The intestinal microbiota and obesity.

Obesity has been and continues to be an epidemic in the United States. Obesity has been addressed in multiple health initiatives, including Healthy People 2010, with no state meeting the proposed goal of a prevalence of obesity < 15% of the adult population. In contrast, obesity rates have continued to increase, with the self-reported prevalence of obesity among adults increasing by 1.1% from 2007 to the present. Indeed, since 2009, 33 states reported obesity prevalences of 25% or more with only 1 state reporting prevalence < 20%. There have been multiple approaches for the treatment of obesity, including fad diets, incentive-based exercise programs, and gastric bypass surgery; none of which have been optimal. In a murine model, it was shown that the majority of the intestinal microbiome consists of two bacterial phyla, the Bacteroidetes and the Firmicutes, and that the relative abundance of these two phyla differs among lean and obese mice; the obese mouse had a higher proportion of Firmicutes to Bacteroidetes (50% greater) than the lean mouse. The same results were appreciated in obese humans compared to lean subjects. The postulated explanation for this finding is that Firmicutes produce more complete metabolism of a given energy source than do Bacteroidetes, thus promoting more efficient absorption of calories and subsequent weight gain. Researchers were able to demonstrate that colonizing germ-free mice with the intestinal microbiome from obese mice led to an increased total body fat in the recipient mice despite a lack of change in diet. The converse, that, colonizing germ-free obese mice with the intestinal microbiome of thin mice causing a decreased total body fat in the recipient mice, has not yet been done. Other possible mechanisms by which the intestinal microbiome affects host obesity include induction of low-grade inflammation with lipopolysaccharide, regulation of host genes responsible for energy expenditure and storage, and hormonal communication between the intestinal microbiome and the host. The following review discusses the microbiome-obesity relationship and proposed mechanisms by which the intestinal microbiota is hypothesized to influence weight gain.

Risk stratification with video capsule endoscopy leads to fewer hospital admissions in emergency department patients with low-risk to moderate-risk upper gastrointestinal bleed: A multicenter clinical trial.

OBJECTIVE: In US emergency departments (EDs), the physician has limited ability to evaluate for common and serious conditions of the gastrointestinal (GI) mucosa such as a bleeding peptic ulcer. Although many bleeding lesions are self-limited, the majority of these patients require emergency hospitalization for upper endoscopy (EGD). We conducted a clinical trial to determine if ED risk stratification with video capsule endoscopy (VCE) reduces hospitalization rates for low-risk to moderate-risk patients with suspected upper GI bleeding. METHODS: We conducted a randomized controlled trial at 3 urban academic EDs. Inclusion criteria included signs of upper GI bleeding and a Glasgow Blatchford score <6. Patients were randomly assigned to 1 of the following 2 treatment arms: (1) an experimental arm that included VCE risk stratification and brief ED observation versus (2) a standard care arm that included admission for inpatient EGD. The primary outcome was hospital admission. Patients were followed for 7 and 30 days to assess for rebleeding events and revisits to the hospital. RESULTS: The trial was terminated early as a result of low accrual. The trial was also terminated early because of a need to repurpose all staff to respond to the coronavirus disease 2019 pandemic. A total of 24 patients were enrolled in the study. In the experimental group, 2/11 (18.2%) patients were admitted to the hospital, and in the standard of care group, 10/13 (76.9%) patients were admitted to the hospital (P = 0.012). There was no difference in safety on day 7 and day 30 after the index ED visit. CONCLUSIONS: VCE is a potential strategy to decrease admissions for upper GI bleeding, though further study with a larger cohort is required before this approach can be recommended.

Post-endoscopic procedure satisfaction scores: Can we improve?

AIM: To organize post-procedure satisfaction data into a useful reference and analyze patient-centered parameters to find trends that influence patient satisfaction. METHODS: A robust database of two cohorts of outpatients that underwent an endoscopic procedure at Georgetown University Hospital at two separate three-month intervals ranging from November 2012 to January 2013 and November 2015 to January 2016 was compiled. Time of year was identical to control for weather/seasonal issues that may have contributed to the patient experience. The variables recorded included age, sex, body mass index (BMI), type of procedure, indication for procedure, time of the procedure, length of the procedure, type of prep used, endoscopist, satisfactory score, and comments/reasons for score. For continuous variables, differences in averages were tested by two sample t-test, Wilcoxon rank sum test, and ANOVA as appropriate. For categorical variables, differences in proportions between two groups were tested by χ2 test. Correlation test and linear regression analyses were conducted to examine relationships between length of procedure and continuous predictors. A P value < 0.05 used to indicate statistically significant relationship. RESULTS: The primary outcome of this study was to assess if telephone outreach after an endoscopic intervention was a satisfactory method of obtaining post-procedure satisfaction scores from patients at a tertiary care center. With the addition of post-procedure calls, instilled in January 2014, the response rate was 40.5% (508/1256 patients) from a prior completion rate of 3.4% (31/918) with the mail out survey initially. There was a statistically significant improved response rate pre and post intervention with P < 0001. The secondary outcome of this study was to assess if we could use predictive analytics to identify independent predictors of procedure length, such as gender, age, type of procedure, time of procedure, or BMI. The combined pre and post intervention data was used in order to optimize the power to identify independent predictors of procedure length. The total number of patient's data analyzed was 2174. There was no statistically significant difference in procedure length between males and females with P value 0.5282. However, there was a small (1 min), but statistically significant difference (P = 0.0185) in procedure length based on the time of day the procedure took place, with afternoon procedures having a longer duration than morning procedures. The type of procedure was an independent predictor of procedure length as demonstrated with P value < 0.0001. There is a statistically significant correlation between age and procedure length, although it is only a weak relationship with a correlation coefficient < 0.3. Contrary to patient age, BMI did not have a statistically significant correlation with procedure length (P = 0.9993), which was also confirmed by linear regression analysis. CONCLUSION: Our study proves calling patients after endoscopy improves post-procedure satisfaction response rates and changing procedural time allotment based on patient characteristics would not change endoscopic workflow.