Chemometric exploratory data analysis for patients with diabetes type 2 and diabetic complications

Abstract

Abstract The present study deals with the interpretation and modeling of clinical data for patients with diabetes mellitus type 2 (DMT2) additionally diagnosed with complications of the disease by the use of multivariate statistical methods. The major goal is to determine some specific clinical descriptors characterizing each health problem by applying the options of the exploratory data analysis. The results from the statistical analysis are commented in details by medical reasons for each of the complications. It was found that each of the complications is characterized by specific medical descriptors linked into each one of the five latent factors identified by factor and principal components analysis. Such an approach to interpret concomitant to DMT2 complications is original and allows a better understanding of the role of clinical parameters for diagnostic and prevention goals.