ABSTRACT
BACKGROUND: Clostridioides difficile infections (CDIs) are common among patients with inflammatory bowel disease (IBD) and can mimic and exacerbate IBD flares, thus warranting appropriate testing during flares. AIMS: To examine recent trends in rates of CDI and associated risk factors in hospitalized IBD patients, which may better inform targeted interventions to mitigate the risk of infection. METHODS: This is a retrospective analysis using the Nationwide Readmissions Database from 2010 to 2020 of hospitalized individuals with Crohn's disease (CD) or ulcerative colitis (UC). Longitudinal changes in rates of CDI were evaluated using International Classification of Diseases codes. Multivariable logistic regression evaluated the association between patient- and hospital-related factors and CDI. RESULTS: There were 2,521,935 individuals with IBD who were hospitalized at least once during the study period. Rates of CDI in IBD-related hospitalizations increased from 2010 to 2015 (CD: 1.64%-3.32%, p < 0.001; UC: 4.15%-5.81%, p < 0.001), followed by a steady decline from 2016 to 2020 (CD: 3.15%-2.27%, p < 0.001; UC: 5.04%-4.27%, p < 0.001). In multivariable models, CDI was associated with the Charlson-Deyo comorbidity index, public insurance, and hospital size. CDI was associated with increased mortality. CONCLUSIONS: Rates of CDI among hospitalized patients with IBD had initially increased, but have declined since 2015. Increased comorbidity, large hospital size, public insurance, and urban teaching hospitals were associated with higher rates of CDI. CDI was associated with increased mortality in hospitalized patients with IBD. Continued vigilance, infection control, and treatment of CDI can help continue the trend of declining infection rates.
Subject(s)
Clostridioides difficile , Clostridium Infections , Colitis, Ulcerative , Crohn Disease , Inflammatory Bowel Diseases , Humans , Retrospective Studies , Inflammatory Bowel Diseases/complications , Inflammatory Bowel Diseases/epidemiology , Colitis, Ulcerative/complications , Colitis, Ulcerative/diagnosis , Colitis, Ulcerative/epidemiology , Crohn Disease/complications , Crohn Disease/diagnosis , Crohn Disease/epidemiology , Clostridium Infections/diagnosis , Clostridium Infections/epidemiology , Risk FactorsABSTRACT
BACKGROUND: Inflammatory bowel disease (IBD) is associated with increased health care utilization. Forecasting of high resource utilizers could improve resource allocation. In this study, we aimed to develop machine learning models (1) to cluster patients according to clinical utilization patterns and (2) to predict longitudinal utilization patterns based on readily available baseline clinical characteristics. METHODS: We conducted a retrospective study of adults with IBD at 2 academic centers between 2015 and 2021. Outcomes included different clinical encounters, new prescriptions of corticosteroids, and initiation of biologic therapy. Machine learning models were developed to characterize health care utilization. Poisson regression compared frequencies of clinical encounters. RESULTS: A total of 1174 IBD patients were followed for more than 5673 12-month observational windows. The clustering method separated patients according to low, medium, and high resource utilizers. In Poisson regression models, compared with low resource utilizers, moderate and high resource utilizers had significantly higher rates of each encounter type. Comparing moderate and high resource utilizers, the latter had greater utilization of each encounter type, except for telephone encounters and biologic therapy initiation. Machine learning models predicted longitudinal health care utilization with 81% to 85% accuracy (area under the receiver operating characteristic curve 0.84-0.90); these were superior to ordinal regression and random choice methods. CONCLUSION: Machine learning models were able to cluster individuals according to relative health care resource utilization and to accurately predict longitudinal resource utilization using baseline clinical factors. Integration of such models into the electronic medical records could provide a powerful semiautomated tool to guide patient risk assessment, targeted care coordination, and more efficient resource allocation.
ABSTRACT
Colorectal cancer is the second most deadly and third most common cancer in the world. Its development is heterogenous, with multiple mechanisms of carcinogenesis. Two distinct mechanisms include the adenoma-carcinoma sequence and the serrated pathway. The gut microbiome has been identified as a key player in the adenoma-carcinoma sequence, but its role in serrated carcinogenesis is less clear. In this study, we characterized the gut microbiome of 140 polyp-free and polyp-bearing individuals using colon mucosa and fecal samples to determine if microbiome composition was associated with each of the two key pathways. We discovered significant differences between the microbiomes of colon mucosa and fecal samples, with sample type explaining 10-15% of the variation observed in the microbiome. Multiple mucosal brushings were collected from each individual to investigate whether the gut microbiome differed between polyp and healthy intestinal tissue, but no differences were found. Mucosal aspirate sampling revealed that the microbiomes of individuals with tubular adenomas and serrated polyps were significantly different from each other and polyp-free individuals, explaining 1-4% of the variance in the microbiome. Microbiome composition also enabled the accurate prediction of subject polyp types using Random Forest, which produced an area under curve values of 0.87-0.99. By directly sampling the colon mucosa and distinguishing between the different developmental pathways of colorectal cancer, our study helps characterize potential mechanistic targets for serrated carcinogenesis. This research also provides insight into multiple microbiome sampling strategies by assessing each method's practicality and effect on microbial community composition.
Subject(s)
Adenoma , Carcinoma , Colonic Polyps , Colorectal Neoplasms , Gastrointestinal Microbiome , Adenoma/pathology , Carcinogenesis , Colonic Polyps/metabolism , Colonic Polyps/pathology , HumansABSTRACT
Mobile health has the potential to transform the management of chronic illnesses, expanding treatment from a purely clinic-based approach to a more patient-centered delivery of care. For patients with inflammatory bowel disease (IBD), a condition characterized by a relapsing and remitting course, adoption of mobile health strategies can promote improved quality of care delivery and clinical outcomes. Benefits of mobile health applications for IBD include tracking symptoms to guide disease management, coordinating data exchange across clinical care providers, increasing communication between patients and the care team, and providing educational materials to increase patient engagement and satisfaction. In this review, we present the current offerings for telemedicine systems and mobile applications designed for patients with IBD and discuss the potential advantages and limitations of utilizing mobile health in the care of these patients.
ABSTRACT
Colorectal cancer (CRC) is the third most commonly diagnosed cancer, the third leading cause of cancer-related deaths, and has been on the rise among young adults in the United States. Research has established that the colonic microbiome is different in patients with CRC compared to healthy controls, but few studies have investigated if and how the microbiome may relate to CRC progression through the serrated pathway versus the adenoma-carcinoma sequence.Our view is that progress in CRC microbiome research requires consideration of how the microbiome may contribute to CRC carcinogenesis through the distinct pathways that lead to CRC, which could enable the creation of novel and tailored prevention, screening, and therapeutic interventions. We first highlight the limitations in existing CRC microbiome research and offer corresponding solutions for investigating the microbiome's role in the adenoma-carcinoma sequence and serrated pathway. We then summarize the findings in the select human studies that included data points related to the two major carcinogenic pathways. These studies investigate the microbiome in CRC carcinogenesis and 1) utilize mucosal samples and 2) compare polyps or tumors by histopathologic type, molecular/genetic type, or location in the colon.Key findings from these studies include: 1) Fusobacterium is associated with right-sided, more advanced, and serrated lesions; 2) the colons of people with CRC have bacteria typically associated with normal oral flora; and 3) colons from people with CRC have more biofilms, and these biofilms are predominantly located in the proximal colon (single study).