Visit-to-Visit Variability in Fasting Blood Glucose Predicts the New-Onset Heart Failure: Results From Two Large Chinese Cohorts

Control for multiple risk factors and incident heart failure and mortality in patients with diabetes mellitus: Insights from the Kailuan cohort study

BACKGROUND

This study evaluated the relationship between controlling multiple risk factors and diabetes-related heart failure and all-cause mortality, and the extent to which the excess risk can be reduced.

METHODS

17,676 patients with diabetes and 69,493 matched non-diabetic control subjects were included in the Kailuan study, with a median follow-up of 11.19 years. The risk factor control was defined by the attainment of target values for systolic blood pressure, body mass index, low-density lipoprotein cholesterol, fasting blood glucose, high-sensitive C-reactive protein and smoking. Fine-Gray and Cox models were used to estimate associations between the degree of risk factor control and risk of heart failure and all-cause mortality respectively.

RESULTS

Among diabetes patients, there was a gradual reduction in the risk of outcomes as the degree of risk factor control increased. For each additional risk factor that was controlled, there was an associated 16 % decrease in heart failure risk and a 10 % decrease in all-cause mortality risk. Among diabetes patients with ≥5 well-controlled risk factors, the adjusted hazard ratio compared to controls for heart failure and all-cause mortality was 1.25 (95 %CI: 0.99-1.56) and 1.17(95 %CI: 1.05-1.31) respectively. The protective effect of comprehensive risk factor control on the risk of heart failure was more pronounced in men and those using antihypertensive medications.

CONCLUSIONS

Control for multiple risk factors is associated with reduced heart failure and all-cause mortality risks in a cumulative and sex-specific manner. However, despite optimization of risk factor control, diabetes patients still face increased risks compared to the general population.

Association of cumulative blood glucose load with cardiovascular risk and all-cause mortality

BACKGROUND

Incorporation both the magnitude and duration of exposure to elevated fasting blood glucose (FBG) into a single risk parameter (cumulative FBG load) for future diseases is intuitively appealing, although a data-based demonstration of the utility of this metric is not available. This study aimed to investigate the associations with cumulative FBG load with the risk of cardiovascular diseases (CVD) and all-cause mortality in the general population.

METHODS

This prospective cohort study included 41,728 participants who were free of CVD and underwent four health examinations from 2006 to 2012. Cumulative FBG load during 2006-2012 was calculated as the area under curve for FBG values ≥ 5.6 mmol/L divided by the total area curve. We also compared the predicting value cumulative FBG load with other FBG metrics.

RESULTS

During a median follow-up of 6.75 years, we identified 2323 cases of CVD and 1724 cases of all-cause mortality. Per 1-standard deviation increase in cumulative FBG load was associated with a 16 % higher risk of CVD (hazard ratio [HR]: 1.16; 95 % confidence interval [CI], 1.13-1.20) and 20 % higher risk of all-cause mortality (HR, 1.20; 95 % CI, 1.16-1.25). For the prediction of cardiovascular outcomes and all-cause mortality, cumulative FBG load outperformed FBG time-in-target, visit-to-visit FBG variability, and mean FBG in terms of C-statistics and reclassification indexes.

CONCLUSIONS

Cumulative FBG load may provide a better prediction of cardiovascular outcomes compared with other FBG metrics in the general population. These findings emphasized the important role of cumulative FBG load in assessing cardiovascular and mortality risk.

Glucose fluctuations aggravate myocardial fibrosis via activating the CaMKII/Stat3 signaling in type 2 diabtetes

BACKGROUND

Glucose fluctuations (GF) are a risk factor for cardiovascular complications associated with type 2 diabetes. However, there is a lack of adequate research on the effect of GF on myocardial fibrosis and the underlying mechanisms in type 2 diabetes. This study aimed to investigate the impact of glucose fluctuations on myocardial fibrosis and explore the potential mechanisms in type 2 diabetes.

METHODS

Sprague Dawley (SD) rats were randomly divided into three groups: the control (Con) group, the type 2 diabetic (DM) group and the glucose fluctuations (GF) group. The type 2 diabetic rat model was established using a high-fat diet combined with low-dose streptozotocin injection and the GF model was induced by using staggered glucose and insulin injections daily. After eight weeks, echocardiography was used to assess the cardiac function of the three groups. Hematoxylin-eosin and Masson staining were utilized to evaluate the degree of pathological damage and fibrosis. Meanwhile, a neonatal rat cardiac fibroblast model with GF was established. Western and immunofluorescence were used to find the specific mechanism of myocardial fibrosis caused by GF.

RESULTS

Compared with rats in the Con and the DM group, cardiac function in the GF group showed significant impairments. Additionally, the results showed that GF aggravated myocardial fibrosis in vitro and in vivo. Moreover, Ca2+/calmodulin‑dependent protein kinase II (CaMKII) was activated by phosphorylation, prompting an increase in phosphorylation of signal transducer and activator of transcription 3 (Stat3) and induced nuclear translocation. Pretreatment with KN-93 (a CaMKII inhibitor) blocked GF-induced Stat3 activation and significantly suppressed myocardial fibrosis.

CONCLUSIONS

Glucose fluctuations exacerbate myocardial fibrosis by triggering the CaMKII/Stat3 pathway in type 2 diabetes.