The Gut Microbiome Alterations in Pediatric Patients with Functional Abdominal Pain Disorders.

In this prospective longitudinal study, we enrolled 54 healthy pediatric controls and 28 functional abdominal pain disorders (FAPDs) pediatric patients (mean age was 11 ± 2.58 years old). Fecal samples and symptom questionnaires were obtained from all participants over the course of the year. Clinical data assessment showed that FAPDs patients were more symptomatic than the control group. Microbiome analysis revealed that Phylum Bacteroidetes was higher in FAPDs compared to the control group (p < 0.05), while phylum Firmicutes was lower in FAPDs (p < 0.05). In addition, Verrucomicrobiota was higher in the control group than the FAPDs (p < 0.05). At the genus level the relative abundance of 72 bacterial taxa showed statistically significant differences between the two groups and at the school term levels. In the control group, Shannon diversity, Observed_species, and Simpson were higher than the FAPDs (p < 0.05), and beta diversity showed differences between the two groups (PERMANOVA = 2.38; p = 0.002) as well. Using linear discriminant analysis effect size (LEfSe), Enterobacteriaceae family and Megaspherae showed increased abundances in vacation term (LDA score > 2.0, LEfSe, p < 0.05). In the FAPDs group, the severity of symptoms (T-scores) correlated with 11 different taxa bacterial relative abundances using Pearson's correlation and linear regression analyses. Our data showed that gut microbiome is altered in FAPDs compared to the control. Differences in other metrics such as alpha- and beta diversity were also reported between the two groups. Correlation of the severity of the disease (T-scores) correlated with gut microbiome. Finally, our findings support the use of Faecalibacterium/Bacteroides ratio as a potential diagnostic biomarker for FAPDs.

Using a Clinical Workflow Analysis to Enhance eHealth Implementation Planning: Tutorial and Case Study.

eHealth apps often fail to improve clinical outcomes due to poor integration with clinical workflow-the sequence and personnel needed to undertake a series of tasks for clinical care. Our central thesis is that eHealth interventions will be more effective if the clinical workflow is studied and taken into consideration for intervention implementation. This paper aims to provide an introductory tutorial on when and how to use a clinical workflow analysis to guide the implementation of eHealth interventions. The tutorial includes a step-by-step guide to conducting a clinical workflow analysis in planning for eHealth implementation. We began with a description of why a clinical workflow analysis is best completed before the implementation of eHealth interventions. Next, we described 4 steps needed to perform the clinical workflow analysis: the identification of discrete workflow components, workflow assessment, triangulation, and the stakeholder proposal of intervention implementation. Finally, we presented a case study of a clinical workflow analysis, which was conducted during patient visits of patients aged 11 or 12 years from 4 diverse pediatric or family medicine clinics to plan the implementation of a tablet-based app for adolescent vaccination. Investigators planning the implementation of new eHealth interventions in health care settings can use the presented steps to assess clinical workflow, thereby maximizing the match of their intervention with the clinical workflow. Conducting a prospective workflow study allows for evidence-based planning, identifying potential pitfalls, and increasing stakeholder buy-in and engagement. This tutorial should aid investigators in increasing the successful implementation of eHealth interventions.

Challenges and lessons learned from clinical pharmacogenetic implementation of multiple gene-drug pairs across ambulatory care settings.

PURPOSE: Incorporating a patient's genotype into the clinical decision-making process is one approach to precision medicine. The University of Florida (UF) Health Precision Medicine Program is a pharmacist-led multidisciplinary effort that has led the clinical implementation of six gene-drug(s) pairs to date. This study focuses on the challenges encountered and lessons learned with implementing pharmacogenetic testing for three of these: CYP2D6-opioids, CYP2D6/CYP2C19-selective serotonin reuptake inhibitors, and CYP2C19-proton pump inhibitors within six pragmatic clinical trials at UF Health and partners. METHODS: We compared common measures collected within each of the pharmacogenetic implementations as well as solicited feedback from stakeholders to identify challenges, successes, and lessons learned. RESULTS: We identified several challenges related to trial design and implementation, and learned valuable lessons. Most notably, case discussions are effective for prescriber education, prescribers need clear concise guidance on genotype-based actions, having genotype results available at the time of the patient-prescriber encounter helps optimize the ability to act on them, children prefer noninvasive sample collection, and study participants are willing to answer patient-reported outcomes questionnaires if they are not overly burdensome, among others. CONCLUSION: The lessons learned from implementing three gene-drug pairs in ambulatory care settings will help shape future pharmacogenetic clinical trials and clinical implementations.