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Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, with early detection playing a crucial role in improving survival rates. Artificial intelligence (AI), particularly in medical image analysis, has emerged as a potential tool for HCC diagnosis and surveillance. Recent advancements in deep learning-driven medical imaging have demonstrated significant potential in enhancing early HCC detection, particularly in ultrasound (US)-based surveillance. This review provides a comprehensive analysis of the current landscape, challenges, and future directions of AI in HCC surveillance, with a specific focus on the application in US imaging. Additionally, it explores AI’s transformative potential in clinical practice and its implications for improving patient outcomes. We examine various AI models developed for HCC diagnosis, highlighting their strengths and limitations, with a particular emphasis on deep learning approaches. Among these, convolutional neural networks have shown notable success in detecting and characterising different focal liver lesions on B-mode US often outperforming conventional radiological assessments. Despite these advancements, several challenges hinder AI integration into clinical practice, including data heterogeneity, a lack of standardisation, concerns regarding model interpretability, regulatory constraints, and barriers to real-world clinical adoption. Addressing these issues necessitates the development of large, diverse, and high-quality data sets to enhance the robustness and generalisability of AI models. Emerging trends in AI for HCC surveillance, such as multimodal integration, explainable AI, and real-time diagnostics, offer promising advancements. These innovations have the potential to significantly improve the accuracy, efficiency, and clinical applicability of AI-driven HCC surveillance, ultimately contributing to enhanced patient outcomes.

ABSTRACTBackgroundMetabolic dysfunction‐associated steatotic liver disease (MASLD) affects over one third of the global population and is closely linked to gastrointestinal, oncological, and cardiovascular diseases. As the most common cause of steatotic liver disease (SLD), MASLD is often referred to as “fatty liver” in general health information searches. With the Internet becoming a primary source of healthcare information, this study aimed to evaluate global and regional public interest in steatotic liver disease using Google Trends data from January 2004 to December 2024.MethodsA comprehensive analysis was performed using Google Trends with the search term “fatty liver disease.” Interest levels were quantified using Google Trends indices, and temporal patterns were evaluated using average annual percent change (AAPC). Regional variations were assessed to identify geographic hotspots of public interest.ResultsGlobal interest in MASLD demonstrated significant growth (AAPC: 6.77%, 95% Confidence interval [CI]: 5.33–8.23), with a 264% increase from 2004 to 2024. Peak interest was observed in August 2024 (index: 100) compared to the lowest point in June 2007. Iran showed the highest country‐specific search volume (index: 100), while within the United States, West Virginia demonstrated the greatest relative interest (index: 100). Key topics associated with MASLD included “liver,” “symptoms,” “disease,” and “therapy.”ConclusionsSubstantial growth in global public interest in MASLD, with distinct temporal and geographical patterns, provides insights to develop targeted awareness campaigns and educational interventions, particularly in regions with low search volumes. Future research should examine the relationship between online search patterns and clinical outcomes in MASLD.

INTRODUCTION: DeepSeek was evaluated in gastroenterology board examination performance against legacy ChatGPT offline models, which previously showed failing performance. METHODS: The performances of the DeepSeek base R1 model and search-augmented R1 model were assessed using American College of Gastroenterology self-assessments (455 questions). RESULTS: DeepSeek exceeded the passing threshold. Search-augmented DeepSeek scored 81.5% across all questions, and the R1 base model scored 77.1%. Both search-augmented and offline DeepSeek models surpassed offline ChatGPT-3 (65.1%) and ChatGPT-4 (62.4%) ( P < 0.001). DISCUSSION: DeepSeek exhibited passing performance on the gastroenterology board examination but had gaps in niche topics and image exclusion limit utility. It may supplement education if validated by specialists.

Backgrounds and Aims: HBV-related liver disease ranks as the seventh leading cause of mortality. Despite advances in prevention and treatment, global disparities in the burden of primary liver cancer (PLC) persist. We evaluate global trends in the prevalence, incidence, and death of HBV-related liver disease. Approach and Results: Data from the Global Burden of Disease Study 2021 evaluated acute HBV infection, HBV-related cirrhosis, and HBV-related liver cancer prevalence, incidence, and death. In 2021, there were 7.30 million cases of acute HBV, 283.64 million cases of HBV-related cirrhosis, and 288,110 cases of HBV-related PLC. HBV-related PLC accounted for 39% of the global incidence of PLC; Western Pacific had the highest rates for HBV-related PLC, with an incidence of 5.24 and a death rate of 4.38 per 100,000 population. Between 2000 and 2021, age-standardized incidence, prevalence, and death rates from HBV-related liver disease decreased; however, the incidence of HBV-related PLC rose in 65 countries from 2000 to 2021. In parallel, age-standardized prevalent rates from HBV-related PLC increased in Europe (annual percent change: 0.77%, 95% CI: 0.72%–0.81%) and the Americas (annual percent change: 1.05%, 95% CI: 1.00%–1.10%). Conclusions: From 2000 to 2021, decreases in HBV-related liver disease incidence and prevalence were observed; however, more than one-third of countries showed an increase in the incidence of HBV-related PLC. These findings highlight the need for strengthened HBV treatment efforts to reduce the risk of liver cancer.

Abstract Background Acute pancreatitis, a prevalent gastrointestinal condition, frequently necessitates hospitalization and is associated with potential adverse in-hospital outcomes. Recent data showed the detrimental effects of COVID-19 infection on acute pancreatitis, particularly in patients with severe COVID-19 infections. However, limited information exists on the specific impacts of COVID-19 infection in patients hospitalized for acute pancreatitis. Methods We analyzed the 2020 U.S. National Inpatient Sample (NIS) to investigate the effects of COVID-19 infection on cases primarily admitted due to acute pancreatitis. Participants aged 18 and above were identified using relevant ICD-10 CM codes. Adjusted odds ratios (aORs) for specified outcomes were calculated through multivariable logistic and linear regression analyses. The primary outcome was inpatient mortality, with secondary outcomes including system-based complications. Statistical significance was established at a P value of 0.05. Results We identified 252,435 patients with a primary discharge diagnosis of acute pancreatitis. The mean age was 50.1 years; 48.6% were female. Caucasians accounted for 41%, followed by Hispanics. Of these, 1.05% (2,675/252,435) had a concurrent diagnosis of COVID-19 infection. In a survey multivariable logistic and linear regression model adjusting for patient and hospital factors, COVID-19 infection was associated with higher in-hospital mortality (aOR 3.71; 95% CI 2.01, 6.84, P &lt; 0.001), prolonged length of stay (β LOS 1.05; 95% CI 0.46, 1.64, P &lt; 0.001), increased hospitalization charge ( β charge 9,327; 95% CI 820, 17834, P &lt; 0.001), and acute respiratory failure (aOR 2.49; 95% CI 1.75, 3.53, P &lt; 0.001), We observed non-significant, but increased, risks of shock, acute kidney injury (AKI), pancreatic pseudocyst, acute respiratory distress syndrome (ARDS), and mechanical ventilation in COVID-19 positive patients. Conclusion In conclusion, our study underscores that COVID-19 infection is associated with higher in-hospital mortality, prolonged hospital stays, and increased incidence of acute respiratory failure in patients diagnosed with acute pancreatitis. Future longitudinal studies are warranted to comprehensively assess the long-term health sequelae in this population. Disclosures All Authors: No reported disclosures

Abstract Background Acute diverticulitis, a prevalent gastrointestinal condition, frequently necessitates hospitalization and is associated with potential adverse in-hospital outcomes. Recent data showed the detrimental effects of COVID-19 infection on acute diverticulitis, particularly in patients with severe COVID-19 infections. However, limited information exists on the specific impacts of COVID-19 infection in patients hospitalized for acute diverticulitis. Methods We analyzed the 2020 U.S. National Inpatient Sample (NIS) to investigate the effects of COVID-19 infection on cases primarily admitted due to acute diverticulitis. Participants aged 18 and above were identified using relevant ICD-10 CM codes. Adjusted odds ratios (aORs) for specified outcomes were calculated through multivariable logistic and linear regression analyses. The primary outcome was inpatient mortality, with secondary outcomes including system-based complications. Statistical significance was established at a P value of 0.05. Results We identified 167,170 patients with a primary discharge diagnosis of acute pancreatitis. The mean age was 60.1 years; 56.8% were female. Caucasians accounted for the majority, followed by Hispanics. Of these, 0.90% (1,504/167,170) had a concurrent diagnosis of COVID-19 infection. In a survey multivariable logistic and linear regression model adjusting for patient and hospital factors, COVID-19 infection was associated with higher in-hospital mortality (aOR 8.43; 95% CI 4.32, 16.42, P &lt; 0.001), prolonged length of stay (β LOS 2.02; 95% CI 1.27, 2.77, P &lt; 0.001) and increased hospitalization charge ( β charge 17,813.27; 95% CI 4,080, 31,546, P &lt; 0.001), We observed non-significant, but increased, risks of shock, acute kidney injury (AKI), acute respiratory distress syndrome (ARDS), and mechanical ventilation in COVID-19 positive patients. Conclusion In conclusion, our study revealed that COVID-19 infection is associated with higher in-hospital mortality, prolonged hospital stays, and increased hospitalization charges in patients diagnosed with acute diverticulitis. Future longitudinal studies are warranted to comprehensively assess the long-term health sequelae in this population. Disclosures All Authors: No reported disclosures

INTRODUCTION: This study investigates seasonal variations in eosinophilic esophagitis (EoE)-related emergency department visits among adults. METHODS: We analyzed the National Emergency Department Sample (2016–2021), identifying adult patients with EoE using ICD-10 codes. Generalized additive models assessed seasonal patterns. RESULTS: Among 18,791 EoE-related emergency department visits, a significant seasonal variation was observed, peaking in summer and nadiring in winter. This pattern was consistent across all US regions. CONCLUSION: Seasonal dietary habits and social behaviors likely contribute to EoE exacerbations. Healthcare providers should emphasize management strategies during high-risk periods, particularly summer months and weekends.

Introduction: Menopause is known to be associated with myocardial infarction (MI). However, the association between menopause age and MI onset in a nationally representative population remains unknown. Objective: To examine the correlation between age of menopause and age of MI onset in the general population and the association between early menopause (onset of menopause ≤ 40 years old) and early onset of MI (onset of MI ≤ 40 years old). Methods: A cross-sectional study was conducted using a population from the 2017-2020 National Health and Nutrition Examination Survey (NHANES). The questionnaire collected self-reported data on the participants' menopause age and their age of first MI. The relationship between these two parameters was analyzed by multivariate linear and logistic regression analyses. Multivariate analysis was adjusted for race, age, body mass index (BMI), smoking status, diabetes mellitus (DM), hypertension, and dyslipidemia status. Results: Among 2,200 postmenopausal females, 90 (4.1%) have had MI. The study involved 85 postmenopausal females who reported both menopause age and MI onset, with a mean ± SD age of 55 ± 13 years. This study found a significant association between menopause age and MI onset. After adjusting for confounders, it was found that every 1-year increase in the age of menopause will delay the onset of MI by 0.28 years, with a 95% CI of 0.013 to 0.552 (Table 1A, Graph 1A, Graph 1B). Additionally, early menopause carries an almost significantly increased risk of 2.11 times (95% CI: 1.00, 4.45) for early-onset MI. After adjusting for confounders, the magnitude of the association was lower and not statistically significant, but the direction remains (OR (95% CI): 2.08 (0.87, 4.95)). However, after stratification with comorbidities, DM status was identified as an effect modifier, with early MI significantly observed in patients with DM in both univariate and multivariate analyses, with OR (95% CI) of 3.03 (1.10, 8.37) and 4.88 (1.26, 18.96), respectively (Table 2A). Conclusion: This study demonstrated a positive association between menopause age and MI onset in a generally representative population. This suggests that prolonged estrogen exposure due to late menopause may delay the onset of MI. Additionally, early menopause was associated with early MI onset in the DM population. Further longitudinal studies are required to examine the potential mechanisms involved in menopause onset and MI onset.

Abstract Background Short sleep is linked to increased acute myocardial infarction (MI) risk.However, the association of weekend-to-weekday sleep patterns with MI in a nationally representative population remains unknown. The goal is to investigate how weekday and weekend sleep durations affect myocardial infarction (MI) in the general population, and if longer weekend sleep can offset insufficient weekday sleep's effects. Methods A cross-sectional study utilized data from the 2017-2020 NHANES to examine the relationship between sleep patterns and MI. Participants self-reported their average sleep durations on weekdays (1) and weekends (2), along with the calculated weekend-to-weekday sleep duration ratio (SDR) (3). Logistic regression models, adjusting for various factors, including demographics and comorbidities, were employed to analyze the association. Those with SDR &gt; 1 had more weekend sleep, while an SDR = 1 indicated equal sleep durations. Results The study involved 9,205 adult participants, with a mean ± SD age of 68.8 ± 10.8 years and 30.7% being female. Among them, 4.65% (428 patients) had a history of MI. The mean ± SD of weekday and weekend sleep hours was 7.6 ± 1.7 and 8.3 ± 1.8 hours, respectively. For weekday sleep duration, after univariate analysis, individuals compared to those in Q1 were statistically significant 0.72 times less likely in Q2 and 1.4 times more likely in Q4 to experience MI . While MI was 0.76 times less likely to occur among participants in Q3, it was not statistically significant (95% CI Q2: 0.54, 0.96; Q4: 1.05, 1.76; Q3:0.57, 1.00). After adjusting, participants only in Q3 were statistically significant 0.71 times less likely to develop MI.(Q3: 95% CI 0.51, 0.99). For weekend sleep duration, the univariate analysis showed that individuals in Q2, Q3, and Q4 were significantly less likely to experience MI (OR = 0.63, 0.67, and 0.69; 95% CIs: 0.48-0.82, 0.51-0.87, 0.53-0.90, respectively) After adjusting, only participants in Q2 were statistically significant less likely to develop MI (OR = 0.71; 95% CI 0.52 - 0.96). For the weekend-to-weekday sleep duration ratio (SDR), after univariate analysis, individuals were statistically significant 0.54 times less likely, and 1.5 times more likely to experience MI in those whose SDR is more than 1, and those whose SDR equals 1, respectively (95% CI SDR &gt; 1: 1.14, 1.98; SDR = 1: 0.39, 0.72). After adjusting, participants with SDR more than 1 were statistically significant 0.69 times less likely to develop MI. Conclusions Moderate sleep durations on weekdays (in Q3), weekends (in Q2), along with SDR more than 1, were negatively linked with MI in a general population. This implies that sleep durations on both weekends and weekdays have comparable associations with MI. Additionally, full recovery sleep on weekends following sleep-deprived weekdays, might reduce MI risk. Further studies are needed to explore impact of weekend and weekday sleep patterns on MI.Histogram and Margins plotTable of Odd ratios