Prevalence, Risk Factors, and Sequelae of Asymptomatic Clostridioides difficile Colonization in Children with Cystic Fibrosis.

Patients with CF (pwCF) have high antibiotic use and an altered intestinal microbiome, known risk factors for infection with Clostridioides difficile. However, in adults with CF, C. difficile infection (CDI) is uncommon and asymptomatic colonization with C. difficile occurs frequently, for reasons that remain unclear. We investigated the rate, risk factors, and sequelae of asymptomatic C. difficile colonization in children with CF (cwCF). We identified that 32% of cwCF were colonized with C. difficile without acute gastrointestinal symptoms. Higher BMI and exposure to specific antibiotic classes (cephalosporins, fluoroquinolones, and vancomycin) were significantly associated with C. difficile colonization. No children developed symptomatic CDI in 90-days following enrollment.

Pediatric Fecal Microbiota Transplantation in Recurrent Clostridioides Difficile.

With the rising rates of Clostridioides (Clostridium) difficile infection (CDI) in children, recognizing the limitations of CDI-directed antibiotic therapy, especially in recurrent CDI (rCDI), is important. Fecal microbiota transplantation (FMT), which directly targets the underlying gut dysbiosis present in rCDI, is an important treatment option to consider in rCDI. This article will summarize indications, procedures, effectiveness, and the safety of FMT for rCDI in pediatric patients. [Pediatr Ann. 2021;50(12):e515-e521.].

Two-step Testing for Clostridioides Difficile is Inadequate in Differentiating Infection From Colonization in Children.

OBJECTIVES: Recent Infectious Disease Society of America guidelines recommend multistep testing algorithms to diagnose Clostridioides difficile infection (CDI), including a combination of nucleic acid amplification-based testing (NAAT) and toxin enzyme immunoassay (EIA). The use of these algorithms in children, including the ability to differentiate between C. difficile colonization and CDI, however, has not been evaluated. METHODS: We prospectively enrolled asymptomatic pediatric patients with cancer, cystic fibrosis (CF), or inflammatory bowel disease (IBD) and obtained a stool sample for NAAT testing. If positive by NAAT (colonized), EIA was performed. In addition, children with symptomatic CDI who tested positive by NAAT via the clinical laboratory were enrolled, and EIA was performed on residual stool. A functional cell cytotoxicity neutralization assay (CCNA) was also applied to stool samples from both the colonized and symptomatic cohorts. RESULTS: Of the 225 asymptomatic children enrolled in the study, 47 (21%) were colonized with C. difficile including 9/59 (15.5%) with cancer, 30/92 (32.6%) with CF, and 8/74 (10.8%) with IBD. An additional 41 children with symptomatic CDI were enrolled. When symptomatic and colonized children were compared, neither EIA positivity (44% vs 26%, P = 0.07) nor CCNA positivity (49% vs 45%, P = 0.70) differed significantly or were able to predict disease severity in the symptomatic cohort. CONCLUSIONS: Use of a multistep testing algorithm with NAAT followed by EIA failed to differentiate symptomatic CDI from asymptomatic colonization in our pediatric cohort. As multistep algorithms are moved into clinical care, the pediatric provider will need to be aware of their limitations.

Esophageal Mucosal Impedance Patterns Discriminate Patients With Eosinophilic Esophagitis From Patients With GERD.

BACKGROUND & AIMS: It is a challenge to make a diagnosis of eosinophilic esophagitis (EoE) because its symptoms and histologic features overlap with those of gastroesophageal reflux disease (GERD). A minimally invasive device was recently developed to detect mucosal impedance (MI) that measures epithelial integrity during upper endoscopy. We aimed to quantify MI along the esophagus and identify patterns that differentiated patients with and without GERD from those with EoE, and determine whether MI values and patterns are sufficient to identify patients with EoE using histologic findings as a reference. METHODS: We performed a retrospective analysis of 91 patients with upper gastrointestinal symptoms referred for diagnostic testing for GERD and EoE from 2012 through 2014 (discovery set). During the first endoscopy, MI measurements were obtained at 2, 5, and 10 cm from the squamocolumnar junction. GERD was confirmed by ambulatory pH tests, and histologic analyses of biopsies were used to confirm EoE. We then used statistical modeling to identify MI patterns along the esophagus (at 10 cm, 5 cm, and 2 cm) that associated with GERD vs EoE. We validated our findings in a prospective cohort of 49 patients undergoing elective upper endoscopy for dysphagia, from 2015 through 2016, testing the ability of MI patterns to identify patients with vs. without EoE. RESULTS: We found patients with EoE to have a unique MI pattern, with low values along the esophageal axis. MI measurements at 5 cm could discern patients with normal vs abnormal mucosa with 83% sensitivity and 79% specificity, and patients with EoE vs GERD with 84% sensitivity and 70% specificity; these measurements differentiated the patient populations with the highest level of accuracy of any of the 6 measurements tested. In the validation study, a rater using the esophageal MI pattern identified patients with EoE with 100% sensitivity and 96% specificity. CONCLUSION: We identified and validated a pattern of MI along the esophagus that can identify patients with EoE vs normal mucosa or GERD with high levels of sensitivity.

Modeling a microbial community and biodiversity assay with OBO Foundry ontologies: the interoperability gains of a modular approach.

The advent of affordable sequencing technology provides for a new generation of explorers who probe the world's microbial diversity. Projects such as Tara Oceans, Moorea Biocode Project and Gut Microbiome rely on sequencing technologies to probe community diversity. Either targeted gene surveys (also known as community surveys) or complete metagenomes are evaluated. The former, being the less costly of the two methods, relies on the identification of specific genomic regions, which can be used as a proxy to estimate genetic distance between related species in a Phylum. For instance, 16 S ribosomal RNA gene surveys are used to probe bacterial communities while internal transcribed spacer surveys, for example, can be used for probing fungal communities. With the explosion of projects and frenzy to explore new domains of life, scientists in the field have issued guidelines to report minimal information (following a checklist), ensuring that information is contextualized in a meaningful way. Yet the semantics of a checklist are not explicit. We demonstrate here how a tabular template can be used to collect information on microbial diversity using an explicit representation in the Resource Description Framework that is consistent with community agreed-upon knowledge representation patterns found in the Ontology for Biomedical Investigations.