Study of variation glycated haemoglobin in diabetic patients using PCA method. Case study: Moroccan eastern region

Oujidi, Wissale; Sekhsoukh, R.; Harrar, Youssef; Mehdi, Mohammed Amine

doi:10.1016/j.amsu.2022.104459

Cited by 1 publication

(1 citation statement)

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“…According to the PCA study, the first four principal axis factors accounted for a reasonable amount of overall variance (58.2%). Oujidi et al 45 found a significant connection between age and HbA1c in T2D patients using a PCA approach.…”

Section: Resultsmentioning

confidence: 99%

Multi-level analysis reveals the association between diabetes, body mass index, and HbA1c in an Iraqi population

Kowsar

Mansouri

2022

Sci Rep

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Type 2 diabetes (T2D) known as a complex metabolic disorder may cause health problems and changes in blood biochemical markers. A growing number of studies have looked into several biomarkers and their connections with T2D risk. However, few have explored the interconnection of these biomarkers, as well as the prospective alterations in the diabetes biomarker correlation network. We conducted a secondary analysis in order to introduce a multi-level approach to establish a relationship between diabetes, pre-diabetes, blood biochemical markers, age, and body mass index (BMI). The dataset was obtained from the Mendeley Data (available at https://data.mendeley.com/datasets/wj9rwkp9c2/1. In this study, three groups were established: non-diabetic (n = 103), pre-diabetic (n = 53), and diabetic (n = 844). According to the Heatmap analysis, non-diabetic and pre-diabetic individuals had the lowest BMI, age, and HbA1c. Diabetes and pre-diabetes were correlated with BMI (r = 0.58 and − 0.27, respectively), age (r = 0.47 and − 0.28, respectively), and HbA1c (r = 0.55 and − 0.21, respectively) using Pearson analysis. Using multivariate analysis, we found that diabetes, BMI, age, HbA1c, cholesterol, triglyceride, LDL, VLDL, and HDL were all associated. Network analysis revealed a connection between BMI and diabetes at the highest cut-off point. Moreover, receiver operating characteristic (ROC) analysis validated the network findings, revealing that BMI (area under the ROC curve, AUC = 0.95), HbA1c (AUC = 0.94), and age (AUC = 0.84) were the best predictors of diabetes. In conclusion, our multi-step study revealed that identifying significant T2D predictors, such as BMI and HbA1c, required a series of mathematical analyses.

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Section: Resultsmentioning

confidence: 99%