Background and aims: Acute cholecystitis is a fairly common inpatient diagnosis among the gastrointestinal disorders. The aim of this study was to use a national database of US hospitals to evaluate the incidence and costs of hospital admissions associated with acute cholecystitis.Method: We analyzed the National Inpatient Sample Database (NIS) for all patients in which acute cholecystitis (ICD-9 codes: 574.00, 574.01, 574.30, 574.31, 574.60, 574.61 or 575.0) was the principal discharge diagnosis from 1997 to 2012. The NIS is the largest all-payer inpatient database in the United States and contains data from approximately 8 million hospital stays each year. The statistical significance of the difference in the number of hospital discharges, lengths of stay and associated hospital costs over the study period was determined by using the Chi-square test for trends.Results: In 1997, there were 149 661 hospital admissions with a principal discharge diagnosis of acute cholecystitis, which increased to 215 995 in 2012 ( P < 0.001). The mean length of stay for acute cholecystitis decreased by 17% between 1997 and 2012 (i.e. from 4.7 days to 3.9 days; (P < 0.05). During the same time period, however, mean hospital charges have increased by 195.4 % from US$14 608 per patient in 1997 to US$43 152 per patient in 2012 ( P < 0.001).Conclusion: The number of inpatient discharges related to acute cholecystitis has increased significantly in the United States over the last 16 years, along with a great increase in the associated hospital charges. However, there has been a gradual decline in the mean length of stay. Inpatient costs associated with acute cholecystitis contribute significantly to the total healthcare bill. Further research on cost-effective evaluation and management of acute cholecystitis is required.

Background and study aims We analyzed NIS (National Inpatient Sample) database from 2007 – 2013 to determine if early esophagogastroduodenoscopy (EGD) (24 hours) for upper gastrointestinal bleeding improved the outcomes in terms of mortality, length of stay and costs. Patients and methods Patients were classified as having upper gastrointestinal hemorrhage by querying all diagnostic codes for the ICD-9-CM codes corresponding to upper gastrointestinal bleeding. For these patients, performance of EGD during admission was determined by querying all procedural codes for the ICD-9-CM codes corresponding to EGD; early EGD was defined as having EGD performed within 24 hours of admission and late EGD was defined as having EGD performed after 24 hours of admission. Results A total of 1,789,532 subjects with UGIH were identified. Subjects who had an early EGD were less likely to have hypovolemia, acute renal failure and acute respiratory failure. On multivariable analysis, we found that subjects without EGD were 3 times more likely to die during the admission than those with early EGD. In addition, those with late EGD had 50 % higher odds of dying than those with an early EGD. Also, after adjusting for all factors in the model, hospital stay was on average 3 and 3.7 days longer for subjects with no or late EGD, respectively, then for subjects with early EGD. Conclusion Early EGD (within 24 hours) is associated with lower in-hospital mortality, morbidity, shorter length of stay and lower total hospital costs.

Background and study aims Early studies have shown that artificial intelligence (AI) has the potential to augment the performance of gastroenterologists during endoscopy. Our aim was to determine how gastroenterologists view the potential role of AI in gastrointestinal endoscopy. Methods In this cross-sectional study, an online survey was sent to US gastroenterologists. The survey included questions about physician level of training, experience, and practice characteristics and physician perception of AI. Descriptive statistics were used to summarize sentiment about AI. Univariate and multivariate analyses were used to assess whether background information about physicians correlated to their sentiment. Results Surveys were emailed to 330 gastroenterologists nationwide. Between December 2018 and January 2019, 124 physicians (38 %) completed the survey. Eighty-six percent of physicians reported interest in AI-assisted colonoscopy; 84.7 % agreed that computer-assisted polyp detection (CADe) would improve their endoscopic performance. Of the respondents, 57.2 % felt comfortable using computer-aided diagnosis (CADx) to support a “diagnose and leave” strategy for hyperplastic polyps. Multivariate analysis showed that post-fellowship experience of fewer than 15 years was the most important factor in determining whether physicians were likely to believe that CADe would lead to more removed polyps (odds ratio = 5.09; P = .01). The most common concerns about implementation of AI were cost (75.2 %), operator dependence (62.8 %), and increased procedural time (60.3 %). Conclusions Gastroenterologists have strong interest in the application of AI to colonoscopy, particularly with regard to CADe for polyp detection. The primary concerns were its cost, potential to increase procedural time, and potential to develop operator dependence. Future developments in AI should prioritize mitigation of these concerns.

This study provides robust, population-based evidence that ERCP should not be delayed for >48 hours in patients with acute cholangitis due to choledocholithiasis.