Visceral Adipose Tissue Reduction Measured by Deep Neural Network Architecture Improved Reflux Esophagitis Endoscopic Grade.

INTRODUCTION: Visceral obesity is a risk factor for reflux esophagitis (RE). We investigated the risk of RE according to visceral adipose tissue (VAT) measured by deep neural network architecture using computed tomography (CT) and evaluated the longitudinal association between abdominal adipose tissue changes and the disease course of RE. METHODS: Individuals receiving health checkups who underwent esophagogastroduodenoscopy (EGD) and abdominal CT at Seoul National University Healthcare System Gangnam Center between 2015 and 2016 were included. Visceral and subcutaneous adipose tissue areas and volumes were measured using a deep neural network architecture and CT. The association between the abdominal adipose tissue area and volume and the risk of RE was evaluated. Participants who underwent follow-up EGD and abdominal CT were selected; the effects of changes in abdominal adipose tissue area and volume on RE endoscopic grade were investigated using Cox proportional hazards regression. RESULTS: We enrolled 6,570 patients who underwent EGD and abdominal CT on the same day. RE was associated with male sex, hypertension, diabetes, excessive alcohol intake, current smoking status, and levels of physical activity. The VAT area and volume increased the risk of RE dose-dependently. A decreasing VAT volume was significantly associated with improvement in RE endoscopic grade (hazard ratio: 3.22, 95% confidence interval: 1.82-5.71). Changes in subcutaneous adipose tissue volume and the disease course of RE were not significantly correlated. DISCUSSION: Visceral obesity is strongly associated with RE. VAT volume reduction was prospectively associated with improvement in RE endoscopic grade dose-dependently. Visceral obesity is a potential target for RE treatment.

Fasting glucose variability and risk of dementia in Parkinson's disease: a 9-year longitudinal follow-up study of a nationwide cohort.

Background: Diabetes is associated with an increased risk of Parkinson's disease dementia (PDD); however, it is unknown whether this association is dependent on continuous hyperglycemia, hypoglycemic events, or glycemic variability. We aimed to investigate the relationship between visit-to-visit fasting glucose variability and PDD development in patients with Parkinson's disease (PD). Methods: Using data from the Korean National Health Insurance Service, we examined 9,264 patients aged ≥40 years with de novo Parkinson's disease (PD) who underwent ≥3 health examinations and were followed up until December 2019. Glucose variability was measured using the coefficient of variation, variability independent of the mean, and average real variability. Fine and Gray competing regression analysis was performed to determine the effect of glucose variability on incident PDD. Results: During the 9.5-year follow-up period, 1,757 of 9,264 (19.0%) patients developed PDD. Patients with a higher visit-to-visit glucose variability had a higher risk of future PDD. In the multivariable adjusted model, patients with PD in the highest quartile (subdistribution hazard ratio [SHR] = 1.50, 95% CI 1.19 to 1.88), quartile 3 (SHR = 1.29, 95% CI 1.02 to 1.62), and quartile 2 (SHR = 1.30, 95% CI 1.04 to 1.63) were independently associated with a higher risk of PDD than those in the lowest quartile. Conclusion: We highlighted the effect of long-term glucose variability on the development of PDD in patients with PD. Furthermore, our findings suggest that preventive measures for constant glucose control may be necessary to prevent PDD.