ChatGPT's ability to comprehend and answer cirrhosis related questions in Arabic.

BACKGROUND AND STUDY AIMS: Cirrhosis is a chronic progressive disease which requires complex care. Its incidence is rising in the Arab countries making it the 7th leading cause of death in the Arab League in 2010. ChatGPT is a large language model with a growing body of literature demonstrating its ability to answer clinical questions. We examined ChatGPT's accuracy in responding to cirrhosis related questions in Arabic and compared its performance to English. MATERIALS AND METHODS: ChatGPTs responses to 91 questions in Arabic and English were graded by a transplant hepatologist fluent in both languages. Accuracy of responses was assessed using the scale: 1. Comprehensive, 2. Correct but inadequate, 3. Mixed with correct and incorrect/outdated data, and 4. Completely incorrect.Accuracy of Arabic compared to English responses was assessed using the scale: 1. Arabic response is more accurate, 2. Similar accuracy, 3. Arabic response is less accurate. RESULTS: The model provided 22 (24.2%) comprehensive, 44 (48.4%) correct but inadequate, 13 (14.3%) mixed with correct and incorrect/outdated data and 12 (13.2%) completely incorrect Arabic responses. When comparing the accuracy of Arabic and English responses, 9 (9.9%) of the Arabic responses were graded as more accurate, 52 (57.1%) similar in accuracy and 30 (33.0%) as less accurate compared to English. CONCLUSION: ChatGPT has the potential to serve as an adjunct source of information for Arabic speaking patients with cirrhosis. The model provided correct responses in Arabic to 72.5% of questions, although its performance in Arabic was less accurate than in English. The model produced completely incorrect responses to 13.2% of questions, reinforcing its potential role as an adjunct and not replacement of care by licensed healthcare professionals. Future studies to refine this technology are needed to help Arabic speaking patients with cirrhosis across the globe understand their disease and improve their outcomes.

Assessing the Accuracy of Responses by the Language Model ChatGPT to Questions Regarding Bariatric Surgery.

PURPOSE: ChatGPT is a large language model trained on a large dataset covering a broad range of topics, including the medical literature. We aim to examine its accuracy and reproducibility in answering patient questions regarding bariatric surgery. MATERIALS AND METHODS: Questions were gathered from nationally regarded professional societies and health institutions as well as Facebook support groups. Board-certified bariatric surgeons graded the accuracy and reproducibility of responses. The grading scale included the following: (1) comprehensive, (2) correct but inadequate, (3) some correct and some incorrect, and (4) completely incorrect. Reproducibility was determined by asking the model each question twice and examining difference in grading category between the two responses. RESULTS: In total, 151 questions related to bariatric surgery were included. The model provided "comprehensive" responses to 131/151 (86.8%) of questions. When examined by category, the model provided "comprehensive" responses to 93.8% of questions related to "efficacy, eligibility and procedure options"; 93.3% related to "preoperative preparation"; 85.3% related to "recovery, risks, and complications"; 88.2% related to "lifestyle changes"; and 66.7% related to "other". The model provided reproducible answers to 137 (90.7%) of questions. CONCLUSION: The large language model ChatGPT often provided accurate and reproducible responses to common questions related to bariatric surgery. ChatGPT may serve as a helpful adjunct information resource for patients regarding bariatric surgery in addition to standard of care provided by licensed healthcare professionals. We encourage future studies to examine how to leverage this disruptive technology to improve patient outcomes and quality of life.

Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma.

BACKGROUND/AIMS: Patients with cirrhosis and hepatocellular carcinoma (HCC) require extensive and personalized care to improve outcomes. ChatGPT (Generative Pre-trained Transformer), a large language model, holds the potential to provide professional yet patient-friendly support. We aimed to examine the accuracy and reproducibility of ChatGPT in answering questions regarding knowledge, management, and emotional support for cirrhosis and HCC. METHODS: ChatGPT's responses to 164 questions were independently graded by two transplant hepatologists and resolved by a third reviewer. The performance of ChatGPT was also assessed using two published questionnaires and 26 questions formulated from the quality measures of cirrhosis management. Finally, its emotional support capacity was tested. RESULTS: We showed that ChatGPT regurgitated extensive knowledge of cirrhosis (79.1% correct) and HCC (74.0% correct), but only small proportions (47.3% in cirrhosis, 41.1% in HCC) were labeled as comprehensive. The performance was better in basic knowledge, lifestyle, and treatment than in the domains of diagnosis and preventive medicine. For the quality measures, the model answered 76.9% of questions correctly but failed to specify decision-making cut-offs and treatment durations. ChatGPT lacked knowledge of regional guidelines variations, such as HCC screening criteria. However, it provided practical and multifaceted advice to patients and caregivers regarding the next steps and adjusting to a new diagnosis. CONCLUSION: We analyzed the areas of robustness and limitations of ChatGPT's responses on the management of cirrhosis and HCC and relevant emotional support. ChatGPT may have a role as an adjunct informational tool for patients and physicians to improve outcomes.

Excess psoriasis and psoriatic arthritis mortality during the COVID-19 pandemic in the United States: A nationwide population-based study from 2010 to 2021.

BACKGROUND: Little is known about mortality trends among patients with psoriasis (PsO) and psoriatic arthritis (PsA) in the United States. OBJECTIVES: To ascertain mortality trends of PsO and PsA between 2010 and 2021, focusing on the effects of the COVID-19 pandemic. METHODS: We collected data from the National Vital Statistic System and calculated age-standardized mortality rates (ASMR) and cause-specific mortality for PsO/PsA. We evaluated observed versus predicted mortality for 2020-2021 based on trends from 2010 to 2019 with joinpoint and prediction modelling analysis. RESULTS: Among 5810 and 2150 PsO- and PsA-related deaths between 2010 and 2021, ASMR for PsO dramatically increased between 2010-2019 and 2020-2021 (annual percentage change [APC] 2.07% vs. 15.26%; p < 0.01), leading to a higher observed ASMR (per 100,000 persons) than predicted for 2020 (0.27 vs. 0.22) and 2021 (0.31 vs. 0.23). The excess mortality of PsO was 22.7% and 34.8% higher than that in the general population in 2020 (16.4%, 95% CI: 14.9%-17.9%) and 2021 (19.8%, 95% CI: 18.0%-21.6%) respectively. Notably, the ASMR rise for PsO was most pronounced in the female (APC: 26.86% vs. 12.19% in males) and the middle-aged group (APC: 17.67% vs. 12.47% in the old-age group). ASMR, APC and excess mortality for PsA were similar to PsO. SARS-CoV-2 infection contributed to more than 60% of the excess mortality for PsO and PsA. CONCLUSIONS: Individuals living with PsO and PsA were disproportionately affected during the COVID-19 pandemic. Both ASMRs increased at an alarming rate, with the most pronounced disparities among the female and middle-aged groups.