Evidence map›Paper›PMID 29848594›Full record

ArticleJournal of the Royal Society, Interface2018

Labile haemoglobin as a glycaemic biomarker for patient-specific monitoring of diabetes: mathematical modelling approach.

O León-Triana, G F Calvo, J Belmonte-Beitia, M Rosa Durán, J Escribano-Serrano, A Michan-Doña, V M Pérez-García

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2018. 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. Article
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

7 authors.

O León-TrianaDepartment of Mathematics, Mathematical Oncology Laboratory (MôLAB), University of Castilla-La Mancha, 13071 Ciudad Real, Spain odelaisyleon@gmail.com.ORCID 0000-0002-7509-7754
G F CalvoDepartment of Mathematics, Mathematical Oncology Laboratory (MôLAB), University of Castilla-La Mancha, 13071 Ciudad Real, Spain gabriel.fernandez@uclm.es.
J Belmonte-BeitiaDepartment of Mathematics, Mathematical Oncology Laboratory (MôLAB), University of Castilla-La Mancha, 13071 Ciudad Real, Spain.
M Rosa DuránDepartment of Mathematics, University of Cádiz, 11510 Puerto Real, Cádiz, Spain.
J Escribano-SerranoUGC Primary Care San Roque, Campo de Gibraltar, Cádiz, Spain.
A Michan-DoñaUGC Internal Medicine, University Hospital of Jerez and Department of Medicine, University of Cádiz, Cádiz, Spain.
V M Pérez-GarcíaDepartment of Mathematics, Mathematical Oncology Laboratory (MôLAB), University of Castilla-La Mancha, 13071 Ciudad Real, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus constitutes a major health problem and its clinical presentation and progression may vary considerably. A number of standardized diagnostic and monitoring tests are currently used for diabetes. They are based on measuring either plasma glucose, glycated haemoglobin or both. Their main goal is to assess the average blood glucose concentration. There are several sources of interference that can lead to discordances between measured plasma glucose and glycated haemoglobin levels. These include haemoglobinopathies, conditions associated with increased red blood cell turnover or the administration of some therapies, to name a few. Therefore, there is a need to provide new diagnostic tools for diabetes that employ clinically accessible biomarkers which, at the same time, can offer additional information allowing us to detect possible conflicting cases and to yield more reliable evaluations of the average blood glucose level concentration. We put forward a biomathematical model to describe the kinetics of two patient-specific glycaemic biomarkers to track the emergence and evolution of diabetes: glycated haemoglobin and its labile fraction. Our method incorporates erythrocyte age distribution and utilizes a large cohort of clinical data from blood tests to support its usefulness for diabetes monitoring.

Indexed as

Models, BiologicalBiomarkersBlood GlucoseDiabetes Mellitus, Type 2ErythrocytesGlycated HemoglobinHumansKineticsMonitoring, PhysiologicBiomarkersBlood GlucoseGlycated Hemoglobindiabeteshaemoglobin glycationred blood cell kinetics

Identifiers

PMID29848594
PMCPMC6000176

What OpenQuestion holds

Textmetadata
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.