Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/124199
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dc.contributor.authorAzcoitia, Pabloen_US
dc.contributor.authorRodríguez-Castellano, Raquelen_US
dc.contributor.authorSaavedra Santana, Pedroen_US
dc.contributor.authorAlberiche Ruano,Maria Del Pinoen_US
dc.contributor.authorMarrero, Duniaen_US
dc.contributor.authorWägner, Anna Maria Claudiaen_US
dc.contributor.authorOjeda, Antonioen_US
dc.contributor.authorBoronat Cortés, Mauroen_US
dc.date.accessioned2023-08-29T15:17:32Z-
dc.date.available2023-08-29T15:17:32Z-
dc.date.issued2023en_US
dc.identifier.issn1932-2968en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/124199-
dc.description.abstractBackground: Glycated hemoglobin (HbA1c) is the gold standard to assess glycemic control in patients with diabetes. Glucose management indicator (GMI), a metric generated by continuous glucose monitoring (CGM), has been proposed as an alternative to HbA1c, but the two values may differ, complicating clinical decision-making. This study aimed to identify the factors that may explain the discrepancy between them. Methods: Subjects were patients with type 1 diabetes, with one or more HbA1c measurements after starting the use of the Freestyle Libre 2 intermittent CGM, who shared their data with the center on the Libreview platform. The 14-day glucometric reports were retrieved, with the end date coinciding with the date of each HbA1c measurement, and those with sensor use ≥70% were selected. Clinical data prior to the start of CGM use, glucometric data from each report, and other simultaneous laboratory measurements with HbA1c were collected. Results: A total of 646 HbA1c values and their corresponding glucometric reports were obtained from 339 patients. The absolute difference between HbA1c and GMI was <0.3% in only 38.7% of cases. Univariate analysis showed that the HbA1c-GMI value was associated with age, diabetes duration, estimated glomerular filtration rate, mean corpuscular volume (MCV), red cell distribution width (RDW), and time with glucose between 180 and 250 mg/dL. In a multilevel model, only age and RDW, positively, and MCV, negatively, were correlated to HbA1c-GMI. Conclusion: The difference between HbA1c and GMI is clinically relevant in a high percentage of cases. Age and easily accessible hematological parameters (MCV and RDW) can help to interpret these differences.en_US
dc.languageengen_US
dc.relation.ispartofJournal of diabetes science and technologyen_US
dc.sourceJournal of Diabetes Science and Technology[EISSN 1932-2968], (Agosto 2023)en_US
dc.subject32 Ciencias médicasen_US
dc.subject320502 Endocrinologíaen_US
dc.subject3206 Ciencias de la nutriciónen_US
dc.subject.otherContinuous Glucose Monitoringen_US
dc.subject.otherGlucose Management Indicatoren_US
dc.subject.otherHba1Cen_US
dc.subject.otherMean Corpuscular Volumeen_US
dc.subject.otherRed Cell Distribution Widthen_US
dc.subject.otherType 1 Diabetes Mellitusen_US
dc.titleAge and Red Blood Cell Parameters Mainly Explain the Differences Between HbA1c and Glycemic Management Indicator Among Patients With Type 1 Diabetes Using Intermittent Continuous Glucose Monitoringen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1177/19322968231191544en_US
dc.identifier.scopus85167827956-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcid0000-0001-9642-3996-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcid0000-0001-8535-8543-
dc.contributor.authorscopusid58534811200-
dc.contributor.authorscopusid58534458600-
dc.contributor.authorscopusid58488587500-
dc.contributor.authorscopusid7801528300-
dc.contributor.authorscopusid54080032500-
dc.contributor.authorscopusid7401456520-
dc.contributor.authorscopusid57040823800-
dc.contributor.authorscopusid7003952293-
dc.identifier.eissn1932-2968-
dc.investigacionCiencias de la Saluden_US
dc.type2Artículoen_US
dc.utils.revisionen_US
dc.date.coverdateAgosto 2023en_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-MEDen_US
dc.description.sjr1,048
dc.description.sjrqQ1
dc.description.miaricds9,6
item.grantfulltextopen-
item.fulltextCon texto completo-
crisitem.author.deptGIR Estadística-
crisitem.author.deptDepartamento de Matemáticas-
crisitem.author.deptGIR IUIBS: Diabetes y endocrinología aplicada-
crisitem.author.deptIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.deptGIR IUIBS: Diabetes y endocrinología aplicada-
crisitem.author.deptIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.deptDepartamento de Ciencias Médicas y Quirúrgicas-
crisitem.author.deptGIR IUIBS: Diabetes y endocrinología aplicada-
crisitem.author.deptIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.deptDepartamento de Ciencias Médicas y Quirúrgicas-
crisitem.author.orcid0000-0003-1681-7165-
crisitem.author.orcid0000-0001-9642-3996-
crisitem.author.orcid0000-0002-7663-9308-
crisitem.author.orcid0000-0001-8535-8543-
crisitem.author.parentorgDepartamento de Matemáticas-
crisitem.author.parentorgIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.parentorgIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.parentorgIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.fullNameSaavedra Santana, Pedro-
crisitem.author.fullNameAlberiche Ruano,Maria Del Pino-
crisitem.author.fullNameWägner, Anna Maria Claudia-
crisitem.author.fullNameBoronat Cortés, Mauro-
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