Continuous glucose monitoring as a growth-preserving strategy: Glycemic stability and GH–IGF-1 axis recovery in pediatric diabetes

 Corresponding author: Ashraf T. Soliman Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. Continuous glucose monitoring as a growth-preserving strategy: Glycemic stability and GH–IGF-1 axis recovery in pediatric diabetes Ashraf T. Soliman 1, *, Shayma Ahmed 1, Fawzia Alyafei 1, Nada Alaaraj 1, Noor Hamed 1, Ahmed Elawwa 2, Shaymaa Elsayed 2 and Dina Fawzy 2 1 Department of Pediatrics, Division of Endocrinology, Hamad Medical Center, Doha, Qatar. 2 Department of Pediatrics, University of Alexandria Children’s Hospital, Alexandria, Egypt. GSC Advanced Research and Reviews, 2025, 25(02), 103-118 Publication history: Received on 27 September 2025; revised on 08 November 2025; accepted on 11 November 2025 Article DOI: https://doi.org/10.30574/gscarr.2025.25.2.0340 Abstract Background: In pediatric type 1 diabetes (T1D), chronic dysglycemia disrupts hepatic GH receptor signaling and reduces IGF-1, impairing growth velocity and height SDS. Continuous glucose monitoring (CGM) and advanced hybrid closed-loop (AHCL) systems improve time-in-range (TIR) and reduce glycemic variability (GV), changes that may restore GH–IGF-1 physiology and preserve linear growth. Objectives: To synthesize clinical and mechanistic evidence on the impact of CGM/AHCL on auxologic outcomes and the GH–IGF-1 axis in youth with diabetes, and to identify scenarios where early CGM adoption offers maximal growth preservation. Methods: We reviewed randomized and observational pediatric studies reporting growth velocity, height SDS, IGF-1, or related endocrine measures alongside CGM metrics (HbA1c, TIR, GV). Risk of bias was assessed using RoB-2 (trials) and ROBINS-I (observational). Certainty of evidence was appraised with GRADE. Given heterogeneity of outcomes and follow-up, synthesis was narrative. Results: Thirty-five studies met inclusion criteria: four pediatric AHCL randomized trials and 31 observational studies. Trials consistently demonstrated improved glycemia (HbA1c ↓ ~0.4–1.0%; TIR ↑ ~10–20%; GV ↓) with objective sensorbased endpoints. Although growth was not a prespecified endpoint in the trials, multiple cohorts linked higher TIR and lower GV with higher IGF-1 and more favorable growth velocity or stabilized height SDS, especially across puberty. Mechanistic data show rapid IGF-1 increases following metabolic stabilization, supporting reversal of functional GH resistance. Cross-sectional and longitudinal cohorts in the modern CGM era generally report near-normal mean height SDS, with subtle suppression concentrated among children with higher GV; this contrasts with the pre-CGM era, where conventional therapy was associated with delayed puberty and lower final height relative to target height. Nocturnal hypoglycemia fell and DKA did not increase in AHCL trials. By GRADE, certainty is high for glycemic outcomes, moderate for IGF-1 recovery, and low for definitive growth effects due to indirectness and confounding in observational designs. Conclusions: CGM/AHCL reliably improves pediatric glycemia and is associated with IGF-1 recovery and stabilization of auxologic trajectories, particularly during puberty. While definitive growth effects require trials with prespecified auxologic endpoints, current evidence supports integrating structured growth surveillance with CGM metrics and adopting CGM early to optimize endocrine and growth outcomes in youth with diabetes. Keywords: Pediatric Type 1 Diabetes; Continuous Glucose Monitoring; Growth Velocity; IGF-1 Axis; Glycemic Variability GSC Advanced Research and Reviews, 2025, 25(02), 103-118 104 1. Introduction Linear growth in children with diabetes reflects a delicate interplay between insulin sufficiency, metabolic stability, and growth hormone (GH)–insulin-like growth factor-1 (IGF-1) axis function. Chronic hyperglycemia and insulinopenia impair hepatic GH receptor signaling and reduce IGF-1 production, resulting in suppressed growth velocity and height SDS decline (1). Although the introduction of intensified insulin therapy has reduced severe growth disturbance, persistent dysglycemia remains a challenge in many children (2). Continuous glucose monitoring (CGM) systems provide real-time glycemic patterns, enabling improved insulin titration and steady glucose exposure. CGM use is consistently associated with lower HbA1c, higher time-in-range (TIR), and reduced glycemic variability metabolic parameters known to normalize GH pulsatility and IGF-1 synthesis (3). Pediatric studies demonstrate height stabilization and IGF-1 gain in children using CGM compared with conventional monitoring (4). Growth failure is more pronounced in patients with long diabetes duration, pubertal insulin resistance, and suboptimal glycemic control. In such groups, CGM-mediated improvements in metabolic homeostasis may restore hepatic GH sensitivity and support catch-up growth (5). Notably, growth deficits in poorly controlled children can appear before overt microvascular complications, underscoring the endocrine vulnerability of the GH–IGF-1 axis (6). Emerging evidence links glycemic variability with counter-regulatory hormone surges (cortisol, catecholamines, glucagon) that antagonize GH action and inhibit IGF-1 bioactivity (7). By minimizing hypoglycemia and post-prandial spikes, CGM reduces these catabolic influences and supports anabolic signaling (8). CGM may therefore be viewed not only as a glucose-safety tool but also as an endocrine-restorative device. CGM use in prepubertal children is especially impactful, as this period depends heavily on normal IGF-1 physiology. Improved IGF-1 correlates with growth velocity gains and normalized bone maturation indices in children using CGM and hybrid closed-loop therapy (9). Benefits extend to type 2 diabetes youth where hepatic dysfunction, hyperinsulinemia, and inflammation impair IGF-1 secretion (10). The increasing adoption of real-time CGM and intermittently scanned CGM has shifted pediatric diabetes management from episodic monitoring to metabolic stabilization. Mechanistic data now supports its integration into growth monitoring pathways (11). However, current literature lacks a focused endocrine synthesis examining CGM as a growthpreserving therapy. This review synthesizes clinical and mechanistic evidence on how CGM use improves growth metrics, IGF-1 levels, and GH sensitivity in children with diabetes, highlighting implications for endocrine surveillance and therapy personalization (12). Objectives • To evaluate the impact of continuous glucose monitoring on growth parameters in children with diabetes. • To explore physiologic mechanisms linking glycemic stability with GH–IGF-1 axis recovery. • To identify clinical scenarios where CGM offers the greatest growth-preservation benefit. 2. Methods A structured literature search was conducted in PubMed, Scopus, and Google Scholar from database inception through January 2025 to identify original studies evaluating continuous glucose monitoring (CGM) and advanced hybrid closedloop (AHCL) insulin systems in relation to growth, insulin-like growth factor-1 (IGF-1), and glycemic profiles in children with type 1 diabetes mellitus. Search terms included combinations of continuous glucose monitoring, CGM, real-time CGM, hybrid closed-loop, time-in-range, glycemic variability, type 1 diabetes, pediatric, child, linear growth, height velocity, IGF-1, and growth hormone axis. Reference lists of selected articles and relevant reviews were also screened. The review followed PRISMA 2020 recommendations. Studies were eligible if they included participants younger than 18 years with type 1 diabetes, used CGM/isCGM/AHCL technologies, and reported growth-related outcomes (height SDS, growth velocity, or IGF-1) alongside glycemic indices such as HbA1c, time-in-range (TIR), or glycemic variability. Eligible study designs included randomized controlled trials, prospective cohort studies, retrospective cohort studies, and cross-sectional studies published in peer-reviewed GSC Advanced Research and Reviews, 2025, 25(02), 103-118 105 journals. Exclusion criteria included studies enrolling adults only, studies on type 2 or gestational diabetes, case reports, commentaries, and studies lacking growthor IGF-related outcomes. After removal of duplicate references, titles and abstracts were screened. Full texts were assessed for eligibility when abstracts indicated relevant growth or IGF-1 outcomes. Data extracted included sample size, age, duration of diabetes, CGM modality and wear characteristics, insulin regimen, height SDS, growth velocity, IGF-1 levels, HbA1c, TIR, and glycemic variability. Ultimately, 35 studies met inclusion criteria: 4 randomized controlled trials evaluating AHCL systems and 31 observational studies examining CGM use and growth-endocrine outcomes. Risk of bias was evaluated independently by two reviewers. Randomized trials were assessed using the Cochrane Risk of Bias-2 (RoB-2) tool, addressing randomization quality, deviations from intended interventions, completeness of outcome data, reliability of outcome measurement, and selective reporting. Observational studies were evaluated using the ROBINS-I tool, considering confounding factors such as pubertal stage, insulin dosing intensity, and diabetes duration, as well as participant selection, intervention classification, deviations from standard care, missing data, outcome measurement methods, and reporting integrity. The certainty of evidence across outcomes was appraised using the GRADE approach. Domains assessed included study limitations, consistency, directness, precision, and reporting bias. Due to heterogeneity in study designs, outcome measures, and follow-up duration, results were synthesized narratively rather than through meta-analysis. Figure 1 PRISMA flow diagram for study selection A systematic search of PubMed, Scopus, and Google Scholar identified 412 records. The final synthesis included 35 studies (4 randomized controlled trials and 31 observational studies). GSC Advanced Research and Reviews, 2025, 25(02), 103-118 106 3. Results Table 1 Baseline Endocrine Growth Abnormalities in Pediatric Diabetes (Pre-CGM) Endocrine Domain Pediatric T1D Baseline Findings Pediatric T2D Baseline Findings Clinical Notes Linear growth / Height SDS Slightly reduced height SDS over time, especially with chronic hyperglycemia and early-onset disease (13) Height SDS often normal; may decrease with severe IR/inflammation (14) Progressive SDS fall can precede complications Growth velocity Reduced growth velocity in poor metabolic control (15) May be preserved early; declines with metabolic deterioration (16) Serial velocity helps detect occult GH axis impairment Serum IGF-1 Low IGF-1 from hepatic GH resistance due to low portal insulin (17) IGF-1 dysregulated due to hepatic steatosis/IR (18) Low IGF-1 is hallmark of disrupted GH axis in T1D IGFBP profile ↑ IGFBP-1 (insulin deficiency & counter-regulation) and ↓/lownormal IGFBP-3 (19) IGFBP-1 is often normal/low with hyperinsulinemia; IGFBP-3 variable (20) IGFBP ratios reflect insulin action vs IR burden GH secretion / sensitivity ↑ GH secretion + ↓ GH signaling (JAK2– STAT5 impairment) (17) GH pathway attenuated by IR & inflammatory cytokines (21) “GH hypersecretion with GH resistance” phenotype Bone age / skeletal maturation Mildly delayed in poorly controlled cases (15) Often normal; IR may accelerate/dysregulate maturation (16) Bone age part of endocrine surveillance Pubertal development Slight pubertal delay, esp. in girls with early-onset T1D (22) Puberty normal or earlier with obesity (16) Puberty modifies GH– IGF-1 dynamics Metabolic stress hormones Nocturnal hypoglycemia → counterregulatory surges (cortisol, glucagon, catecholamines) reduce IGF-1 bioavailability (19) IR-related hyperinsulinemia, adipokine imbalance, NAFLD → growth axis strain (18) Stability prevents catabolic axis disruption Abbreviations: IR, insulin resistance; NAFLD, nonalcoholic fatty liver disease; SDS, standard deviation score. Before CGM-based metabolic stabilization, children with T1D commonly demonstrated low IGF-1, elevated IGFBP-1, GH hypersecretion with hepatic GH resistance, and subtle growth velocity decline, proportional to dysglycemia severity and duration. Youth-onset T2D shows IR-mediated IGF-1 pathway dysregulation, NAFLD-linked GH insensitivity, and potential pubertal acceleration patterns. GSC Advanced Research and Reviews, 2025, 25(02), 103-118 107 Table 2 Growth Outcomes with CGM Use vs. Non-CGM Monitoring in Pediatric Diabetes Study (year) Design and Population Comparator Followup Glycemic outcomes (CGM arm) Growth endpoints reported Direction of effect (CGM vs. control) Ref Franceschi et al., 2022 Prospective cohort, newonset T1D (isCGM initiated within 1 month), n=97 Standard care prior to isCGM (historical/withinpatient baseline) 6–12 mo ↓HbA1c; ↑TIR; improved QoL NR (no height/IGF-1 reported) CGM improves metabolic stability; growth effect not directly assessed (23) Areekal et al., 2023 Longitudinal analysis of height growth patterns in T1D youth Contextual (not a CGM trial) up to 24 mo N/A ↓Height velocity and delayed pubertal spurt associated with dysglycemia Supports rationale that stabilizing glycemia (e.g., via CGM) may protect growth (24) Blasetti et al., 2023 Observational; link between glycemic variability and linear growth in T1D Variability strata (no dedicated CGM vs non-CGM arms) 12 mo Higher variability → worse outcomes Height velocity reported: higher GV associated with slower growth Implies variability reduction (CGM) could favor growth (25) Chisalita et al., 2018 Prospective; adolescents with new T1D Prevs post-metabolic stabilization (insulin) weeks– months Rapid metabolic correction IGF-1 increased with improved control Mechanistic support: as control improves (facilitated by CGM), IGF-1 rises (26) Demir et al., 2010 Cohort; growth in children with T1D (prebroad CGM uptake) N/A 5 yrs N/A Height SDS stable overall with modern care Baseline benchmark; later CGM eras seek to maintain this stability (27) Canha et al., 2023 Cross-sectional clinic cohort (T1D 5–18 y) N/A single visit HbA1c, bmi, Height/anthropometry documented; no IGF-1 Reinforces need to add growth endpoints to CGM studies (28) CGM: Continuous glucose monitoring (rtCGM/isCGM); SMBG: Self-monitoring blood glucose; T1D: Type 1 diabetes; HbA1c: Glycated hemoglobin; TIR: Time-in-range; GV: Glycemic variability; NR: Not reported. GSC Advanced Research and Reviews, 2025, 25(02), 103-118 108 Direct head-to-head pediatric trials reporting formal growth endpoints (height SDS/velocity or IGF-1) for CGM vs. nonCGM are scarce. However, cohort and physiologic evidence show that **reducing HbA1c and glycemic variability typical effects of CGM aligns with higher IGF-1 and better growth trajectories. Table 2 combines (i) CGM-specific pediatric outcomes (metabolic) and (ii) pediatric growth literature linking metabolic stability to growth, to contextualize the expected direction of effect. Table 3 Glycemic indices associated with growth-axis recovery in pediatric diabetes (CGM era) CGM metric / index Typical CGM-associated change Expected effect on GH–IGF-1 axis and growth Key pediatric evidence HbA1c (%) ↓ with CGM/AHCL adoption Lower chronic hyperglycemia reduces hepatic GH resistance → ↑ IGF-1, ↑ growth velocity, stabilization of height SDS (35) Time in Range (TIR 70– 180 mg/dL) ↑ by 10–20% in many pediatric cohorts using CGM/AHCL More time at euglycemia improves GH pulse effectiveness and hepatic IGF-1 generation → supports linear growth (35), (37) Time in Tight Range (TITR 80–140 mg/dL) ↑ with advanced hybrid closed loop Tighter normoglycemia reduces counterregulatory surges and glucotoxicity → facilitates IGF-1 bioavailability (39) Glycemic variability (GV: CV%, SD, MAGE) ↓ variability (lower CV%, SD, MAGE) Fewer excursions → less cortisol/catecholamine activation antagonizing GH; higher height-SDS tertiles seen with lower GV (33), (34), (36) Nocturnal hypoglycemia (% time <70 mg/dL overnight) ↓ with CGM alerts & AHCL safeguards Fewer nocturnal lows → less counterregulatory hormone disruption of GH secretion overnight → protects growth (38) Post-prandial excursions (PPG spikes) ↓ with algorithmic microcorrections and better pre-bolus timing informed by CGM Reduced post-prandial glucotoxicity and inflammatory signaling → improves hepatic GH signaling/IGF-1 (36), (37) Wear time / sensor adherence ↑ (targets ≥85–90%) More complete data → steadier insulin titration → sustained euglycemia → better IGF-1 and growth trajectory (35), (36) Pubertal stage–specific GV patterns (pre/early vs mid/late puberty) CGM reveals higher GV around mid-puberty; AHCL partly mitigates Smoother glucose in pubertal insulinresistance window → supports expected pubertal growth spurt physiology (36), (34) AHCL: Advanced hybrid closed loop; CV%: Coefficient of variation for glucose; GV: Glycemic variability; IGF-1: Insulin-like growth factor 1; MAGE: Mean amplitude of glycemic excursions; PPG: Post-prandial glucose; TIR: Time in range; TITR: Time in tight range. Pediatric data link lower GV and higher TIR/TITR to a metabolic milieu that favors GH effectiveness and IGF-1 production, aligning with observed associations between lower variability and better height-SDS tertiles. CGM (and AHCL) primarily acts by reducing excursions and nocturnal hypoglycemia, thereby protecting the growth axis during critical developmental periods. (33–40) GSC Advanced Research and Reviews, 2025, 25(02), 103-118 109 Table 4 Glycemic Indices Associated with Growth Recovery in Children with Diabetes (CGM/AHCL Era) Glycemic index (definition) Typical CGM/AHCL direction Pragmatic pediatric target* Mechanistic link to GH–IGF-1 and growth Key pediatric evidence HbA1c (%) ↓ Individualized; often ≲7.0–7.5% if safe Less chronic hyperglycemia → less hepatic GH resistance → ↑ IGF-1, ↑ growth velocity (35) Time-in-Range (TIR 70–180 mg/dL) ↑ ≥70% if safely achievable More euglycemia → more effective GH pulses & hepatic IGF-1 generation → stabilizes height SDS (35), (37) Time-in-Tight-Range (TITR 80–140 mg/dL) ↑ Emerging goal (contextdependent) Tighter normoglycemia → fewer counter-regulatory surges → better IGF-1 bioavailability (39) Glycemic variability (GV; CV%, SD, MAGE) ↓ (CV%, SD, MAGE) CV% <36% (context-dependent) Fewer excursions → reduced cortisol/catecholamines antagonizing GH → higher heightSDS tertiles (33), (34), (36) Time <70 mg/dL (overall/overnight) ↓ Minimal time <70 (esp. nocturnal) Fewer nocturnal lows → less counter-regulatory disruption of GH secretion → protects growth (38) Time >180 mg/dL (hyperglycemia burden) ↓ Lower proportion >180 Less glucotoxicity/inflammation → improved hepatic GH signaling → ↑ IGF-1 (35), (37) Post-prandial excursions (PPG spikes) ↓ peak & duration Aim for modest post-meal rise Lower oxidative/inflammatory signaling → enhanced GH receptor/JAK2-STAT5 action (36), (37), (40) Sensor wear/adherence (% of time on CGM) ↑ ≥85–90% Stable data stream enables consistent insulin titration → sustained euglycemia → supports linear growth (35), (36) Puberty-phase GV patterning Blunted peaks on AHCL N/A (phase-specific) Mitigates puberty-related IR spikes → preserves expected pubertal growth spurt (36), (34) AHCL: Advanced hybrid closed loop; CV%: Coefficient of variation; GV, glycemic variability; IGF-1: Insulin-like growth factor-1; JAK2: STAT5, Janus kinase 2/signal transducer and activator of transcription 5; SDS: Standard deviation score; TIR, time in range; TITR, time in tight range. GSC Advanced Research and Reviews, 2025, 25(02), 103-118 110 Pediatric datasets show that higher TIR/TITR and lower GV align with a metabolic milieu favoring GH effectiveness and IGF-1 production, matching observed links between lower variability and better height-SDS tertiles and the protective role of reducing nocturnal hypoglycemia for overnight GH secretion. (33–40) Table 5 Comparison: Growth in Pediatric T1D pre-CGM (2006) vs CGM/AHCL Era (8, 25,28, 41-44) Domain Pre-CGM era — Elamin et al., 2006 (Sudan; conventional therapy) CGM/AHCL era — key pediatric evidence Final height vs target height Final height below genetic target height; pubertal growth spurt reduced. Height SDS generally stable in modern cohorts; auxologic decline is concentrated in children with higher GV/poorer control (association). Height at diagnosis / baseline Boys 0.04 SDS; Girls −0.15 SDS at diagnosis. Baseline varies; many cohorts start near population means. Growth dynamics across puberty Delayed puberty (girls’ menarche ≈15.1 y; boys’ full maturation ≈17.2 y). Growth faltering correlated with higher HbA1c and longer prepubertal diabetes duration. Lower glycemic variability (GV) associates with better Δ height-SDS over 2 years; higher GV links to SDS decline (Blasetti 2023). Trials with CGM/AHCL show ↑TIR, ↓GV—mechanistic support for preserving pubertal growth. Glycemic control markers Poor control common; growth/puberty inversely related to HbA1c. CGM/AHCL RCTs: TIR +9–12 percentage points, HbA1c ↓; observational pediatric data: IGF-1 rises with improved control; Δ height-SDS tracks inversely with GV. Complication modifiers DKA at diagnosis predicted shorter stature throughout follow-up. CGM/AHCL reduces nocturnal hypoglycemia and excursions; earlier use and high wear favor more stable growth milieu. Weight trajectory Marked pubertal weight gain (esp. girls) correlated with insulin dose and HbA1c. Mixed by cohort; technology enables smoother dosing and may mitigate wide swings, but requires diet/activity counseling. The contrast between historical cohorts managed without continuous glucose monitoring and modern pediatric diabetes populations underscores a meaningful shift in growth preservation linked to metabolic stability. In the preCGM era, children frequently exhibited delayed puberty, reduced pubertal growth velocity, and lower final height relative to genetic potential, with poor glycemic control and prolonged pre-pubertal hyperglycemia emerging as dominant predictors of impairment. In contemporary practice, the introduction of CGM and hybrid closed-loop systems has markedly improved time-in-range and reduced glycemic variability—two factors central to restoring physiologic GH–IGF-1 axis activity. Although randomized trials have not yet included growth as a prespecified endpoint, real-world data consistently show that lower variability and higher CGM wear are associated with better IGF-1 levels and stabilization of height SDS, particularly through puberty when metabolic demands are highest. Collectively, these findings suggest that modern diabetes technology not only improves glucose safety and quality of life, but may also mitigate the growth and pubertal delays historically observed in youth with type 1 diabetes, supporting CGM as a cornerstone of endocrine protection across the pediatric years. GSC Advanced Research and Reviews, 2025, 25(02), 103-118 111 Figure 2 Continuous Glucose Monitoring–Based Growth Surveillance Algorithm in Pediatric Diabetes Children starting CGM require baseline auxologic and endocrine evaluation, followed by early metabolic review at 6–12 weeks, growth and IGF-1 reassessment at 6 months, and an annual endocrine audit. 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