Artificial intelligence is increasingly transforming gastrointestinal endoscopy, particularly in endoscopic ultrasound (EUS), biliary disease, and upper gastrointestinal (GI) endoscopy. EUS plays a key role in evaluating subepithelial lesions (SELs) and solid and cystic pancreatic neoplasms, incorporating techniques such as elastography and contrast enhancement. Nonetheless, its diagnostic performance remains strongly operator-dependent, with notable interobserver variability and only moderate accuracy even among experienced endosonographers. Computational models applied to EUS images and videos have shown encouraging results in lesion detection, characterization, and risk stratification, in some cases reaching or exceeding expert-level performance. However, most available data are retrospective and derived from single-center studies. Cholangiocarcinoma continues to be associated with poor outcomes, largely due to delayed diagnosis and the difficulty of distinguishing malignant from benign biliary strictures. Although advances in cholangioscopy, imaging, and tissue acquisition have improved diagnostic yield, indeterminate strictures remain frequent. The incorporation of artificial intelligence into imaging analysis, radiologic assessment, and tissue evaluation may improve diagnostic precision, decrease unnecessary procedures, and provide real-time decision support. In upper GI endoscopy, detection and characterization of esophageal and gastric neoplasia remain inconsistent in daily practice and are highly dependent on operator expertise. Emerging systems can enhance lesion recognition, reduce variability among observers, and assist real-time assessment. Overall, these technologies represent a promising adjunct across endoscopic modalities, although prospective multicenter validation and real-time clinical integration are still required for widespread adoption.
BACKGROUND Metabolic dysfunction-associated steatotic liver disease (MASLD) is a complex multisystem disorder, with cardiovascular disease (CVD) representing the most common cause of mortality. This study aims to analyze trends in MASLD and CVD-related mortality in the United States. METHODS Mortality data for individuals aged 25 years and older from 1999 to 2024 were obtained from the CDC WONDER database. Age-adjusted mortality rates (AAMRs) per 100,000 population were calculated among patients with MASLD and CVD. Temporal trends were assessed using Joinpoint regression analysis to estimate the annual percent change (APC) and average annual percent change (AAPC) in mortality rates. RESULTS Between 1999 and 2024, a total of 55,788 deaths were identified related to MASLD and CVD among adults aged 25 years or older. The number of deaths increased from 1044 in 1999 to 5216 in 2024, reflecting a 400% increase in mortality. The most common causes of CVD-related mortality were hypertension and ischemic heart disease. The total number of deaths among men was higher compared to women (30,201 vs. 25,587), and the rate of increase in mortality was higher among women (7.60, 95% CI: 7.07-8.35 vs. 3.42, 95% CI: 2.78-4.17). CONCLUSION Our analysis highlights acceleration in CVD-related mortality among MASLD patients with widening disparities. These findings highlight MASLD as a growing contributor to cardiovascular mortality, and targeted prevention, along with reduction strategies, are urgently needed to mitigate this rising burden.
GOALS This study aimed to evaluate the incidence of acute pancreatitis (AP) following initiation of potassium-competitive acid blockers (PCABs) versus proton pump inhibitors (PPIs). BACKGROUND The comparative risk of AP associated with PCABs versus PPIs remains uncertain. STUDY This retrospective cohort study analyzed data from the TriNetX database, which included adult patients who received a prescription for either PCAB or PPI between January 1, 2016, and August 1, 2025. Patients with a prior diagnosis of acute or chronic pancreatitis, pancreatic neoplasms, organ transplantation, or pregnancy were excluded. Propensity score matching (1:1) was used to adjust for demographic and other confounders. Univariate Cox proportional hazards models were used to assess the incidence of AP within 90 days of therapy initiation. RESULTS In total, 77,841 adults using PCAB and 13,497,134 adults using PPI were included. Among them, 80 patients in the PCAB cohort and 96,170 patients in the PPI cohort developed AP. The overall incidence of AP within 90 days of therapy initiation was 0.65% in the PCAB cohort and 0.96% in the PPI cohort, with the highest rates observed in adults aged 75 years or older and females. After matching, PCAB use was not associated with a statistically significant difference in new-onset AP compared with PPI (OR: 0.624; P=0.24). PCAB users had significantly lower odds of acute respiratory failure, acute renal failure, and sepsis than PPI users. Mortality was also significantly lower in the PCAB cohort. CONCLUSIONS The study suggests that PCABs may offer a safer alternative to PPIs with respect to AP risk, although further investigation is warranted.
