Predicting the 10-year incidence of dyslipidemia based on novel anthropometric indices, using data mining

BACKGROUND

The aim was to establish a 10-year dyslipidemia incidence model, investigating novel anthropometric indices using exploratory regression and data mining.

METHODS

This data mining study was conducted on people who were diagnosed with dyslipidemia in phase 2 (n = 1097) of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study, who were compared with healthy people in this phase (n = 679). The association of dyslipidemia with several novel anthropometric indices including Conicity Index (C-Index), Body Roundness Index (BRI), Visceral Adiposity Index (VAI), Lipid Accumulation Product (LAP), Abdominal Volume Index (AVI), Weight-Adjusted-Waist Index (WWI), A Body Shape Index (ABSI), Body Mass Index (BMI), Body Adiposity Index (BAI) and Body Surface Area (BSA) was evaluated. Logistic Regression (LR) and Decision Tree (DT) analysis were utilized to evaluate the association. The accuracy, sensitivity, and specificity of DT were assessed through the performance of a Receiver Operating Characteristic (ROC) curve using R software.

RESULTS

A total of 1776 subjects without dyslipidemia during phase 1 were followed up in phase 2 and enrolled into the current study. The AUC of models A and B were 0.69 and 0.63 among subjects with dyslipidemia, respectively. VAI has been identified as a significant predictor of dyslipidemias (OR: 2.81, (95% CI: 2.07, 3.81)) in all models. Moreover, the DT showed that VAI followed by BMI and LAP were the most critical variables in predicting dyslipidemia incidence.

CONCLUSIONS

Based on the results, model A had an acceptable performance for predicting 10 years of dyslipidemia incidence. Furthermore, the VAI, BMI, and LAP were the principal anthropometric factors for predicting dyslipidemia incidence by LR and DT models.

Efficacy of mesenchymal stem cell therapy on glucose levels in type 2 diabetes mellitus: A systematic review and meta-analysis

AIMS/INTRODUCTION

In recent years, mesenchymal cellular therapies have received much attention in the treatment of diabetes. In this meta-analysis, we aimed to evaluate the efficacy of mesenchymal stem cell therapy in type 2 diabetes mellitus patients.

MATERIALS AND METHODS

A comprehensive literature search was carried out using PubMed, Scopus, Web of Science and Central databases. A total of 1,721 articles were identified, from which nine full-text clinical trials were qualified to enter the current meta-analysis. The assessment groups included patients with type 2 diabetes, and levels of C-peptide, glycosylated hemoglobin and insulin dose were analyzed before and after mesenchymal stem cell infusion. Data analysis was carried out in Stata version 11, and the Jadad Score Scale was applied for quality assessment.

RESULTS

Changes in levels of C-peptide after mesenchymal stem cell therapy were: standardized mean difference 0.20, 95% confidence interval -0.61 to 1.00, glycosylated hemoglobin levels were: standardized mean difference -1.45, 95% confidence interval -2.10 to -0.79 and insulin dose were: standardized mean difference -1.40, 95% confidence interval -2.88 to 0.09.

CONCLUSIONS

This meta-analysis of prospective studies showed associations between mesenchymal stem cell therapy and control of glucose level in patients with type 2 diabetes.