What question did this study set out to answer?

To develop a mathematical framework for modeling cumulative glycemic exposure and its relationship with diabetic complications.

June 2, 2026Open Access

Glycation Corrosion Index (GCI) for Modeling Cumulative Glycemic Exposure and Multi-Organ Diabetic Complication Risk: A Mathematical Framework with Lo-Shu Spatial Visualization and NHANES-Based Exploratory Analysis

Key Points

To develop a mathematical framework for modeling cumulative glycemic exposure and its relationship with diabetic complications.
Utilized logistic regression to analyze NHANES data with focus on HbA1c, age, and sex.
Calculated Glycation Corrosion Index (GCI) and integral GCI (IGCI) for nine organ systems.
Conducted Cochran-Armitage trend tests for statistical assessment.
HbA1c shows no significant association with complications (OR=1.09, p=0.557).
Age significantly increases risk (OR=1.74, p=0.0005) and males have higher odds (OR=1.92, p<0.0001).
Cochran-Armitage trend test indicates no significant trend (Z=0.91, p=0.363).

Abstract

v2 (peer-review revised). Key changes: (1) Title revised to 'exploratory analysis'; (2) Lo-Shu repositioned as visualization scaffold only, not causal claim; (3) kᵢ derivation table with DCCT/EDIC + UKPDS sources added; (4) Full logistic regression: HbA1c OR=1. 09 p=0. 557 (ns), Age OR=1. 74 p=0. 0005 (***), Sex (M) OR=1. 92 p<0. 0001; (5) Bootstrap 95% CI for all HbA1c strata; (6) Cochran-Armitage trend test Z=0. 91 p=0. 363; (7) Null result reframed: cross-sectional HbA1c failure motivates IGCI. Core framework: GCI=max (HbA1c-5. 7, 0), IGCI=integral (GCI) dt, dDᵢ/dt = kᵢ*GCI - rᵢ*Dᵢ for nine organ systems.

Glycation Corrosion Index (GCI) for Modeling Cumulative Glycemic Exposure and Multi-Organ Diabetic Complication Risk: A Mathematical Framework with Lo-Shu Spatial Visualization and NHANES-Based Exploratory Analysis

Key Points

Abstract

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