Fatigue is a burdensome, multidimensional, and multifactorial symptom that is associated with a wide array of chronic illnesses, specifically occurring in nearly 50% of patients with inflammatory bowel disease (IBD). Although common, given its subjective nature, physicians often under-recognize and undertreat this debilitating symptom. There are multiple etiologies that can contribute to fatigue in patients with IBD, including disease activity, anemia, medications, psychosomatic symptoms, and alterations to the gut-brain axis. The management of fatigue in IBD can be challenging, as it is often times multifaceted. In this review, we summarize the available tools for the diagnosis and measurement of fatigue, discuss etiologies, and make recommendations for their management. We identify knowledge gaps for the workup and treatment of fatigue and propose an algorithm to aid physicians in the evaluation and management of fatigue in this unique population. However, future research is needed to address several areas of knowledge deficits and improve the management of fatigue in IBD.

The first cases of a novel corona virus infection were reported in Wuhan China in December of 2019, followed by the declaration of an international pandemic by the World Health Organization in March 2020. Early reports of the virus, now known as severe acute respiratory syndrome coronavirus 2, and its clinical disease coronavirus disease 2019 (COVID-19), has shown higher rates of morbidity and mortality in the elderly and those with pre-existing medical conditions. Of particular concern is the safety of those with compromised immune systems. Inflammatory Bowel disease (IBD) is itself caused by a disordered immune response, with the most effective medical therapies being immune suppressing or modifying. As such, the risk of COVID-19, virus related outcomes, and appropriate management of IBD patients during the global pandemic is of immediate concern to gastroenterologists worldwide. There has been a rapid accumulation of clinical data and expert opinion on the topic. This review will highlight the latest source information on clinical observation/outcomes of the IBD population and provide a concise summary of the most up to date perspectives on IBD management in the age of COVID-19.

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BackgroundDespite the effectiveness of fecal microbiota transplantation (FMT) for treating recurrent Clostridium difficile (C. difficile) infection, some patients are reluctant to accept this therapy. Our study examined attitudes towards FMT and factors that contribute to patients’ acceptance of this treatment.MethodsWe distributed patient surveys at a Veterans Affairs hospital, a public hospital, and an academic faculty practice. Multivariable logistic regression was performed, adjusting for factors associated with FMT acceptance on univariate analysis and prior experience with C. difficile infection.ResultsOf 267 patients, only 12% knew of FMT prior to the survey, but 77% would undergo the procedure if medically indicated. On multivariable analysis, those with children and with college degrees or higher were more likely to agree to FMT (odds ratio [OR] 2.11, 95% confidence interval [CI] 1.02-4.35; OR 2.27, 95% CI 1.11-4.60 respectively). Sixty-five respondents (71%) chose colonoscopy as the preferred vehicle for FMT, while nasogastric tube was least preferred. Disease transmission was the most common concern (30%, n=242), and FMT success rate was the least selected concern (9.1%).ConclusionsMost patients in a diverse sample of gastroenterology clinics had no prior knowledge of FMT, but were receptive to the procedure. Having children and higher education levels were predictors for FMT acceptance. Our findings suggest that barriers to FMT utilization may be overcome with counseling about safety concerns. More data on the risk of transmitting diseases or clinical characteristics, such as obesity, through FMT are needed and will be important for the acceptance of this procedure.

The Inflammatory Bowel Disease (IBD) population, which may require treatment with immunosuppressive medications, may be uniquely vulnerable to COVID-19 infection. In fact, there is some evidence these medications may inhibit the cytokine storm that is theorized to cause a rapid decline seen in COVID-19. In addition, the digestive symptoms of COVID-19 can be difficult to distinguish from the activation of IBD. We present an interesting case of a Crohn’s patient inadvertently administering anti-cytokine therapy during the pre-symptomatic period of COVID-19 infection. Immune suppression during early infection with SARS-COV2 risks a poor immune response to the virus and could theoretically result in a more severe course of infection.

Background Regional variation in Helicobacter pylori resistance patterns is a significant contributing factor for the ineffectiveness of traditional treatments. To improve treatment outcomes, we sought to create an individualized, susceptibility‐driven therapeutic approach among our patient population, which is one of the poorest in the nation. It is medically underserved, minority‐predominant and has high incidence of H pylori infection. Methods We compiled various factors involved in the antibiotic resistance of H pylori from literature. We then created a predictive model to customize therapies based on analyzed data from 2,014 H pylori patients with respect to several of these factors. The predictions of the model were further tested with analysis of patient stool samples. Results A clear pattern of H pylori prevalence and antibiotic resistance was observed in our patients. We observed that majority of H pylori patients were women (62%) and over the age of 40 years (80%). 30% and 36% of the H pylori patients were African American and Hispanic, respectively. A median household income of less than $54,000, past H pylori infection, previous use of certain antibiotics for any infection decreased the chance of eradication. Results of the stool testing were consistent with model predictions (90% accuracy). Conclusion This model demonstrates the predictive accuracy of H pylori infection and antibiotic resistance based on patient attributes and previous treatment history. It will be useful to formulate customized treatments with predicted outcomes to minimize failures. Our community attributes may contribute toward broad applicability of model for other similar communities.

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