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INTRODUCTION: The integration of artificial intelligence (AI) in healthcare, particularly through language models like ChatGPT and ChatSonic, has gained substantial attention. This article explores the utilization of these AI models to address patient queries related to hypertension, emphasizing their potential to enhance health literacy and disease understanding. The study aims to compare the quality and reliability of responses generated by ChatGPT and ChatSonic in addressing common patient queries about hypertension and evaluate these AI models using the Global Quality Scale (GQS) and the Modified DISCERN scale. METHODS: A virtual cross-sectional observational study was conducted over one month, starting in October 2023. Ten common patient queries regarding hypertension were presented to ChatGPT (https://chat.openai.com/) and ChatSonic (https://writesonic.com/chat), and the responses were recorded. Two internal medicine physicians assessed the responses using the GQS and the Modified DISCERN scale. Statistical analysis included Cohen's Kappa values for inter-rater agreement. RESULTS: The study evaluated responses from ChatGPT and ChatSonic for 10 patient queries. Assessors observed variations in the quality and reliability assessments between the two AI models. Cohen's Kappa values indicated minimal agreement between the evaluators for both the GQS and Modified DISCERN scale. CONCLUSIONS: This study highlights the variations in the assessment of responses generated by ChatGPT and ChatSonic for hypertension-related queries. The findings highlight the need for ongoing monitoring and fact-checking of AI-generated responses.
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PURPOSE: SARS-CoV-2 had a significant impact on public health since its declaration as a pandemic. It is linked to a high rate of multiple organ dysfunction syndrome (MODS) and a slew of long-term symptoms that are yet to be thoroughly investigated. Among these, genitourinary symptoms of an overactive bladder (increased frequency, urgency, and nocturia) have recently been identified and labeled as COVID-associated cystitis (CAC). This current research is performed to review this phenomenon. METHODS: A literature search was performed in MEDLINE, Cochrane, and Google Scholar databases and 185 articles were obtained in total, including reviews and trials involving CAC, which were screened using various methods, and 42 articles were gathered for the review. RESULTS: Among its multitude of symptoms, overactive bladder (OAB) leads to poorer outcomes. The inflammatory mediator-based theory and the ACE-2 receptor-based theory are two probable theories for how it harms the bladder urothelium. The expression of ACE-2 receptors during the pathogenesis of CAC warrants further investigation as ACE modulation may reveal more information about COVID-19 complications. Other comorbidities, immunocompromised patients, or patients with a history of urinary tract infections can also exacerbate this condition. CONCLUSION: The scarce literature collected related to CAC gives us an insight into the symptomatology, pathophysiology, and possible treatment plans. Treatment choices are diverse among COVID-19-afflicted and unaffected patients for treating urinary symptoms which highlights the importance to distinguish between the two. CAC shows greater prevalence and morbidity when linked to other conditions, thereby warranting future developments in it.