Fadi Aljamaan

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.

Background: COVID-19 is a respiratory disease that eventually became a pandemic, with 300 million people infected around the world. Alongside the improvement in COVID-19 management and vaccine development, identifying biomarkers for COVID-19 has recently been reported to help in early prediction and managing severe cases, which might improve outcomes. Our study aimed to find out if there is any correlation between clinical severity and elevated hematological and biochemical markers in COVID-19 patients and its effect on the outcome. Methods: We have collected retrospective data on socio-demographics, medical history, biomarkers, and disease outcomes from five hospitals and health institutions in the Kingdom of Saudi Arabia. Results: Pneumonia was the most common presentation of COVID-19 in our cohort. The presence of abnormal inflammatory biomarkers (D-dimer, CRP, troponin, LDH, ferritin, and t white blood cells) was significantly associated with unstable COVID-19 disease. In addition, patients with evidence of severe respiratory disease, particularly those who required mechanical ventilation, had higher biomarkers when compared to those with stable respiratory conditions (p < 0.001). Conclusion: Identifying biomarkers predicts outcomes for COVID-19 patients and may significantly help in their management.