Evidence map›Paper›PMID 41260209›Full record

ArticleAnnals of pediatric endocrinology & metabolism2026

Development of a glycated hemoglobin prediction model using continuous glucose monitoring metrics in pediatric type 1 diabetes mellitus: insights into average glucose and recent glycemic trends.

Hakyung Lee, Mi Yang, Hwa Young Kim, Jaehyun Kim

Abstract read
In one paragraph

Article in Annals of pediatric endocrinology & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hakyung LeeDepartment of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Korea.
Mi YangDepartment of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Korea.
Hwa Young KimDepartment of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Korea.
Jaehyun KimDepartment of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Korea. jaehyun.kim@snu.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeGiven the limitations of glycated hemoglobin (HbA1c), continuous glucose monitoring (CGM) metrics have been proposed as complementary indicators of glycemic control. This study evaluated the association between CGM metrics and HbA1c and developed HbA1c prediction models in Korean pediatric patients with type 1 diabetes mellitus (T1DM).

methodsWe retrospectively analyzed CGM data from 85 patients aged 2-18 years using real-time CGM systems (G6 or G7). CGM records over 12 weeks were segmented into 5 intervals (0-2, 0-4, 4-8, 8-12, and 0-12 weeks) prior to HbA1c measurement. Metrics included time-in-range (TIR), time-above-range (TAR), time-below-range, time-in-tight-range, coefficient of variation, and average glucose. HbA1c prediction models were constructed using ridge regression and validated in a separate test dataset.

resultsTIR consistently showed the strongest negative association with HbA1c, while TAR and average glucose showed the strongest positive associations. Among all intervals, 0- to 4-week CGM data demonstrated the strongest relationship with HbA1c (all P<0.05). Average glucose achieved the best explanatory power among all metrics (R²=0.83, Akaike Information Criterion=84.34), and prediction models incorporating average glucose and TAR yielded the lowest mean squared error (0.15) and highest R² (0.83), with robust results in the test dataset.

conclusionShort-term CGM metrics, particularly average glucose during the 0-4 weeks preceding HbA1c testing, are strong predictors of HbA1c. These findings support the clinical utility of recent CGM data in optimizing individualized glycemic management in pediatric patients with T1DM.

Indexed as

Continuous glucose monitoringGlycated hemoglobinPediatricsType 1 diabetes mellitus

Identifiers

PMID41260209
PMCPMC13342894

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.