Nocturnal Glycemic Stability Index
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Introduction
The Nocturnal Glycemic Stability Index (NGSI) is a novel quantitative metric designed to comprehensively assess overnight glucose stability by integrating amplitude, frequency, and temporal patterns of glycemic fluctuations. NGSI addresses this gap by providing a multidimensional, sensitive measure tailored to the nocturnal period, enhancing risk stratification and therapeutic optimization in diabetes management.
Objective
To develop and validate the NGSI, a novel metric designed to comprehensively quantify overnight glucose stability.
Method
This multi-cohort study analyzed CGM data from individuals with T1DM and T2DM using FDA-approved devices over at least two weeks. The NGSI, integrating amplitude, frequency, and temporal stability of nocturnal glucose fluctuations, was developed and optimized via machine learning. Validation included cross-cohort ROC analyses, descriptive statistics, and group comparisons using ANOVA or Kruskal-Wallis tests with Bonferroni correction (p < 0.05).
Results
A retrospective analysis of CGM data from three studies validated the NGSI for detecting nocturnal glycemic instability. Study 1 (n=23, T1DM) yielded an AUC-ROC of 0.80, study 1 (n=33,685, T1DM/T2DM) 0.85, and study 3 (n=31,034, T1DM/T2DM) 0.87. Descriptive statistics showed NGSI scores of 0.74 ± 0.09 (study 1), 0.71 ± 0.12 (study2), and 0.72 ± 0.11 (study 3). ANOVA revealed no significant differences (F=1.996, p=0.138), confirmed by Bonferroni-corrected post-hoc tests. Final Index Range: NGSI ∈, where 1 denotes perfect stability. Interpretation: NGSI > 0.8: Optimal nocturnal glycemic stability. 0.5 ≤NGSI ≤ 0.8: Moderate instability requiring monitoring. NGSI < 0.5: High instability necessitating therapeutic intervention.
Conclusion
NGSI offers a multidimensional, machine learning–optimized assessment of nocturnal glycemic stability, outperforming traditional metrics, but requires high-quality CGM data and further validation across diverse populations for clinical adoption.
