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Fingerprinting hyperglycemia using predictive modelling approach based on low-cost routine CBC and CRP diagnostics
Amna Tahir1, Kashif Asghar2, Waqas Shafiq3
1Biomedical Informatics and Engineering Research Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, Pakistan.
This study found that combining inflammatory markers with Red Blood Cell (RBC) indices can accurately predict hyperglycemia and borderline hyperglycemia, aiding early diagnosis and intervention.
Area of Science:
- Endocrinology and Metabolism
- Hematology
- Clinical Diagnostics
Background:
- Hyperglycemia, a result of disrupted glucose homeostasis, is exacerbated by lifestyle factors and inflammation, contributing to diabetes mellitus (DM).
- The rising prevalence of type 2 diabetes necessitates early diagnostic and treatment strategies.
- Systemic inflammation and altered Red Blood Cell (RBC) indices are implicated in the pathophysiology of hyperglycemia.
Purpose of the Study:
- To evaluate the discriminatory capacity of inflammatory biomolecules and RBC indices in predicting hyperglycemia and borderline hyperglycemia.
- To develop predictive models for glycemic outcomes using clinical diagnostic data.
- To identify key predictors for different glycemia levels.
Main Methods:
- Retrospective analysis of 208,137 clinical diagnostic entries over five years.
- Inclusion of tests such as Hemoglobin A1c (HbA1c), Complete Blood Count (CBC), Fasting Blood Glucose (FBG), and C-reactive protein (CRP).
- Application of multivariate analysis (MANOVA) and univariate analysis (ANOVA) to identify significant predictors.
Main Results:
- Four glycemic predictive models developed for HbA1c and FBG cohorts, each exceeding 80% predictive accuracy (p < 0.0001).
- Significant discriminatory capacity identified for predictors of different glycemia levels.
- A novel predictor combining inflammatory markers and RBC indices demonstrated high sensitivity and specificity for predicting glycemic outcomes (ROC p < 0.0001).
Conclusions:
- The interplay between inflammation, RBC derangements, and glucose homeostasis can prognosticate hyperglycemic outcomes.
- A sensitive and specific predictor using inflammatory markers and RBC indices can aid in early hyperglycemia detection.
- This predictor can serve as a prophylactic intervention for identifying individuals at risk of hyperglycemia and borderline hyperglycemia.
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