Przegla̜d Gastroenterologiczny最新文献

Colon cancer is a major public health issue, affecting a growing number of individuals worldwide. Proper and early diagnosis of colon cancer is the necessary first step toward effective treatment and/or prevention of future disease relapse. Artificial intelligence and its subtypes, deep learning in particular, tend nowadays to have an expanding role in all fields of medicine, and diagnosing colon cancer is no exception. This report aims to summarize the entire application spectrum of deep learning in all diagnostic tests regarding colon cancer, from endoscopy and histologic examination to medical imaging and screening serologic tests.

Inflammatory bowel diseases (IBD) are chronic intestinal conditions of multifactorial aetiology including genetic susceptibility, immunological impairment, dysbiosis, and environmental factors. The diagnosis is based on both clinical and endoscopic features, wherein histopathological evaluation remains a gold diagnostic standard. However, fast, reliable, and non-invasive biological markers have been used for years for diagnosis as well as for disease activity monitoring. Currently, commonly used faecal calprotectin is the only biomarker approved and recommended by the European Crohn's and Colitis Organization (ECCO). Nonetheless, other biological markers discriminating between functional and organic bowel conditions have been widely studied. Therefore, the aim of this manuscript was to review new potential biomarkers of inflammation in IBD. The aim of this study was to review currently available biomarkers of intestinal inflammation and increased gut permeability in IBD.

Introduction: Retrospective exploratory analysis to identify biomarker pairs in the AVAGAST Phase III study.

Aim: The main hypothesis of this retrospective exploratory biomarker analysis is the identification of dichotomization levels based on optimal selection driven by the predictive value of single biomarkers. The outcome of interest optimization might unveil additional treatment benefits. Furthermore, testing the biomarker pairs at their optimal cut-off selection might provide the predictive score candidates.

Material and methods: 712 plasma 92% and 727 plasma 94% tumor samples of all patients were using Cox model by identifying optimal dichotomization to maximize treatment benefit. A quadrant analysis grouped biomarker pairs into subsets yielded the best clinical benefit. Candidate biomarker score using the nested 2-fold cross-validation method was used to adjust the optimal cut-off selection.

Results: Patients with lower VEGF-R1 at optimal cut-off with low IHER2G showed significant improvement in PFS - first line (HR = 0.62; 95% CI: 0.50 to 0.78). The interaction p-value of the biomarker pair was adjusted at 0.0147094.

Conclusions: The predictive biomarker is a potential candidate for PFS - first line in patients with advanced gastric cancer treated with Bevacizumab.

Introduction: Cirrhosis is a common liver disease, which is characterized by life-limiting complications. In cirrhosis, liver ACE2 mRNA levels were 34-times upregulated, ACE2 protein 97-times upregulated, and ACE2 receptors increased in 80% of hepatocytes. Increased ACE2 receptor sensitizes hepatocytes to COVID-19.

Aim: To evaluate the applications of cirrhosis patients to the Emergency Department before and after the pandemic.

Material and methods: The study was conducted retrospectively in a single centre on cirrhotic patients who applied to the Emergency Department in a 2-year period. The obtained data were compared with the laboratory values of the patients: the severity of cirrhosis, the reasons for applying to the Emergency Department, hospitalization/discharge status, and pre-pandemic and pandemic period values. The mortality of the patients was recorded.

Results: The biochemical values, CTP score, and complications of cirrhosis patients deteriorated during the pandemic period, which contributed to the increase in mortality and that the CTP score and its complications worsened, which contributed to the increase in mortality. COVID-19 positivity contributes to the progression of the CTP score, but it is not directly associated with mortality.

Conclusions: We think that new treatment protocols should be included in the guidelines to minimize the effects of this type of viral infection on the liver.