Reframing Pediatric Dysglycemia Detection: Continuous Glucose Monitoring as a Tool for Early Metabolic Risk Identification

Background: Continuous glucose monitoring (CGM) provides dynamic, real-life information on glycemic patterns that cannot be captured by fasting glucose, HbA1c, or oral glucose tolerance tests (OGTT). As CGM adoption expands in pediatric endocrinology, there is increasing need to clarify interpretation standards, examine relationships with traditional metabolic tests, and determine its diagnostic value in high-risk pediatric populations.

Objectives: To (1) summarize core CGM metrics and interpretation principles; (2) evaluate associations between CGM parameters and standard glycemic tests; and (3) assess the diagnostic performance of CGM for detecting early dysglycemia in high-risk children and adolescents.

Methods: A narrative review of studies published between 2000–2025 was performed using PubMed, Scopus, Web of Science, Google Scholar, and Cochrane Library. Eligible studies reported CGM metrics, CGM–biochemical correlations, or CGM-based dysglycemia detection in pediatric or mixed-age cohorts with extractable pediatric data. Data were synthesized qualitatively; no meta-analysis was performed.

Results: Consensus-endorsed CGM metrics—including time-in-range (TIR), time-above-range (TAR), time-below-range (TBR), mean glucose, glycemic variability (GV), and risk indices (LBGI/HBGI)—offer a comprehensive evaluation of glycemic control. TIR and mean glucose demonstrate strong correlations with HbA1c across populations, although substantial inter-individual dispersion at a given HbA1c underscores the limitations of HbA1c as a standalone marker. CGM parameters also align with OGTT-derived glucose tolerance categories and physiological indices such as HOMA-IR, HOMA-β, and CGM-derived disposition index, reflecting their capacity to capture early metabolic dysregulation.

Across high-risk pediatric groups, CGM identifies dysglycemia earlier and more sensitively than traditional tests. In children with obesity, CGM reveals postprandial hyperglycemia, reduced TIR, and increased GV even when fasting glucose and HbA1c are normal, indicating early insulin resistance. In cystic fibrosis, short hyperglycemic excursions detected by CGM precede abnormal OGTT results and correlate with nutritional and pulmonary decline. In β-thalassemia major, CGM uncovers nocturnal hyperglycemia, peri-transfusion spikes, and fluctuating glycemic instability missed by OGTT and poorly reflected by HbA1c due to altered erythrocyte survival. Autoantibody-positive siblings of children with type 1 diabetes demonstrate declining TIR and rising TAR months to years before OGTT-defined dysglycemia, supporting CGM for disease staging and risk prediction. In syndromic obesity (e.g., Prader–Willi), CGM detects nocturnal eating–related excursions that remain invisible to fasting tests.

Conclusion: CGM provides physiologically rich, clinically actionable insights that complement and frequently surpass standard tests for identifying early dysglycemia in high-risk pediatric populations. Its integration alongside biochemical testing can improve early diagnosis, risk stratification, and individualized management. Future work should refine pediatric-specific thresholds and evaluate CGM-driven interventions on long-term outcomes.