Evidence map›Paper›PMID 30575414›Full record

ArticleDiabetes technology & therapeutics2019

The Relationship of Hemoglobin A1C to Time-in-Range in Patients with Diabetes.

Robert A Vigersky, Chantal McMahon

2 registry-linked trialsAbstract read
PubMed Publisher
In one paragraph

Article in Diabetes technology & therapeutics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 214 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
214citing papers in PubMed, 8 pooled it
27.6field-weighted citation impact, top 1% of its field
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.

NCT04790760 naunknown statusnot on this mapstarted 2021, after this paper: background citation

Glucose Differences Between the Left Arm and Right Arm in Diabetic Patients Using a Continuous Glucose Monitor

TypeinterventionalSponsorUniversity of the PacificRan2021 to 2022Enrolled10ConditionsDiabetesArmsSupplement Consumption, Continuous Glucose Monitors
NCT05849428 naunknown statusnot on this mapstarted 2023, after this paper: background citation

Blood Glucose Differences Between Left Arm and Right Arm in Patients With Type 1 or Type 2 Diabetes Using a Continuous Glucose Monitor

TypeinterventionalSponsorUniversity of the PacificRan2023 to 2024Enrolled10ConditionsType 1 Diabetes, Type 2 DiabetesArmsFreestyle Libre 3
3 · Its place in the literature

Who cites it

214 citing papers in PubMed, 8 syntheses or guidelines pooled it, 447 citations in OpenAlex.

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  6. American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2022
    Guideline
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154 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Robert A VigerskyMedical Affairs and Data Science and Informatics, Medtronic Diabetes, Northridge, California.
Chantal McMahonMedical Affairs and Data Science and Informatics, Medtronic Diabetes, Northridge, California.
Medtronic (Ireland) · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere has been recent recognition of the limitations of hemoglobin A1C (HbA1C) in describing both short- and long-term glycemic control. Continuous glucose monitoring (CGM) provides robust data about short-term glycemic control and provides metrics such as percent time-in-range (%TIR) that are now routinely reported to describe the change in glycemic control after an intervention in a clinical study or a change in therapy in a patient's care. Recent studies have shown that %TIR may have similar associations with diabetes microvascular complications as does HbA1C. The relationship of %TIR to the long-standing metric of overall glycemic control has not been clearly defined to date.

methodsArticles that report paired HbA1C and %TIR metrics (n = 1137) or HbA1C and frequent self-monitoring of blood glucose (SMBG) (n = 1440) across a wide range of HbA1Cs, technologies, and subject demographics were reviewed to determine the correlation of these metrics.

resultsSelected paired HbA1C and %TIR data from 18 articles were evaluated by linear regression analysis and Pearson's correlation coefficient. There was an excellent correlation between the two (R = -0.84; R

conclusionsThere is a good correlation between HbA1C and %TIR that may permit the transition to %TIR as the preferred metric for determining the outcome of clinical studies, predicting of the risk of diabetes complications, and assessing of an individual patient's glycemic control.

Indexed as

AdolescentAdultAgedBlood GlucoseBlood Glucose Self-MonitoringChildDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2FemaleGlycated HemoglobinHumansHypoglycemic AgentsInsulinInsulin Infusion SystemsMaleMiddle AgedBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanHypoglycemic AgentsInsulinContinuous glucose monitoring.HbA1CTime-in-range

Identifiers

PMID30575414
OpenAlexW2906596531

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.