Cross-sectional study finds associations between glucose monitoring metrics and corneal neuropathy, indicating clinical relevance.
Objective The relationship between corneal neuropathy measured by in vivo confocal microscopy (IVCM) and continuous glucose monitoring (CGM) remains unclear. We describe the associations between corneal neuropathy and CGM metrics. Methods A single center cross sectional study recruited people with type 2 diabetes. All participants wore a 14-day blinded Freestyle Libre Pro CGM and underwent corneal IVCM. Multiple generalized estimating equation models were created to study the association of independent variables (HbA1c and CGM metrics) on dependent variables (corneal nerve fiber and cellular metrics) adjusted for age, sex, ethnicity, hypertension, hyperlipidemia, BMI, diabetes duration. Benjamini–Hochberg procedure controlled for multiplicity. Results 307 people were recruited, 277 were included in the analysis. Median Age 58y, 49.5% female, 60.6% Chinese, BMI 26.6 kg/m², diabetes duration 12y, HbA1c 8.1%. HbA1c associated negatively (β= -0.609, pseudoR²= 0.068, p=0.013) with Corneal Nerve Fiber Density and positively (β= 0.003, pseudoR² = 0.066, p=0.027) with Corneal Nerve Fiber Width (CNFW). Time-in-Range and Time-in-Tight-Range negatively (β for both = -0.006, pseudoR²= 0.075 and 0.066, respectively, both p<0.03), and Time-Above-Range (β=0.006, pseudoR²=0.073, p=0.021) positively, associated with CNFW. Among Corneal Cellular metrics, Time-Above-Range (β=0.088, pseudoR² = 0.055, p=0.004), mean glucose (β=0.049, pseudoR²=0.055, p=0.004) and glucose variability (SD, MAGE and MODD; β= 0.13, 0.046, 0.164; pseudoR²= 0.053, 0.044, 0.060, respectively, all p<0.03) associated positively with average epithelial size, while Time-in-Range and Time-in-Tight-Range had a negative association (β= -0.084 and -0.104; pseudoR²= 0.052 and 0.057, respectively, both p<0.01). Conclusion CGM measures, including mean glycemia, TIR, TITR and glucose variability, were significantly associated with corneal neuropathy, supporting the role of CGM metrics in optimising glycemia.
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Chandran et al. (2026) studied this question.
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