-FoxP3+) Tregs, as well as the LAG3+ immune suppressive form of cTreg/uTreg, in the blood of severe COVID-19 cases compared to the milder, non-hospitalized cases. The increase in blood levels of cTreg/uTreg, but not LAG3+ cTreg/uTreg subtypes, was even higher among patients with severe COVID-19 and auto-Abs to type I IFNs. Regarding Bregs, compared to the milder, non-hospitalized cases, the proportion of IL-35+ and IL-10+ Bregs was elevated in the blood of severe COVID-19 patients, and to a higher extent in those with auto-Abs to type I IFNs. Moreover, blood levels of cTreg, LAG3+ cTreg/uTreg, and IL-35+ and IL-10+ Breg subtypes were associated with lower blood levels of proinflammatory cytokines such as IL-6, IL-17, TNFα, and IL-1ß. Interestingly, patients who were treated with either tocilizumab and/or a high dose of Vitamin D had higher blood levels of these regulatory cells and better control of the proinflammatory cytokines. These observations suggest that perturbations in the levels of immunomodulatory Tregs and Bregs occur in COVID-19, especially in the presence of auto-Abs to type I IFNs.

ChatGPT Surpasses 1000 Publications on PubMed: Envisioning the Road Ahead.

The exponential growth of ChatGPT in medical literature, amassing over 1000 PubMed citations by August 2023, underscores a pivotal juncture in the convergence of artificial intelligence (AI) and healthcare. This remarkable rise not only showcases its potential to revolutionize medical academia but also indicates its impending influence on patient care and healthcare systems. Notwithstanding this enthusiasm, one-third of these citations are editorials or commentaries, stressing a gap in empirical research. Alongside its potential, there are concerns about ChatGPT becoming a "Weapon of Mass Deception" and the need for rigorous evaluations to counter inaccuracies. The World Association of Medical Editors has released guidelines emphasizing that AI tools should not be manuscript co-authors and advocates for clear disclosures in AI-assisted academic works. Interestingly, ChatGPT achieved its citation milestone within nine months, compared to Google's 14 years. As Large Language Models (LLMs), like ChatGPT, become more integral in healthcare, issues surrounding data protection, patient privacy, and ethical implications gain prominence. As the future of LLM research unfolds, key areas of interest include its efficacy in clinical settings, its role in telemedicine, and its potential in medical education. The journey ahead necessitates a harmonious partnership between the medical community and AI developers, emphasizing both technological advancements and ethical considerations.

Integrating ChatGPT in Medical Education: Adapting Curricula to Cultivate Competent Physicians for the AI Era.

The rapid advancements in artificial intelligence (AI) language models, particularly ChatGPT (OpenAI, San Francisco, California, United States), necessitate the adaptation of medical education curricula to cultivate competent physicians in the AI era. In this editorial, we discuss short-term solutions and long-term adaptations for integrating ChatGPT into medical education. We recommend promoting digital literacy, developing critical thinking skills, and emphasizing evidence-based relevance as quick fixes. Long-term adaptations include focusing on the human factor, interprofessional collaboration, continuous professional development, and research and evaluation. By implementing these changes, medical educators can optimize medical education for the AI era, ensuring students are well prepared for a technologically advanced future in healthcare.

Prevalence and Predictive Factors of Compassion Fatigue among Healthcare Workers in Saudi Arabia: Implications for Well-Being and Support.

Compassion fatigue (CF) poses significant challenges to healthcare workers' (HCWs) well-being. This study aimed to estimate the prevalence of CF and identify its predictive factors among HCWs in all regions of Saudi Arabia (SA). As such, all HCWs from different disciplines in different centers were allowed to participate, resulting in 678 participants. The study tool, distributed between October 2022 and January 2023, consisted of a questionnaire created by the authors based on the Professional Quality of Life Scale (ProQOL). The ProQOL measures the positive (compassion satisfaction [CS]) and negative (CF) effects of helping those who have suffered, noting that burnout (BO) and secondary traumatic stress (STS) are the two subscales that constitute CF. Our findings revealed that 63.9% of HCWs experienced average STS, while 57.2% reported average BO levels. HCWs in the southern and northern regions exhibited higher STS (p-value = 0.003 and 0.010, respectively). Physicians displayed higher BO levels (p-value = 0.024). Higher levels of CS were found among older HCWs (p-value = 0.001) and lower levels among those with more years of experience (p-value = 0.004). Support at work and job, life, and financial income satisfaction were significantly and positively correlated with CS and negatively correlated with BO and STS. These findings highlight the need for tailored awareness campaigns targeting HCWs, particularly physicians, to promote well-being, enhance coping skills, and foster problem-solving techniques. Keywords: burnout; compassion fatigue; compassion satisfaction; healthcare workers; professional quality of life; Saudi Arabia; secondary traumatic stress; medical trainees' well-being.

Snakebite Advice and Counseling From Artificial Intelligence: An Acute Venomous Snakebite Consultation With ChatGPT.

BACKGROUND: Snakebites, particularly from venomous species, present a significant global public health challenge. Access to accurate and timely information regarding snakebite prevention, recognition, and management is crucial for minimizing morbidity and mortality. Artificial intelligence (AI) language models, such as ChatGPT (Chat Generative Pre-trained Transformer), have the potential to revolutionize the dissemination of medical information and improve patient education and satisfaction. METHODS: This study aimed to explore the utility of ChatGPT, an advanced language model, in simulating acute venomous snakebite consultations. Nine hypothetical questions based on comprehensive snakebite management guidelines were posed to ChatGPT, and the responses were evaluated by clinical toxicologists and emergency medicine physicians. RESULTS: ChatGPT provided accurate and informative responses related to the immediate management of snakebites, the urgency of seeking medical attention, symptoms, and health issues following venomous snakebites, the role of antivenom, misconceptions about snakebites, recovery, pain management, and prevention strategies. The model highlighted the importance of seeking professional medical care and adhering to healthcare practitioners' advice. However, some limitations were identified, including outdated knowledge, lack of personalization, and inability to consider regional variations and individual characteristics. CONCLUSION: ChatGPT demonstrated proficiency in generating intelligible and well-informed responses related to venomous snakebites. It offers accessible and real-time advice, making it a valuable resource for preliminary information, education, and triage support in remote or underserved areas. While acknowledging its limitations, such as the need for up-to-date information and personalized advice, ChatGPT can serve as a supplementary source of information to complement professional medical consultation and enhance patient education. Future research should focus on addressing the identified limitations and establishing region-specific guidelines for snakebite management.

ChatGPT and the Future of Digital Health: A Study on Healthcare Workers' Perceptions and Expectations.

This study aimed to assess the knowledge, attitudes, and intended practices of healthcare workers (HCWs) in Saudi Arabia towards ChatGPT, an artificial intelligence (AI) Chatbot, within the first three months after its launch. We also aimed to identify potential barriers to AI Chatbot adoption among healthcare professionals. A cross-sectional survey was conducted among 1057 HCWs in Saudi Arabia, distributed electronically via social media channels from 21 February to 6 March 2023. The survey evaluated HCWs' familiarity with ChatGPT-3.5, their satisfaction, intended future use, and perceived usefulness in healthcare practice. Of the respondents, 18.4% had used ChatGPT for healthcare purposes, while 84.1% of non-users expressed interest in utilizing AI Chatbots in the future. Most participants (75.1%) were comfortable with incorporating ChatGPT into their healthcare practice. HCWs perceived the Chatbot to be useful in various aspects of healthcare, such as medical decision-making (39.5%), patient and family support (44.7%), medical literature appraisal (48.5%), and medical research assistance (65.9%). A majority (76.7%) believed ChatGPT could positively impact the future of healthcare systems. Nevertheless, concerns about credibility and the source of information provided by AI Chatbots (46.9%) were identified as the main barriers. Although HCWs recognize ChatGPT as a valuable addition to digital health in the early stages of adoption, addressing concerns regarding accuracy, reliability, and medicolegal implications is crucial. Therefore, due to their unreliability, the current forms of ChatGPT and other Chatbots should not be used for diagnostic or treatment purposes without human expert oversight. Ensuring the trustworthiness and dependability of AI Chatbots is essential for successful implementation in healthcare settings. Future research should focus on evaluating the clinical outcomes of ChatGPT and benchmarking its performance against other AI Chatbots.