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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.
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The COVID-19 pandemic has led to significant changes in healthcare practices, including increased antibiotic usage. This study aimed to investigate the impact of the pandemic on the prevalence of extended-spectrum ß-lactamase (ESBL) production and carbapenem resistance among key bacterial species causing urinary tract infections (UTIs). Conducted at King Fahad Medical City in Riyadh from January 2018 to December 2022, the study analyzed urine samples from 9697 UTI patients. Patients were categorized into 'pre-COVID-19' and 'during COVID-19' groups. Bacterial isolates were identified, and antimicrobial susceptibility testing was performed following guidelines. ESBL production was detected using the Double-Disc Synergy Test. Escherichia coli and Klebsiella pneumoniae were the main pathogens. During the pandemic, ESBL production decreased in E. coli by 1.9% and in K. pneumoniae by 6.0%. Carbapenem resistance also declined, with E. coli displaying a 1.2% reduction and K. pneumoniae and Pseudomonas aeruginosa displaying 10.7% and 7.9% reductions, respectively. Notably, logistic regression analysis revealed that the odds of ESBL presence were 10% lower during the COVID-19 pandemic (OR 0.91; 95% CI 0.83-0.99; p = 0.040), and there was a significant reduction in the odds of carbapenem resistance (OR 0.43; 95% CI 0.37-0.51; p < 0.001). This study reveals a significant decrease in ESBL production and carbapenem resistance among UTI pathogens during the COVID-19 pandemic, hinting at the impact of modified antibiotic and healthcare approaches. It emphasizes the need for persistent antimicrobial resistance surveillance and policy adaptation to address resistance challenges, offering key directions for future public health actions.
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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.
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Background: Palliative care (PC) plays a crucial role in improving the quality of life for terminally ill patients and their families. In Saudi Arabia, the Reform of Healthcare Vision 2030 has recognized the importance of PC and aimed to enhance its availability and quality. Objectives: This study evaluates the current state of PC in Saudi Arabia post-Vision 2030 reforms. Design: A cross-sectional survey-based research was conducted at a ministry of health health care facility to assess the accessibility and quality of PC services. Setting/Subjects: The survey collected quantitative and qualitative data from PC managers in Saudi Arabia. Retrospective analysis of annual death records determined the demand for PC. Results: The results indicate notable progress in developing PC services in Saudi Arabia, including increased number of PC units, community home care services, outpatient services, and consultations. However, challenges persist in terms of geographical distribution, resource allocation, and availability of pain medications, particularly opioids. The study highlights the substantial need for PC for both cancer and noncancer patients, emphasizing the importance of expanding these services. Conclusions: To further improve PC, policymakers and stakeholders should prioritize resource allocation, health care workforce, and access to pain medications. These efforts will address the growing demand for PC and benefit terminally ill patients and their families in Saudi Arabia.
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Reforma de la Atención de Salud , Cuidados Paliativos , Humanos , Arabia Saudita , Estudios Transversales , Accesibilidad a los Servicios de Salud , Estudios Retrospectivos , Masculino , Femenino , Adulto , Persona de Mediana Edad , Encuestas y CuestionariosRESUMEN
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.
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This editorial discusses the role of artificial intelligence (AI) chatbots in the healthcare sector, emphasizing their potential as supplements rather than substitutes for medical professionals. While AI chatbots have demonstrated significant potential in managing routine tasks, processing vast amounts of data, and aiding in patient education, they still lack the empathy, intuition, and experience intrinsic to human healthcare providers. Furthermore, the deployment of AI in medicine brings forth ethical and legal considerations that require robust regulatory measures. As we move towards the future, the editorial underscores the importance of a collaborative model, wherein AI chatbots and medical professionals work together to optimize patient outcomes. Despite the potential for AI advancements, the likelihood of chatbots completely replacing medical professionals remains low, as the complexity of healthcare necessitates human involvement. The ultimate aim should be to use technology like AI chatbots to enhance patient care and outcomes, not to replace the irreplaceable human elements of healthcare.
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BACKGROUND: One of the most prevalent bacterial infections in children is urinary tract infection (UTI), which has become a major concern with increasing resistance of the pathogens to the routinely used antimicrobial agents. The aim of the study is to determine the antimicrobial susceptibility patterns of pediatric UTI-causing pathogens, including ESBL-producing bacteria, in Saudi Arabia. METHODS: This cross-sectional retrospective study was conducted to ascertain the frequency of isolation and the antimicrobial resistance pattern of uropathogens among children aged 0-15 years. The data from the urine cultures was collected during 2019-2020 at the King Fahad Medical City, a major tertiary hospital in Riyadh, Saudi Arabia. A total of 1022 urine samples from patients diagnosed with urinary tract infections (UTIs) were collected for this study. Microbial species present in the samples were cultured and identified using standard biochemical techniques. To assess the resistance of these strains to antimicrobial drugs, an in vitro method was employed, and the criteria set by the Clinical Laboratory Standard Institute (CLSI) were followed. In addition, a double-disc synergy test was conducted to identify strains of E. coli that produce extended-spectrum beta-lactamase (ESBL). RESULTS: The predominant pathogens were E. coli (58.6%), followed by Klebsiella sp. (23.9%). E. coli isolates were more sensitive to meropenem and ertapenem in 99.2% of cases, followed by amikacin (99%). Klebsiella sp. were sensitive to amikacin in 97.1% of cases, followed by meropenem and ertapenem (92.2% in both). The highest sensitivities of antimicrobials toward ESBL were for meropenem and ertapenem (100% in both), followed by amikacin (99%). CONCLUSIONS: Our study recommends using local antibiotic sensitivity data for empirical UTI treatment. Amikacin, ertapenem, and meropenem are effective intravenous options. Cephalosporin, cefuroxime, amoxicillin/clavulanic acid, and nitrofurantoin are suitable oral choices. No significant changes in antimicrobial susceptibility were observed during the COVID-19 pandemic. Further research is needed to assess potential pandemic-related alterations.