Evidence mapPaperPMID 39443334Full record

ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2024

Unveiling the Spectrum of Glucose Variability: A Novel Perspective on FreeStyle Libre Monitoring Data.

Adrian H Heald, Mike Stedman, John Warner-Levy, Lleyton Belston, Angela Paisley, Aleksandra Jotic, Nebojsa Lalic, Martin Gibson, Hellena H Habte-Asres, Martin Whyte and 1 more

Abstract read
In one paragraph

Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Association of HbADiabetologia · 2026
    Article
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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

11 authors.

Adrian H HealdThe School of Medicine and Manchester Academic Health Sciences Centre, Manchester University, Manchester, UK. adrian.heald@manchester.ac.uk.ORCID http://orcid.org/0000-0002-9537-4050
Mike StedmanRes Consortium, Andover, UK.
John Warner-LevyDepartment of Endocrinology and Diabetes, Salford Royal Hospital, Salford, UK.
Lleyton BelstonDepartment of Endocrinology and Diabetes, Salford Royal Hospital, Salford, UK.
Angela PaisleyDepartment of Endocrinology and Diabetes, Salford Royal Hospital, Salford, UK.
Aleksandra JoticClinic for Endocrinology, Diabetes and Metabolic Disease, University Clinical Centre of Serbia, Belgrade, Serbia.
Nebojsa LalicClinic for Endocrinology, Diabetes and Metabolic Disease, University Clinical Centre of Serbia, Belgrade, Serbia.
Martin GibsonThe School of Medicine and Manchester Academic Health Sciences Centre, Manchester University, Manchester, UK.
Hellena H Habte-AsresFlorence Nightingale Faculty of Nursing, Midwifery and Palliative Care, King's College London, London, UK.
Martin WhyteDepartment of Clinical and Experimental Medicine, University of Surrey, Guildford, UK.
Angus ForbesFlorence Nightingale Faculty of Nursing, Midwifery and Palliative Care, King's College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSince the introduction of insulin therapy, it has become apparent that type 1 diabetes (T1D) is accompanied by long-term microvascular and macrovascular complications. In the context of the many benefits of continuous glucose monitoring (CGM), there remain opportunities to study the large amount of data now available in order to maximise its potential in the endeavour to reduce the occurrence of diabetes tissue complications in the longer term.

methodsContinuous glucose monitoring values were downloaded for 89 type 1 diabetes mellitus (T1D) individuals for up to 18 months from 2021 to 2023. Data for patient demographics was also taken from the patient record which included Sex, Date of Birth, and Date of Diagnosis. The recorded laboratory glycated haemoglobin (HbA1c) test results were also recorded. The glucose management index (GMI) was calculated from average glucose readings for 18 months using the formula GMI (%) = (0.82 - (Average glucose/100)). This was then adjusted to give GMI (mmol/mol) = 10.929 * (GMI (%) - 2.15). Average Glucose Fluctuation (AGF) was calculated by adding up the total absolute change value between all recorded results over 18 months and dividing by the number of results minus one. The % Above Critical Threshold (ACT) was calculated by summing the total number of occurrences for each result value. A cumulative 95% limit was then applied to identify the glucose value that only 5% of results exceeded in the overall population. Using this value, we estimated the percentage of total tests that were above the Critical Threshold (ACT).

resultsThe mean age of the participants was 42.6 years, and the mean duration of T1D was 18.4 years. A total of 3.22 million readings were analysed, yielding an average blood glucose level of 10.3 mmol/l and a GMI of 57.2 mmol/mol. There was a strong correlation between GMI and measured HbA1c (r

conclusionsWe have shown here that the percentage glucose results above 18 mmol/l (top 5% of distribution) increased exponentially above 54 mmol/mol HbA1c. The %AVTD is introduced as a useful measure. Our data indicate that over the 24-h period, improvement in metabolic control could be focussed on the afternoon and evening, when there are higher-than-average levels of GMI, a higher-than-average degree of glucose change, and higher-than-average risks of being above the critical threshold. In conclusion, a measure of glycaemic variation based on the amplitude of glucose change to a population mean could be used to provide valuable clinical insights into glucose change over a 24-h period.

Indexed as

Continuous glucose monitoringGlucose variabilityGlycated haemoglobin (HbA1c)Type 1 diabetes (T1D)

Identifiers

PMID39443334
PMCPMC11561226

What Socratic holds

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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 Socratic graph.