Dynamic circadian fluctuations of glycemia in patients with type 2 diabetes mellitus

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dc.contributor.authorVásquez Muñoz, Manuel
dc.contributor.authorArce Álvarez, Alexis
dc.contributor.authorÁlvarez, Cristian
dc.contributor.authorRamírez Campillo, Rodrigo
dc.contributor.authorCrespo, Fernando A.
dc.contributor.authorArias, Dayana
dc.contributor.authorSalazar Ardiles, Camila
dc.contributor.authorIzquierdo, Mikel
dc.contributor.authorAndrade, David C.
dc.date.accessioned2023-04-06T16:42:09Z
dc.date.available2023-04-06T16:42:09Z
dc.date.issued2022-12
dc.descriptionIndexación: Scopus.es
dc.description.abstractBackground: Diabetes mellitus (DM) has glucose variability that is of such relevance that the appearance of vascular complications in patients with DM has been attributed to hyperglycemic and dysglycemic events. It is known that T1D patients mainly have glycemic variability with a specific oscillatory pattern with specific circadian characteristics for each patient. However, it has not yet been determined whether an oscillation pattern represents the variability of glycemic in T2D. This is why our objective is to determine the characteristics of glycemic oscillations in T2D and generate a robust predictive model. Results: Showed that glycosylated hemoglobin, glycemia, and body mass index were all higher in patients with T2D than in controls (all p < 0.05). In addition, time in hyperglycemia and euglycemia was markedly higher and lower in the T2D group (p < 0.05), without significant differences for time in hypoglycemia. Standard deviation, coefficient of variation, and total power of glycemia were significantly higher in the T2D group than Control group (all p < 0.05). The oscillatory patterns were significantly different between groups (p = 0.032): the control group was mainly distributed at 2–3 and 6 days, whereas the T2D group showed a more homogeneous distribution across 2–3-to-6 days. Conclusions: The predictive model of glycemia showed that it is possible to accurately predict hyper- and hypoglycemia events. Thus, T2D patients exhibit specific oscillatory patterns of glycemic control, which are possible to predict. These findings may help to improve the treatment of DM by considering the individual oscillatory patterns of patients. © 2022, The Author(s).es
dc.description.urihttps://biolres.biomedcentral.com/articles/10.1186/s40659-022-00406-1
dc.identifier.citationBiological Research, Volume 55, Issue 1 December 2022 Article number 37es
dc.identifier.doi10.1186/s40659-022-00406-1
dc.identifier.issn0716-9760
dc.identifier.urihttps://repositorio.unab.cl/xmlui/handle/ria/48352
dc.language.isoenes
dc.publisherBioMed Central Ltdes
dc.rights.licenseAtribución 4.0 Internacional (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed.es
dc.subjectCircadian rhythmes
dc.subjectContinuous glucose monitoringes
dc.subjectDiabetes mellituses
dc.subjectGlycemiaes
dc.subjectOscillationses
dc.titleDynamic circadian fluctuations of glycemia in patients with type 2 diabetes mellituses
dc.typeArtículoes
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