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The different methods of assessing glycemic variability, quality of glycemic control and glycemic risk cannot be interpreted as equivalent in clinical practice

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dc.contributor.authorMuñoz Velandia, Oscar Mauricio
dc.contributor.authorGómez García, Ana María
dc.contributor.authorGarcía Jaramillo, Maira
dc.contributor.authorLeon Vargas, Fabián Mauricio
dc.contributor.authorRuíz, Álvaro J
dc.contributor.corporatenamePontificia Universidad Javeriana. Facultad de Medicina. Departamento de Medicina Interna. Grupo de Investigación de Enfermedades Crónicas del Adulto
dc.contributor.corporatenamePontificia Universidad Javeriana. Facultad de Medicina. Departamento de Epidemiología Clínica y Bioestadística
dc.date.accessioned2020-05-13T21:16:03Z
dc.date.available2020-05-13T21:16:03Z
dc.date.created2018
dc.description.abstractenglishObjective Several methods are available to calculate glycemic variability (GV), quality of glycemic control (QGC) and glycemic risk (GR). However, clinicians do not easily interpret these data. This study evaluates whether the results of the different methods can be interpreted as equivalent. Methods A prospective study was performed including outpatients with DMT2 evaluated at the San Ignacio Hospital and the Colombian Diabetes Association in Bogotá, Colombia. From six-day continuous glucose monitoring data, GV (SD, CV, IQR, MODD, MAGE), QGC (M-value, J-index) and GR (LBGI, HBGI) were calculated. Reference values ​​were generated, classifying the patients according to GV control quartiles (excellent, good, fair or poor). The concordance between the different indices was evaluated. Results In total, 140 patients (68.9 ± 11.2 years) were included. The agreement levels (Kappa) between GV indices were moderate, 0.40 (CI 95%:0.29–0.51), 0.42 (CI 95%:0.31–0.53) and 0.39 (CI 95%:0.28–0.50), for CV versus SD, IQR and CONGA respectively. The levels of agreement between GV and QGC indices were minimal (Kappa CV vs. M-value, 0.15CI 95%:0.046–0.26) and weak between the GV and GR indices (Kappa CVvs.LBGI 0.37CI95%:0.26–0.48). The estimators did not improve significantly when the analysis was performed with linearly weighted or quadratic weighted Kappa. Conclusions The present study demonstrates that the concordance between the clinical interpretation of the different GV, QGC and GR indices is poor, suggesting that they cannot be assumed as equivalent, so different indices evaluating different concepts, must be evaluated simultaneously to analyze adequately each patient. New studies are needed to evaluate which of the methods better predicts hypoglycemia and microvascular or macrovascular complications.spa
dc.description.paginas555-561spa
dc.description.quartilescopusQ2spa
dc.formatPDFspa
dc.format.mimetypeapplication/pdfspa
dc.format.soportePapel / Electrónicospa
dc.identifierhttps://reader.elsevier.com/reader/sd/pii/S1871402118300651?token=DCB4B2F68EB57F80EBA6001928A1C65AA2B3B2562A5C9B16FEA7726A2799AF89C695A8E6FD669F8D2DC01E4E89479C4Fspa
dc.identifier.doihttps://doi.org/10.1016/j.dsx.2018.03.028spa
dc.identifier.issn1871-4021spa
dc.identifier.urihttp://hdl.handle.net/10554/49218
dc.languagespaspa
dc.rights.licenceAtribución-NoComercial 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.sourceDiabetes & Metabolic Syndrome; Vol. 12 Núm. 4 (2018)spa
dc.subject.keywordType 2 diabetesspa
dc.subject.keywordContinuous glucose monitoringspa
dc.subject.keywordGlucose variabilityspa
dc.subject.keywordConcordancespa
dc.titleThe different methods of assessing glycemic variability, quality of glycemic control and glycemic risk cannot be interpreted as equivalent in clinical practicespa
dc.typeinfo:eu-repo/semantics/article
dc.type.hasversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.localArtículo de revistaspa

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