Long-term Predictions of Incident Coronary Artery Calcium to 85 Years of Age for Asymptomatic Individuals With and Without Type 2 Diabetes

Comprehensive Factors for Predicting the Complications of DiabetesMellitus: A Systematic Review

BACKGROUND

This article focuses on extracting a standard feature set for predicting the complications of diabetes mellitus by systematically reviewing the literature. It is conducted and reported by following the guidelines of PRISMA, a well-known systematic review and meta-analysis method. The research articles included in this study are extracted using the search engine "Web of Science" over eight years. The most common complications of diabetes, diabetic neuropathy, retinopathy, nephropathy, and cardiovascular diseases are considered in the study.

METHOD

The features used to predict the complications are identified and categorised by scrutinising the standards of electronic health records.

RESULT

Overall, 102 research articles have been reviewed, resulting in 59 frequent features being identified. Nineteen attributes are recognised as a standard in all four considered complications, which are age, gender, ethnicity, weight, height, BMI, smoking history, HbA1c, SBP, eGFR, DBP, HDL, LDL, total cholesterol, triglyceride, use of insulin, duration of diabetes, family history of CVD, and diabetes. The existence of a well-accepted and updated feature set for health analytics models to predict the complications of diabetes mellitus is a vital and contemporary requirement. A widely accepted feature set is beneficial for benchmarking the risk factors of complications of diabetes.

CONCLUSION

This study is a thorough literature review to provide a clear state of the art for academicians, clinicians, and other stakeholders regarding the risk factors and their importance.

Diabesity in Elderly Cardiovascular Disease Patients: Mechanisms and Regulators

Cardiovascular disease (CVD) is the leading cause of death in the world. In 2019, 550 million people were suffering from CVD and 18 million of them died as a result. Most of them had associated risk factors such as high fasting glucose, which caused 134 million deaths, and obesity, which accounted for 5.02 million deaths. Diabesity, a combination of type 2 diabetes and obesity, contributes to cardiac, metabolic, inflammation and neurohumoral changes that determine cardiac dysfunction (diabesity-related cardiomyopathy). Epicardial adipose tissue (EAT) is distributed around the myocardium, promoting myocardial inflammation and fibrosis, and is associated with an increased risk of heart failure, particularly with preserved systolic function, atrial fibrillation and coronary atherosclerosis. In fact, several hypoglycaemic drugs have demonstrated a volume reduction of EAT and effects on its metabolic and inflammation profile. However, it is necessary to improve knowledge of the diabesity pathophysiologic mechanisms involved in the development and progression of cardiovascular diseases for comprehensive patient management including drugs to optimize glucometabolic control. This review presents the mechanisms of diabesity associated with cardiovascular disease and their therapeutic implications.

The Relationship Between Lipoproteins and Insulin Sensitivity in Youth With Obesity and Abnormal Glucose Tolerance

CONTEXT

Youth with obesity and abnormal glucose tolerance have an increased risk for atherosclerosis but the relative contributions of insulin resistance and hyperglycemia to dyslipidemia and the development of subclinical atherosclerosis are unknown.

OBJECTIVE

This work aims to determine the association between insulin resistance, dyslipidemia, and carotid intimal thickness (cIMT) in adolescents with normal and abnormal glucose tolerance.

METHODS

An observational cohort study in 155 youth: 44 obese insulin sensitive (OIS; fasting insulin ≤ 20 µM/mL, body mass index [BMI] ≥ 95th percentile), 35 obese insulin resistant (OIR; fasting insulin > 20 µM/mL, BMI ≥ 95th percentile), 34 obese abnormal glucose tolerant (AGT; BMI ≥ 95th percentile), and 42 Lean (BMI 5th-85th percentile). Lipids, lipoprotein particle size and concentration (-P), insulin sensitivity (SI an intravenous glucose test), and CMIT were compared using linear models adjusted for age, race/ethnicity, biological sex, and Tanner stage. Lipid/lipoprotein profile and CMIT were reevaluated in a subset after 2 years.

RESULTS

Compared to OIS and Lean, OIR and AGT had elevated triglycerides and low high-density lipoprotein cholesterol (HDL-C) but similar total cholesterol and low-density lipoprotein cholesterol (LDL-C). Among OIS, OIR, AGT, lower SI was associated with atherogenic lipids (higher triglycerides, LDL-C, non-HDL-C, and lower HDL-C) and lipoproteins (higher total LDL-P and small HDL-P, and lower large HDL-P). There was a steeper decline in the association of SI with HDL-C and large HDL-P in AGT compared with OIR and OIS. cIMT was comparable across groups and inversely correlated with SI, with no change after 2 years.

CONCLUSION

Among youth with obesity, insulin resistance was associated with an atherogenic lipoprotein/lipid profile and cIMT, regardless of glucose tolerance status. Insulin resistance in AGT youth was associated with a shift to smaller HDL-P compared to normoglycemic youth with obesity. Alterations in HDL-P metabolism may be early adverse manifestations of hyperglycemia in youth with obesity.