Journal of Gastrointestinal and Liver Diseases最新文献

Background and aims: High-resolution esophageal manometry (HREM) is the gold standard procedure used for the diagnosis of esophageal motility disorders (EMD). Artificial intelligence (AI) might provide an efficient solution for the automatic diagnosis of EMD by improving the subjective interpretation of HREM images. The aim of our study was to develop an AI-based system, using neural networks, for the automatic diagnosis of HREM images, based on one wet swallow raw image.

Methods: In the first phase of the study, the manometry recordings of our patients were retrospectively analyzed by three experienced gastroenterologists, to verify and confirm the correct diagnosis. In the second phase of the study raw images were used to train an artificial neural network. We selected only those tracings with ten test swallows that were available for analysis, including a total of 1570 images. We had 10 diagnosis categories, as follows: normal, type I achalasia, type II achalasia, type III achalasia, esophago-gastric junction outflow obstruction, jackhammer oesophagus, absent contractility, distal esophageal spasm, ineffective esophageal motility, and fragmented peristalsis, based on Chicago classification v3.0 for EMDs.

Results: The raw images were cropped, binarized, and automatically divided in 3 parts: training, testing, validation. We used Inception V3 CNN model, pre-trained on ImageNet. We developed a custom classification layer, that allowed the CNN to classify each wet swallow image from the HREM system into one of the diagnosis categories mentioned above. Our algorithm was highly accurate, with an overall precision of more than 93%.

Conclusion: Our neural network approach using HREM images resulted in a high accuracy automatic diagnosis of EMDs.

Background and aims: Objective monitoring and effective early treatment using a treat-to-target approach are key to improving therapeutic outcomes in IBD patients. This study aimed to assess adherence to objective monitoring (clinical, biomarkers, and endoscopy) and its impact on clinical outcomes.

Methods: A prospective, multicenter study included consecutive IBD patients starting on adalimumab therapy between January 2019 and December 2020. Disease activity, assessed by the Harvey-Bradshaw index (HBI), partial Mayo, C-reactive protein (CRP), fecal calprotectin (FCAL), and endoscopy were evaluated at adalimumab initiation and 3, 6, 9 and 12 months. Therapeutic drug monitoring, changes in treatment, drug sustainability, and clinical outcomes were assessed.

Results: 104 IBD patients were enrolled (78.8% CD, median age 34.3 years, disease duration 9 years). During the 12 months follow-up, high adherence to clinical activity assessment was observed in both CD (81.3%- 87.7%) and UC patients (76.5-90.9%). CRP measurement decreased over time in both CD (37.3%-54.9%) and UC (29.4%-50.0%). The adherence to serial FCAL monitoring was low in CD (22.7-31.3%) and UC patients (17.6-56.0%). UC patients had higher adherence to early endoscopic assessment (<6 months) compared to CD patients (40.9% vs. 21.5%). Adherence to early combined clinical and biomarkers resulted in earlier dose optimization in CD and UC (log-rank<0.001), but drug sustainability was not different. The patients with early combined adherence had a significantly higher clinical remission rate at 1 year compared to non-adherence (70.2% vs. 29.8%, p=0.007) but no significant difference in UC patients.

Conclusions: The adherence to early objective monitoring with combined clinical and biomarkers assessment in IBD patients starting adalimumab therapy led to dose optimization and improved 1-year clinical remission in CD but did not change drug sustainability and clinical remission in UC.

Obesity is a systemic disease and represents one of the leading causes of death worldwide by constituting the main risk factor for a series of non-communicable diseases such as type 2 diabetes mellitus (T2DM), cardiovascular diseases and dyslipidemia. Lifestyle interventions have been attempting to prevent T2DM and obesity but are difficult to maintain by most patients. However, the recent focus on the intestinal microbiota and its important role in the host's metabolism provides a new key for improving metabolic health. Modulating the composition of the gut microbiota was proposed as a method to manage these metabolic diseases and most frequently this is undertaken by using probiotics, prebiotics or synbiotics. Furthermore, the action of metformin, the most commonly prescribed drug for treating T2DM, is mediated in part by the gut microbiota, although this interplay may also be responsible for the frequent gastrointestinal adverse effects of metformin. Thus, adding a gut microbiota modulator (GMM), such as probiotics or prebiotics, to metformin therapy could amplify its anti-diabetic effects, while decreasing its adverse reactions. This review summarizes the various therapies that are used to shift the composition of the microbiome and their efficacy in alleviating metabolic parameters, it assesses the interaction between metformin and the gut microbiota, and it evaluates the existing clinical and preclinical studies that analyze the potential synergy of a combined metformin-GMM therapy.

Erratum for: Probiotics in the Treatment of Inflammatory Bowel Diseases in Adulthood: A Systematic Review. J Gastrointest. Liv. Dis. 2022; 31: 74-84.

Background and aims: Non-alcoholic steatohepatitis (NASH) is acknowledged as a severe disease that is associated with a significant burden on patients, payers, and society. However, limited evidence exists on the cost associated with NASH across different countries. This analysis aims to describe the cost associated with the routine care of patients with NASH in France, Germany, and the United States.

Methods: Data was sourced from the Gesellschaft für Konsumforschung (now Ipsos) Disease Atlas Real- World Evidence program collected from July through November 2017 in France, Germany, and the United States. Country-level unit cost was estimated from national databases for diagnostic tests and procedures, prescription drugs, hospital stays, and outpatient visits in respective local currency based on 2017 values. These were combined to provide an estimate of the cost of management of confirmed NASH in this specific patient population and are presented as mean cost per patient per year for each country in local currency and as USD adjusted for purchasing power parity for comparison.

Results: Annual mean ± standard deviation cost of non-alcoholic steatohepatitis ranged from purchasing power parity USD 1,049±2,461 in Germany to USD 1,723±2,988 in the United States. In all markets, the predominant contributor to cost is healthcare resource use represented by hospitalisation and outpatient visits.

Conclusions: This study reveals that costs associated with NASH treatment and management vary across the three countries studied, in part due to differences in healthcare systems but also due to different approaches in managing this disease. Our analysis represents the costs for a specific cohort of patients and further studies are warranted to better understand the progressive impact of NASH on healthcare systems and society.