Extra-pulmonary manifestations of COVID-19 (SARS-CoV-2) are of increasing interest as a consequence of the increase in cases worldwide and a better understanding of the pathophysiology of the disease. However, gastrointestinal symptoms are rarely described but are a common occurrence.We report a case of a 62-year-old male with severe pulmonary infection with COVID-19, who presented with abdominal pain, hematemesis, bloody diarrhea, and abdominal distention, which led to the diagnosis of paralytic ileus after diagnostic laparoscopy. Further, we discuss the potential pathophysiological mechanisms behind this manifestation of COVID-19.

Background: When liver bleeding cannot be controlled by conventional methods, a topical hemostatic patch can be applied during surgery. In recent years new hemostats have become available. The aim of this study was to investigate the degree of adhesion and infl ammation for three topical hemostatic patches, TachoSil ® , Hemopatch™ and Veriset™. Methods: In 60 adult male Sprague Dawley rats liver two lesions were induced with a scalpel. Each rat was treated with two of the three patches tested. After 1, 2 and 3 months the animals were euthanized and macroscopic evaluation of adhesions and histological assessment of infl ammation and macrophage infi ltration were performed. Results: A signifi cant higher (p<0.05) occurrence of foreign body giant cells (FBGCs) was found in Hemopatch™ and Veriset™, whereas both had a lower degree of infl ammatory and macrophage infi ltration compared to TachoSil ®. No differences in the occurrence of adhesions were found. Conclusion: Our study found evidence for difference in infl ammation and formation of foreign body giant cells for the three hemostatic patches.

Ambulatory long-term motility recording is used increasingly for evaluation of esophageal function. The enormous amount of motility data recorded by this method demands subsequent computer analysis. One of the most crucial steps of this analysis becomes the process of automatic selection of relevant pressure peaks at the various recording levels. Until now, this selection has been performed entirely by rule-based systems, requiring each pressure deflection to fit within predefined rigid numerical limits in order to be detected. However, due to great variations in the shapes of the pressure curves generated by muscular contractions, rule-based criteria do not always select the pressure events most relevant for further analysis. We have therefore been searching for a new concept for automatic event recognition. The present study describes a new system, based on the method of neurocomputing. A large sample of normal esophageal pressure deflections was used as a "learning set," and the performance of the trained neural networks was subsequently verified on different sets of data from normal subjects. Our trained networks detected pressure deflections with sensitivities of 0.79-0.99 and accuracies of 0.89-0.98, depending on the recording level within the esophageal lumen. The neural networks often recognized peaks that clearly represented true contractions but that had been rejected by a rule-based system. We conclude that neural networks have potentials for automatic detections of esophageal, and possibly also other kinds of gastrointestinal, pressure variations.

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