Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning

Abstract

Introduction Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and variability of HbA1c and lipids for adverse outcomes. Methods This retrospective cohort study consists of type 1 and type 2 diabetic patients who were prescribed insulin at outpatient clinics of Hong Kong public hospitals, from 1st January to 31st December 2009. Standard deviation (SD) and coefficient of variation were used to measure the variability of HbA1c, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and triglyceride. The primary outcome is all-cause mortality. Secondary outcomes were diabetes-related complications. Result The study consists of 25,186 patients (mean age = 63.0, interquartile range [IQR] of age = 15.1 years, male = 50%). HbA1c and lipid value and variability were significant predictors of all-cause mortality. Higher HbA1c and lipid variability measures were associated with increased risks of neurological, ophthalmological and renal complications, as well as incident dementia, osteoporosis, peripheral vascular disease, ischemic heart disease, atrial fibrillation and heart failure (p < 0.05). Significant association was found between hypoglycemic frequency (p < 0.0001), HbA1c (p < 0.0001) and lipid variability against baseline neutrophil-lymphocyte ratio (NLR). Conclusion Raised variability in HbA1c and lipid parameters are associated with an elevated risk in both diabetic complications and all-cause mortality. The association between hypoglycemic frequency, baseline NLR, and both HbA1c and lipid variability implicate a role for inflammation in mediating adverse outcomes in diabetes, but this should be explored further in future studies.

Pioglitazone Inhibits Diabetes-Induced Atrial Mitochondrial Oxidative Stress and Improves Mitochondrial Biogenesis, Dynamics, and Function Through the PPAR-γ/PGC-1α Signaling Pathway

“…Diabetes is a well-recognized risk factor for the development of AF (Xiong et al, 2018), adverse cardiovascular events (Lee et al, 2021a;Lee et al, 2021b), complications involving different organs (Lee et al, 2020), and mortality. Of the different classes of antidiabetic drugs, thiazolidinediones act by activating PPAR-γ (Lebovitz, 2019;Veettil et al, 2020).…”

Development of a predictive risk model for all-cause mortality in patients with diabetes in Hong Kong

“…Both measures have been associated with a higher risk of complications and mortality in patients with diabetes mellitus in both randomized controlled trials and real-world settings. [51][52][53][54][55] There are several methods that can be used to calculate variability, such as SD, CV and score based on the frequency exceeding a fixed percentage change in the absolute values. Prior studies have demonstrated the Cardiovascular and metabolic risk importance of such measures of variability in the prediction of adverse outcomes, 16 17 but a systematic and direct comparison of different methodologies has not been made with regard to their predictive performance.…”

The Effect of Berberine on Metabolic Profiles in Type 2 Diabetic Patients: A Systematic Review and Meta‐Analysis of Randomized Controlled Trials

“…Moreover, patients with T2DM are more likely to be overweight or obese, which indicates insulin resistance and dyslipidemia along with hyperglycemia [ 5 , 6 ]. For T2DM patients, glycemic or lipid values and their variability can significantly predict all-cause mortality and the occurrence of complications, including micro- and macrovascular complications [ 7 , 8 ]. Growing evidence has indicated that chronic inflammation, hyperglycemia, and dyslipidemia are all involved in insulin resistance, pathogenesis of T2DM, and systematic diabetic complications [ 9 , 10 ].…”