Short-Lived Hyperglycaemia Contributes to Continuous Glucose Monitoring Metrics Used for Therapeutic Decision-Making
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Background
Continuous glucose monitoring (CGM) metrics, including time in range (TIR) and median glucose, guide therapeutic decisions in type 1 diabetes (T1D) but do not distinguish sustained from transient hyperglycaemia. We investigated the prevalence of short-lived hyperglycaemia (SLH), i.e. brief isolated hyperglycaemic episodes, and its contribution to CGM metrics in T1D children and adolescents.
Methods
In this monocentric retrospective cohort study, T1D patients aged 6 months–20 years, enrolled in 2025–2026, with 5-minute CGM data, ≥70% coverage and median glucose 6·1–9·4 mmol/L within a 45-day window were included. SLH were hyperglycaemic episodes lasting 10–60 minutes surrounded by normoglycaemia, classified by onset as daytime or night-time. Their contribution to CGM metrics was estimated by replacing SLH with plausible trajectories; sensitivity analyses varied construction parameters.
Findings
Among 135 participants, 2,874 of 15,556 hyperglycaemic episodes (18·5%) met daytime SLH criteria (median 19·0 per participant). Removing SLH increased daytime TIR by 1·74 percentage points (95% CI 1·59–1·89) and reduced daytime median glucose by 0·18 mmol/L (95% CI 0·17–0·20). Whole-day effects were modest, but local impact was substantially greater: at maximal divergence, glucose profiles differed by 1·30 mmol/L (95% CI 1·21–1·38), around meals. Patients with near-identical conventional metrics could show markedly different SLH frequency.
Interpretation
SLH are common in this paediatric T1D cohort and alter reported CGM metrics: modest whole-day effects contrast with greater impact at specific times. Distinguishing transient from sustained hyperglycaemia provides clinically relevant information beyond aggregate metrics and may guide behavioural or educational interventions rather than insulin intensification.
Funding
Francqui Foundation and Helmsley Charitable Trust.
Research in context
Evidence before this study
We searched PubMed, Embase, and Web of Science from database inception to 31 March 2026, without language restriction, using the terms “short-lived hyperglycaemia” OR “transient hyperglycaemia” OR “brief hyperglycaemia” OR “isolated hyperglycaemia” OR “postprandial excursion” AND (“time in range” OR TIR OR “median glucose” OR “ambulatory glucose profile” OR CGM metric) AND (“type 1 diabetes” OR T1D) AND (paediatric OR children OR adolescents). We also reviewed reference lists of relevant reviews and ISPAD/ADA consensus statements on CGM interpretation. CGM metrics guide therapeutic decisions but do not distinguish sustained hyperglycaemia from brief, isolated excursions, and patients with similar metrics show heterogeneous glucose patterns. No study had quantified the contribution of such episodes to routine CGM metrics, and episode definitions were heterogeneous, without isolation criteria or a reproducible detection method.
Added value of this study
This is the first study to define short-lived hyperglycaemia (SLH) with explicit duration, isolation, and data-completeness criteria, and to quantify its contribution to CGM metrics using counterfactual glucose trajectories with these episodes removed. In this paediatric cohort, SLH accounted for about one-fifth of hyperglycaemic episodes; removing them increased daytime time in range by 1·74 percentage points, and median daily glucose profiles differed by up to 1·30 mmol/L around meals. SLH were more frequent in younger children, in those with shorter diabetes duration, and in those with better overall glycaemic control (lower GTAA1c, a score combining HbA1c and time in range). Patients with nearly identical conventional metrics differed markedly in SLH frequency, a temporal pattern invisible to summary metrics alone.
Implications of all the available evidence
Because recurrent SLH episodes can inflate the CGM metrics used for insulin titration, clinicians should check whether hyperglycaemia is brief and isolated before intensifying insulin, as behavioural or educational measures may then be more appropriate. Future studies should integrate automated SLH detection into CGM reports and test prospectively, with meal, insulin, and activity data, whether targeting SLH improves individualised management and reduces overtreatment.
