Increased risk of incident diabetes in patients with MAFLD not meeting the criteria for NAFLD.

We aimed to compare the risk of incident diabetes according to fatty liver disease (FLD) definition, focusing on the comparison between those who met criteria for either metabolic dysfunction-associated fatty liver disease (MAFLD) or nonalcoholic fatty liver disease (NAFLD) but not the other. This was a 5.0-year (interquartile range, 2.4-8.2) retrospective longitudinal cohort study of 21,178 adults who underwent at least two serial health checkup examinations. The presence of hepatic steatosis was determined by abdominal ultrasonography at the first health examination. Cox proportional hazard analyses were used to compare the risk of incident diabetes among five groups. Incident diabetes cases occurred in 1296 participants (6.1%). When non-FLD without metabolic dysfunction (MD) group was set as a reference, the risk of incident diabetes increased in the order of NAFLD-only, non-FLD with MD, both FLD, and MAFLD-only groups. The presence of excessive alcohol consumption and/or hepatitis B virus (HBV)/hepatitis C virus (HCV) infection, FLD, and MD synergistically increased the risk of incident diabetes. MAFLD-only group showed a greater increase in incidence of diabetes than non-FLD with MD and NAFLD-only groups. The interaction among excessive alcohol consumption, HBV/HCV infection, MD, and hepatic steatosis on the development of diabetes should not be overlooked.

MAFLD and NAFLD in the prediction of incident chronic kidney disease.

Whether metabolic dysfunction-associated fatty liver disease (MAFLD) can replace nonalcoholic fatty liver disease (NAFLD) is under debate. This study evaluated which definition better predicted incident chronic kidney disease (CKD). This was a 5.3-year (range, 2.8-8.3) retrospective cohort study of 21,713 adults who underwent at least two serial health examinations. Cox analyses were used to compare the risk of incident CKD among non-fatty liver disease (FLD) without metabolic dysregulation (MD; reference), non-FLD with MD, MAFLD-only, NAFLD-only, or both-FLD groups. Non-FLD with MD group (hazard ratio [HR] 1.23, 95% confidence interval [CI] 1.00-1.53), both-FLD group (HR 1.50, 95% CI 1.19-1.89), and MAFLD-only group (HR 1.97, 95% CI 1.49-2.60), but not NAFLD-only group (HR 1.06, 95% CI 0.63-1.79) demonstrated an increased risk of CKD. The increased risk of CKD was significant in MAFLD subgroups with overweight/obesity (HR 2.94, 95% CI 1.91-4.55), diabetes (HR 2.20, 95% CI 1.67-2.90), MD only (HR 1.50, 95% CI 1.19-1.89), excessive alcohol consumption (HR 2.71, 95% CI 2.11-3.47), and viral hepatitis (HR 2.38, 95% CI 1.48-3.84). The switch from NAFLD to MAFLD criteria may identify a greater number of individuals at CKD risk. The association was also significant in MAFLD patients with excessive alcohol consumption or viral hepatitis.

Prediction Algorithms for Blood Pressure Based on Pulse Wave Velocity Using Health Checkup Data in Healthy Korean Men: Algorithm Development and Validation.

BACKGROUND: Pulse transit time and pulse wave velocity (PWV) are related to blood pressure (BP), and there were continuous attempts to use these to predict BP through wearable devices. However, previous studies were conducted on a small scale and could not confirm the relative importance of each variable in predicting BP. OBJECTIVE: This study aims to predict systolic blood pressure and diastolic blood pressure based on PWV and to evaluate the relative importance of each clinical variable used in BP prediction models. METHODS: This study was conducted on 1362 healthy men older than 18 years who visited the Samsung Medical Center. The systolic blood pressure and diastolic blood pressure were estimated using the multiple linear regression method. Models were divided into two groups based on age: younger than 60 years and 60 years or older; 200 seeds were repeated in consideration of partition bias. Mean of error, absolute error, and root mean square error were used as performance metrics. RESULTS: The model divided into two age groups (younger than 60 years and 60 years and older) performed better than the model without division. The performance difference between the model using only three variables (PWV, BMI, age) and the model using 17 variables was not significant. Our final model using PWV, BMI, and age met the criteria presented by the American Association for the Advancement of Medical Instrumentation. The prediction errors were within the range of about 9 to 12 mmHg that can occur with a gold standard mercury sphygmomanometer. CONCLUSIONS: Dividing age based on the age of 60 years showed better BP prediction performance, and it could show good performance even if only PWV, BMI, and age variables were included. Our final model with the minimal number of variables (PWB, BMI, age) would be efficient and feasible for predicting BP.

Mean and visit-to-visit variability of glycemia and left ventricular diastolic dysfunction: A longitudinal analysis of 3025 adults with serial echocardiography.

OBJECTIVE: We aimed to determine the mean glucose thresholds to increase the risk of left ventricular diastolic dysfunction (LVDD) and whether visit-to-visit variability of fasting plasma glucose (FPG) and glycated hemoglobin (A1C) could independently increase the risk in a cohort with serial echocardiography. METHODS: This was a 3.5-year (range, 0.5-8.3) retrospective longitudinal cohort study of 3025 adults (age, 55.15 ±â€¯7.6 years; without diabetes, n = 2755) with LV ejection fraction > 50% by serial echocardiography between 2006 and 2016. Mean, standard of deviation (SD) and coefficient of variation (CV) of FPG and A1C obtained from three consecutive measurements preceding the first echocardiography. The definition of LVDD in this study was primarily based on early peak mitral inflow velocity and early diastolic mitral annulus motion velocity. RESULTS: LVDD developed in 611/3025 subjects (20.2%). Cox proportional hazard models showed increased adjusted hazard ratios (HRs) for incident LVDD in the highest quartile of FPG-mean (HR 1.76, 95% confidence interval [CI]; 1.36-2.30), FPG-SD (HR 1.63, 95% CI; 1.27-2.09), FPG-CV (HR 1.47, 95% CI; 1.15-1.89), and A1C-mean (HR 1.83, 95% CI; 1.41-2.38) versus the lowest quartile, which was consistent even in subjects without diabetes. Mean glucose thresholds for the increased risk were below the lower limits for pre-diabetes. CONCLUSIONS: In terms of mean glycemia, LVDD may be initiated in the earliest diabetic continuum, and such changes could be measurable within several years. Visit-to-visit variability of FPG, but not that of A1C, predicted accelerated development of LVDD.