Early Glucose Derangement Detected by Continuous Glucose Monitoring and Progression of Liver Fibrosis in Nonalcoholic Fatty Liver Disease: An Independent Predictive Factor?

Two-week continuous glucose monitoring-derived metrics and degree of hepatic steatosis: a cross-sectional study among Chinese middle-aged and elderly participants

BACKGROUND

Continuous glucose monitoring (CGM) devices provide detailed information on daily glucose control and glycemic variability. Yet limited population-based studies have explored the association between CGM metrics and fatty liver. We aimed to investigate the associations of CGM metrics with the degree of hepatic steatosis.

METHODS

This cross-sectional study included 1180 participants from the Guangzhou Nutrition and Health Study. CGM metrics, covering mean glucose level, glycemic variability, and in-range measures, were separately processed for all-day, nighttime, and daytime periods. Hepatic steatosis degree (healthy: n = 698; mild steatosis: n = 242; moderate/severe steatosis: n = 240) was determined by magnetic resonance imaging proton density fat fraction. Multivariate ordinal logistic regression models were conducted to estimate the associations between CGM metrics and steatosis degree. Machine learning models were employed to evaluate the predictive performance of CGM metrics for steatosis degree.

RESULTS

Mean blood glucose, coefficient of variation (CV) of glucose, mean amplitude of glucose excursions (MAGE), and mean of daily differences (MODD) were positively associated with steatosis degree, with corresponding odds ratios (ORs) and 95% confidence intervals (CIs) of 1.35 (1.17, 1.56), 1.21 (1.06, 1.39), 1.37 (1.19, 1.57), and 1.35 (1.17, 1.56) during all-day period. Notably, lower daytime time in range (TIR) and higher nighttime TIR were associated with higher steatosis degree, with ORs (95% CIs) of 0.83 (0.73, 0.95) and 1.16 (1.00, 1.33), respectively. For moderate/severe steatosis (vs. healthy) prediction, the average area under the receiver operating characteristic curves were higher for the nighttime (0.69) and daytime (0.66) metrics than that of all-day metrics (0.63, P < 0.001 for all comparisons). The model combining both nighttime and daytime metrics achieved the highest predictive capacity (0.73), with nighttime MODD emerging as the most important predictor.

CONCLUSIONS

Higher CGM-derived mean glucose and glycemic variability were linked with higher steatosis degree. CGM-derived metrics during nighttime and daytime provided distinct and complementary insights into hepatic steatosis.

Glycemic variability assessed using continuous glucose monitoring in individuals without diabetes and associations with cardiometabolic risk markers: A systematic review and meta-analysis

BACKGROUND & AIMS

Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes.

METHODS

Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for ≥24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta-analyzes were performed, depending on outcome.

RESULTS

Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease.

CONCLUSION

GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes.

Wearable Devices Beyond Activity Trackers in Youth With Obesity: Summary of Options

Background: Current treatment protocols to prevent and treat pediatric obesity focus on prescriptive lifestyle interventions. However, treatment outcomes are modest due to poor adherence and heterogeneity in responses. Wearable technologies offer a unique solution as they provide real-time biofeedback that could improve adherence to and sustainability of lifestyle interventions. To date, all reviews on wearable devices in pediatric obesity cohorts have only explored biofeedback from physical activity trackers. Hence, we conducted a scoping review to (1) catalog other biofeedback wearable devices available in this cohort, (2) document various metrics collected from these devices, and (3) assess safety and adherence to these devices. Methods: This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Fifteen eligible studies examined the use of biofeedback wearable devices beyond activity trackers in pediatric cohorts, with an emphasis on feasibility of these devices. Results: Included studies varied in sample sizes (15-203) and in ages 6-21 years. Wearable devices are being used to capture various metrics of multicomponent weight loss interventions to provide more insights about glycemic variability, cardiometabolic function, sleep, nutrition, and body fat percentage. High safety and adherence rates were reported among these devices. Conclusions: Available evidence suggests that wearable devices have several applications aside from activity tracking, which could modify health behaviors through real-time biofeedback. Overall, these devices appear to be safe and feasible so as to be employed in various settings in the pediatric age group to prevent and treat obesity.

NAFLD Fibrosis Progression and Type 2 Diabetes: The Hepatic-Metabolic Interplay

The bidirectional relationship between type 2 diabetes and (non-alcoholic fatty liver disease) NAFLD is indicated by the higher prevalence and worse disease course of one condition in the presence of the other, but also by apparent beneficial effects observed in one, when the other is improved. This is partly explained by their belonging to a multisystemic disease that includes components of the metabolic syndrome and shared pathogenetic mechanisms. Throughout the progression of NAFLD to more advanced stages, complex systemic and local metabolic derangements are involved. During fibrogenesis, a significant metabolic reprogramming occurs in the hepatic stellate cells, hepatocytes, and immune cells, engaging carbohydrate and lipid pathways to support the high-energy-requiring processes. The natural history of NAFLD evolves in a variable and dynamic manner, probably due to the interaction of a variable number of modifiable (diet, physical exercise, microbiota composition, etc.) and non-modifiable (genetics, age, ethnicity, etc.) risk factors that may intervene concomitantly, or subsequently/intermittently in time. This may influence the risk (and rate) of fibrosis progression/regression. The recognition and control of the factors that determine a rapid progression of fibrosis (or its regression) are critical, as the fibrosis stages are associated with the risk of liver-related and all-cause mortality.

Excessive gluconeogenesis causes the hepatic insulin resistance paradox and its sequelae

Background

Hepatic insulin signaling suppresses gluconeogenesis but promotes de novo lipid synthesis. Paradoxically, hepatic insulin resistance (HIR) enhances both gluconeogenesis and de novo lipid synthesis. Elucidation of the etiology of this paradox, which participates in the pathogenesis of non-alcoholic fatty liver disease (NAFLD), cardiovascular disease, the metabolic syndrome and hepatocellular carcinoma, has not been fully achieved.

Scope of review

This article briefly outlines the previously proposed hypotheses on the etiology of the HIR paradox. It then discusses literature consistent with an alternative hypothesis that excessive gluconeogenesis, the direct effect of HIR, is responsible for the aberrant lipogenesis. The mechanisms involved therein are explained, involving de novo synthesis of fructose and uric acid, promotion of glutamine anaplerosis, and induction of glucagon resistance. Thus, gluconeogenesis via lipogenesis promotes hepatic steatosis, a component of NAFLD, and dyslipidemia. Gluconeogenesis-centred mechanisms for the progression of NAFLD from simple steatosis to non-alcoholic steatohepatitis (NASH) and fibrosis are suggested. That NAFLD often precedes and predicts type 2 diabetes is explained by the ability of lipogenesis to cushion against blood glucose dysregulation in the earlier stages of NAFLD.

Major conclusions

HIR-induced excessive gluconeogenesis is a major cause of the HIR paradox and its sequelae. Such involvement of gluconeogenesis in lipid synthesis rationalizes the fact that several types of antidiabetic drugs ameliorate NAFLD. Thus, dietary, lifestyle and pharmacological targeting of HIR and hepatic gluconeogenesis may be a most viable approach for the prevention and management of the HIR-associated network of diseases.

Use of continuous glucose monitoring in obesity research: A scoping review

BACKGROUND

This scoping review provides a timely synthesis of the use of continuous glucose monitoring in obesity research with considerations to adherence to continuous glucose monitor devices and metrics most frequently reported.

METHODS

This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Eligible studies (n = 31) evaluated continuous glucose monitor use in research on participants, of all ages, with overweight or obesity.

RESULTS

Reviewed studies varied in duration from one to 84 days (mean: 8.74 d, SD 15.2, range 1-84 d) with 889 participants total (range: 11-118 participants). Across all studies, the mean percent continuous glucose monitor wear time (actual/intended wear time in days) was 92% (numerator - mean: 266.1 d, SD: 452, range: 9-1596 d/denominator - mean: 271.6 d, SD: 451.5, range: 9-1596 d). Continuous glucose monitoring was utilized to provide biofeedback (n = 2, 6%), monitor dietary adherence (n = 2, 6%), and assess glycemic variability (n = 29, 93%). The most common variability metrics reported were standard deviation (n = 19, 62%), area under the curve (n = 12, 39%), and glycemic range (n = 12, 39%).

CONCLUSIONS

Available evidence suggests that continuous glucose monitoring is a well-tolerated and versatile tool for obesity research in pediatric and adult patients. Future investigation is needed to substantiate the feasibility and utility of continuous glucose monitors in obesity research and maximize comparability across studies.

Association between Liver Cirrhosis and Diabetes Mellitus: A Review on Hepatic Outcomes

BACKGROUND

Liver cirrhosis (LC) is largely associated with diabetes mellitus (DM). More than 80% of patients with LC manifest glucose intolerance and about 30% have type 2 DM. A particular and yet unrecognized entity is hepatogenous diabetes (HD), defined as impaired glucose regulation caused by altered liver function following LC. Numerous studies have shown that DM could negatively influence liver-related outcomes.

AIM

We aimed to investigate whether patients with LC and DM are at higher risk for hepatic encephalopathy (HE), variceal hemorrhage (VH), infections and hepatocellular carcinoma (HCC). The impact of DM on liver transplant (LT) outcomes was also addressed.

METHODS

Literature search was performed in PubMed, Ovid, and Elsevier databases. Population-based observational studies reporting liver outcomes in patients with LC were included.

RESULTS

Diabetics are at higher risk for HE, including post-transjugular intrahepatic portosystemic shunt HE. DM also increases the risk of VH and contributes to elevated portal pressure and variceal re-bleeding, while uncontrolled DM is associated with increased risk of bacterial infections. DM also increases the risk of HCC and contributes to adverse LT outcomes.

CONCLUSIONS

Patients with DM and LC may benefit from close follow-up in order to reduce readmissions and mortality. Due to the heterogeneity of available research, prospective multicenter clinical trials are needed to further validate these findings.

Hemoglobin A1c Has Suboptimal Performance to Diagnose and Monitor Diabetes Mellitus in Patients with Cirrhosis

BACKGROUND

Glycated hemoglobin A1c (HbA1c) is routinely used to diagnose and monitor type 2 diabetes mellitus (T2DM) in cirrhotic patients. Remarkably, HbA1c may be falsely low in such patients.

AIMS

We assessed the diagnostic and monitoring yield of HbA1c in cirrhotic patients with T2DM (DM-Cirr) and without T2DM (NoDM-Cirr).

METHODS

We conducted a composite study allocating 21 NoDM-Cirr into a cross-sectional module and 16 DM-Cirr plus 13 controls with T2DM only (DM-NoCirr) into a prospective cohort. Oral glucose tolerance test (OGTT) was performed in NoDM-Cirr. DM-Cirr and DM-NoCirr were matched by sex, age, BMI, and T2DM treatment and studied with continuous glucose monitoring (CGM). Percent deviations from target, low/high blood glucose indexes (LBGI/HBGI) were calculated from CGM, as well as the average daily risk range (ADRR) as a marker of glucose variability.

RESULTS

Overall, HbA1c and OGTT diagnostic yield agreed in 12 patients (57%, ρ = 0.45, p < 0.03). CGM captured 3463 glucose determinations in DM-Cirr and 4273 in DM-NoCirr (p = 0.42). Regression analysis showed an inferior association between HbA1c and CGM in DM-Cirr (R² = 0.52), when compared to DM-NoCirr (R² = 0.94), and fructosamine did not improve association for DM-Cirr (R² = 0.31). Interestingly, cirrhosis and Child-Turcotte-Pugh class accounted for HbA1c variance (p < 0.05). Patients in DM-Cirr were less frequently within target glucose (70-180 mg/dL), but at higher risk for hyperglycemia (HBGI > 9) when compared to DM-NoCirr, and they also showed higher glucose variability (ADRR 13.9 ± 2.5 vs. 8.9 ± 1.8, respectively, p = 0.03).

CONCLUSION

HbA1c inaccurately represents chronic glycemia in patients with cirrhosis, likely in relation to increased glucose variability.

A Noninvasive Score Model for Prediction of NASH in Patients with Chronic Hepatitis B and Nonalcoholic Fatty Liver Disease

Aims. To develop a noninvasive score model to predict NASH in patients with combined CHB and NAFLD. Objective and Methods. 65 CHB patients with NAFLD were divided into NASH group (34 patients) and non-NASH group (31 patients) according to the NAS score. Biochemical indexes, liver stiffness, and Controlled Attenuation Parameter (CAP) were determined. Data in the two groups were compared and subjected to multivariate analysis, to establish a score model for the prediction of NASH. Results. In the NASH group, ALT, TG, fasting blood glucose (FBG), M30 CK-18, CAP, and HBeAg positive ratio were significantly higher than in the non-NASH group (P < 0.05). Multivariate analysis showed that CK-18 M30, CAP, FBG, and HBVDNA level were independent predictors of NASH. Therefore, a new model combining CK18 M30, CAP, FBG, and HBVDNA level was established using logistic regression. The AUROC curve predicting NASH was 0.961 (95% CI: 0.920-1.00, cutoff value is 0.218), with a sensitivity of 100% and specificity of 80.6%. Conclusion. A noninvasive score model might be considered for the prediction of NASH in patients with CHB combined with NAFLD.

High predictability of impaired glucose tolerance by combining cardiometabolic screening parameters in obese children

BACKGROUND

There is debate on which overweight and obese children should be screened for the presence of impaired glucose tolerance (IGT) by oral glucose tolerance testing (OGTT). The objective of the study was to identify risk factors predictive of the presence of IGT.

METHODS

In a cohort of overweight children, who underwent OGTT, we determined the association of anthropometric and laboratory parameters with IGT and whether combining parameters improved the sensitivity of screening for IGT.

RESULTS

Out of 145 patients, IGT was present in 11, of whom two had impaired fasting glucose (IFG). Elevated blood pressure (p=0.025) and elevated liver enzymes (p=0.003) were associated with IGT, whereas IFG was not (p=0.067), screening patients with either one of these parameters predicted IGT with a high sensitivity of 1.00, and a number needed to screen of 5.7.

CONCLUSIONS

Screening all patients with either IFG, presence of elevated blood pressure and elevated liver enzymes, significantly increases predictability of IGT compared to using IFG alone.