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

Circadian rhythm Continuous glucose monitoring Diabetes mellitus Glycemia Oscillations

Journal

Biological research
ISSN: 0717-6287
Titre abrégé: Biol Res
Pays: England
ID NLM: 9308271

Informations de publication

Date de publication:
02 Dec 2022
Historique:
received: 01 09 2022
accepted: 22 11 2022
entrez: 2 12 2022
pubmed: 3 12 2022
medline: 7 12 2022
Statut: epublish

Résumé

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. 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. 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.

Sections du résumé

BACKGROUND BACKGROUND
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 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 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.

Identifiants

pubmed: 36461078
doi: 10.1186/s40659-022-00406-1
pii: 10.1186/s40659-022-00406-1
pmc: PMC9716682
doi:

Substances chimiques

Blood Glucose 0
Glucose IY9XDZ35W2

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

37

Subventions

Organisme : Iniciativa ANILLO, ANID
ID : ACT210083
Organisme : fondecyt iniciación, ANID
ID : 11220870
Organisme : Minera Escondida Ltda.
ID : MEL2203

Informations de copyright

© 2022. The Author(s).

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Auteurs

Manuel Vásquez-Muñoz (M)

Exercise Applied Physiology Laboratory, Centro de Investigación en Fisiología Y Medicina de Altura, Departamento Biomedico, Facultad de Ciencias de La Salud, Universidad de Antofagasta, Antofagasta, Chile.
Clínica Santa María, Santiago, Chile.
Navarrabiomed, Hospital Universitario de Navarra (UHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Navarra, Spain.

Alexis Arce-Álvarez (A)

Escuela de Kinesiología, Facultad de Salud, Universidad Católica Silva Henríquez, Santiago, Chile.

Cristian Álvarez (C)

Exercise and Rehabilitation Sciences Laboratory, School of Physical Therapy, Faculty of RehabilitationSciences, Universidad Andres Bello, Santiago, Chile.

Rodrigo Ramírez-Campillo (R)

Exercise and Rehabilitation Sciences Laboratory, School of Physical Therapy, Faculty of RehabilitationSciences, Universidad Andres Bello, Santiago, Chile.

Fernando A Crespo (FA)

Departamento de Gestion Y Negocios, Facultad de Economía Y Negocios, Universidad Alberto Hurtado, Santiago, Chile.

Dayana Arias (D)

Departamento de Biotecnología, Facultad de Ciencias del Mar Y Recursos Biológicos, Universidad de Antofagasta, Antofagasta, Chile.

Camila Salazar-Ardiles (C)

Exercise Applied Physiology Laboratory, Centro de Investigación en Fisiología Y Medicina de Altura, Departamento Biomedico, Facultad de Ciencias de La Salud, Universidad de Antofagasta, Antofagasta, Chile.
Navarrabiomed, Hospital Universitario de Navarra (UHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Navarra, Spain.

Mikel Izquierdo (M)

Navarrabiomed, Hospital Universitario de Navarra (UHN), Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Navarra, Spain.
CIBER of Frailty and Healthy Aging (CIBERFES), Instituto de Salud Carlos III, Madrid, Spain.

David C Andrade (DC)

Exercise Applied Physiology Laboratory, Centro de Investigación en Fisiología Y Medicina de Altura, Departamento Biomedico, Facultad de Ciencias de La Salud, Universidad de Antofagasta, Antofagasta, Chile. david.andrade@uantof.cl.

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Classifications MeSH