We described features of hospitalized Covid-19 patients and identified predictors of clinical deterioration. We included patients consecutively admitted at Humanitas Research Hospital (Rozzano, Milan, Italy); retrospectively extracted demographic; clinical; laboratory and imaging findings at admission; used survival methods to identify factors associated with clinical deterioration (defined as intensive care unit (ICU) transfer or death), and developed a prognostic index. Overall; we analyzed 239 patients (29.3% females) with a mean age of 63.9 (standard deviation [SD]; 14.0) years. Clinical deterioration occurred in 70 patients (29.3%), including 41 (17.2%) ICU transfers and 36 (15.1%) deaths. The most common symptoms and signs at admission were cough (77.8%) and elevated respiratory rate (34.1%), while 66.5% of patients had at least one coexisting medical condition. Imaging frequently revealed ground-glass opacity (68.9%) and consolidation (23.8%). Age; increased respiratory rate; abnormal blood gas parameters and imaging findings; coexisting coronary heart disease; leukocytosis; lymphocytopenia; and several laboratory parameters (elevated procalcitonin; interleukin-6; serum ferritin; C-reactive protein; aspartate aminotransferase; lactate dehydrogenase; creatinine; fibrinogen; troponin-I; and D-dimer) were significant predictors of clinical deterioration. We suggested a prognostic index to assist risk-stratification (C-statistic; 0.845; 95% CI; 0.802–0.887). These results could aid early identification and management of patients at risk, who should therefore receive additional monitoring and aggressive supportive care.

Histological remission is evolving as an important treatment target in UC. We aimed to develop a simple histological index, aligned to endoscopy, correlated with clinical outcomes, and suited to apply to an artificial intelligence (AI) system to evaluate inflammatory activity. Methods Using a set of 614 biopsies from 307 patients with UC enrolled into a prospective multicentre study, we developed the Paddington International virtual ChromoendoScopy ScOre (PICaSSO) Histologic Remission Index (PHRI). Agreement with multiple other histological indices and validation for inter-reader reproducibility were assessed. Finally, to implement PHRI into a computer-aided diagnosis system, we trained and tested a novel deep learning strategy based on a CNN architecture to detect neutrophils, calculate PHRI and identify active from quiescent UC using a subset of 138 biopsies. Results PHRI is strongly correlated with endoscopic scores (Mayo Endoscopic Score and UC Endoscopic Index of Severity and PICaSSO) and with clinical outcomes (hospitalisation, colectomy and initiation or changes in medical therapy due to UC flare-up). A PHRI score of 1 could accurately stratify patients’ risk of adverse outcomes (hospitalisation, colectomy and treatment optimisation due to flare-up) within 12 months. Our inter-reader agreement was high (intraclass correlation 0.84). Our preliminary AI algorithm differentiated active from quiescent UC with 78% sensitivity, 91.7% specificity and 86% accuracy. Conclusions PHRI is a simple histological index in UC, and it exhibits the highest correlation with endoscopic activity and clinical outcomes. A PHRI-based AI system was accurate in predicting histological remission.

Objective: The gut virome is a dense community of viruses inhabiting the gastrointestinal tract and an integral part of the microbiota. The virome coexists with the other components of the microbiota and with the host in a dynamic equilibrium, serving as a key contributor to the maintenance of intestinal homeostasis and functions. However, this equilibrium can be interrupted in certain pathological states, including inflammatory bowel disease, causing dysbiosis that may participate in disease pathogenesis. Nevertheless, whether virome dysbiosis is a causal or bystander event requires further clarification. Design: This review seeks to summarise the latest advancements in the study of the gut virome, highlighting its cross-talk with the mucosal microenvironment. It explores how cutting-edge technologies may build upon current knowledge to advance research in this field. An overview of virome transplantation in diseased gastrointestinal tracts is provided along with insights into the development of innovative virome-based therapeutics to improve clinical management. Results: Gut virome dysbiosis, primarily driven by the expansion of Caudovirales , has been shown to impact intestinal immunity and barrier functions, influencing overall intestinal homeostasis. Although emerging innovative technologies still need further implementation, they display the unprecedented potential to better characterise virome composition and delineate its role in intestinal diseases. Conclusions: The field of gut virome is progressively expanding, thanks to the advancements of sequencing technologies and bioinformatic pipelines. These have contributed to a better understanding of how virome dysbiosis is linked to intestinal disease pathogenesis and how the modulation of virome composition may help the clinical intervention to ameliorate gut disease management.

The inflammatory bowel diseases (IBDs) are systemic conditions that affect not only the gastrointestinal tract but also other parts of the body. The presence of extraintestinal manifestations can significantly impact the quality of life in IBD patients. Peripheral arthritis, episcleritis, and erythema nodosum are frequently associated with active intestinal inflammation and often improve with standard treatment targeting intestinal inflammation. In contrast, anterior uveitis, ankylosing spondylitis, and primary sclerosing cholangitis typically occur independently of disease flares. The incidence of these conditions in individuals with IBD can reach up to 50% of patients over the course of their lifetime. In addition, some advanced therapies utilized for the treatment of IBD potentially result in side effects that may resemble extraintestinal manifestations. This review provides a thorough analysis of the pathophysiology and treatment of extraintestinal manifestations associated with Crohn’s disease and ulcerative colitis.

Patients with inflammatory bowel diseases (IBDs), including both ulcerative colitis (UC) and Crohn’s disease (CD), are at a higher risk of developing colorectal cancer (CRC). However, advancements in endoscopic imaging techniques, integrated surveillance programs, and improved medical therapies have led to a decrease in the incidence of CRC among IBD patients. Currently, the management of patients with IBD who have a history of or ongoing active malignancy is an unmet need. This involves balancing the risk of cancer recurrence/progression with the potential exacerbation of IBD if the medications are discontinued. The objective of this review is to provide an updated summary of the epidemiology, causes, risk factors, and surveillance approaches for CRC in individuals with IBD, and to offer practical guidance on managing IBD patients with history of previous or active cancer.

Background: We aimed to predict response to biologics in inflammatory bowel disease (IBD) using computerized image analysis of probe confocal laser endomicroscopy (pCLE) in vivo and assess the binding of fluorescent-labeled biologics ex vivo. Additionally, we investigated genes predictive of anti-tumor necrosis factor (TNF) response. Methods: Twenty-nine patients (15 with Crohn’s disease [CD], 14 with ulcerative colitis [UC]) underwent colonoscopy with pCLE before and 12 to 14 weeks after starting anti-TNF or anti-integrin α4β7 therapy. Biopsies were taken for fluorescein isothiocyanate–labeled infliximab and vedolizumab staining and gene expression analysis. Computer-aided quantitative image analysis of pCLE was performed. Differentially expressed genes predictive of response were determined and validated in a public cohort. Results: In vivo, vessel tortuosity, crypt morphology, and fluorescein leakage predicted response in UC (area under the receiver-operating characteristic curve [AUROC], 0.93; accuracy 85%, positive predictive value [PPV] 89%; negative predictive value [NPV] 75%) and CD (AUROC, 0.79; accuracy 80%; PPV 75%; NPV 83%) patients. Ex vivo, increased binding of labeled biologic at baseline predicted response in UC (UC) (AUROC, 83%; accuracy 77%; PPV 89%; NPV 50%) but not in Crohn’s disease (AUROC 58%). A total of 325 differentially expressed genes distinguished responders from nonresponders, 86 of which fell within the most enriched pathways. A panel including ACTN1, CXCL6, LAMA4, EMILIN1, CRIP2, CXCL13, and MAPKAPK2 showed good prediction of anti-TNF response (AUROC >0.7). Conclusions: Higher mucosal binding of the drug target is associated with response to therapy in UC. In vivo, mucosal and microvascular changes detected by pCLE are associated with response to biologics in inflammatory bowel disease. Anti-TNF–responsive UC patients have a less inflamed and fibrotic state pretreatment. Chemotactic pathways involving CXCL6 or CXCL13 may be novel targets for therapy in nonresponders.