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CGM-Derived Glycemic Persistence Index Predicts OGTT 2-Hour Glucose in Dysglycemia

CGM-Derived Glycemic Persistence Index Predicts OGTT 2-Hour Glucose in Dysglycemia
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Key Takeaway
Consider GPI as a complementary CGM metric for OGTT glucose prediction and dysglycemia classification, but do not replace OGTT.

In an observational cohort study of adults with paired free-living continuous glucose monitoring (CGM) and oral glucose tolerance testing (OGTT), researchers evaluated the glycemic persistence index (GPI) as a CGM-derived metric. The primary aim was to predict OGTT 2-hour glucose, with secondary aims including day-to-day repeatability of CGM metrics and classification of OGTT-defined dysglycemia. The cohort size, setting, and follow-up duration were not reported.

For the primary outcome, GPI was the strongest single predictor of OGTT 2-hour glucose, with an LOO R^2 = 0.439. Day-to-day repeatability of GPI was strong, with an ICC = 0.665. For classifying OGTT-defined dysglycemia, HbA1c had a slightly higher AUC than GPI, but the combination of GPI plus HbA1c performed best overall, indicating complementary information.

No adverse events, serious adverse events, discontinuations, or tolerability data were reported. Key limitations include the absence of reported sample size, setting, and follow-up duration. As an observational cohort study, associations are reported, not causation, and results are based on a single cohort, so generalizability and external validity are not established.

Practice relevance is restrained: GPI may serve as a convenient CGM-derived marker of dysglycemia that could reduce reliance on burdensome OGTT, but it should not be considered a replacement for OGTT, and clinical utility beyond prediction and classification is not established.

Study Details

Study typeCohort
EvidenceLevel 3
PublishedApr 2026
View Original Abstract ↓
Aims The oral glucose tolerance test (OGTT) is effective for detecting post-load dysglycemia, but it is burdensome and therefore not routinely used. Continuous glucose monitoring (CGM) offers a convenient way to capture real-world glucose patterns, yet it remains unclear whether CGM-derived metrics reflect OGTT-defined dysglycemia. We therefore aimed to evaluate CGM-derived and clinical metrics for predicting OGTT 2-hour glucose, classifying OGTT-defined dysglycemia, and assessing day-to-day repeatability. Methods We analyzed a cohort with paired free-living CGM and OGTT. Multiple CGM-derived metrics and clinical measures were compared for prediction of OGTT 2-hour glucose, classification of OGTT-defined dysglycemia, and day-to-day stability. Predictive performance was assessed primarily by leave-one-out (LOO) R^2, and day-to-day repeatability by intraclass correlation coefficients (ICC). Results The glycemic persistence index (GPI), a metric integrating the magnitude and duration of glycemic elevation, was the strongest single predictor of OGTT 2-hour glucose (LOO R^2 = 0.439). GPI also showed strong day-to-day repeatability (ICC = 0.665) and ranked first on a combined prediction-stability score. For classification of OGTT-defined dysglycemia, HbA1c had a slightly higher AUC than GPI, but GPI plus HbA1c performed best overall, indicating complementary information. Conclusions GPI was a strong predictor of OGTT 2-hour glucose and showed a favorable balance between predictive performance and day-to-day stability, supporting its potential utility as a CGM-derived marker of dysglycemia.
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