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

被引:2
作者
Vasquez-Munoz, Manuel [1 ,2 ,3 ]
Arce-Alvarez, Alexis [4 ]
Alvarez, Cristian [5 ]
Ramirez-Campillo, Rodrigo [5 ]
Crespo, Fernando A. [6 ]
Arias, Dayana [7 ]
Salazar-Ardiles, Camila [1 ,3 ]
Izquierdo, Mikel [3 ,8 ]
Andrade, David C. [1 ]
机构
[1] Univ Antofagasta, Fac Ciencias Salud, Ctr Invest Fisiol & Med Altura, Dept Biomed,Exercise Appl Physiol Lab, Antofagasta, Chile
[2] Clin Santa Maria, Santiago, Chile
[3] Univ Publ Navarra UPNA, Hosp Univ Navarra UHN, Navarrabiomed, IdiSNA, Navarra, Spain
[4] Univ Catolica Silva Henriquez, Fac Salud, Escuela Kinesiol, Santiago, Chile
[5] Univ Andres Bello, Fac Rehabil Sci, Sch Phys Therapy, Exercise & Rehabil Sci Lab, Santiago, Chile
[6] Univ Alberto Hurtado, Fac Econ & Negocios, Dept Gest & Negocios, Santiago, Chile
[7] Univ Antofagasta, Fac Ciencias Mar & Recursos Biol, Dept Biotecnol, Antofagasta, Chile
[8] Inst Salud Carlos III, CIBER Frailty & Hlth Aging CIBERFES, Madrid, Spain
关键词
Glycemia; Diabetes mellitus; Circadian rhythm; Oscillations; Continuous glucose monitoring; GLUCOSE VARIABILITY; ASSOCIATION; OBESITY; HYPERTENSION; RETINOPATHY; DURATION; RISK; CGM;
D O I
10.1186/s40659-022-00406-1
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 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.
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页数:9
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共 44 条
[1]  
[Anonymous], 2020, Health at a glance: Latin America and the Caribbean 2020, DOI DOI 10.1787/6089164F-EN
[2]  
Barman P, 2018, DECKERMED MED, DOI [10.2310/im.14056, DOI 10.2310/IM.14056]
[3]   CGM-Based Clinical Targets: Recommendations from the International Consensus on Time-in-Range (TIR) [J].
Battelino, Tadej ;
Danne, Thomas ;
Phillip, Moshe .
DIABETES, 2019, 68
[4]   The relationship of body mass index to diabetes mellitus, hypertension and dyslipidaemia: comparison of data from two national surveys [J].
Bays, H. E. ;
Chapman, R. H. ;
Grandy, S. .
INTERNATIONAL JOURNAL OF CLINICAL PRACTICE, 2007, 61 (05) :737-747
[5]  
Bellazzi Riccardo, 2009, J Diabetes Sci Technol, V3, P603
[6]   Glucose Management Indicator (GMI): A New Term for Estimating A1C From Continuous Glucose Monitoring [J].
Bergenstal, Richard M. ;
Beck, Roy W. ;
Close, Kelly L. ;
Grunberger, George ;
Sacks, David B. ;
Kowalski, Aaron ;
Brown, Adam S. ;
Heinemann, Lutz ;
Aleppo, Grazia ;
Ryan, Donna B. ;
Riddlesworth, Tonya D. ;
Cefalu, William T. .
DIABETES CARE, 2018, 41 (11) :2275-2280
[7]   Epidemiology of Obesity and Diabetes and Their Cardiovascular Complications [J].
Bhupathiraju, Shilpa N. ;
Hu, Frank B. .
CIRCULATION RESEARCH, 2016, 118 (11) :1723-1735
[8]   Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Medical Care in Diabetes-2019 [J].
Cefalu, William T. ;
Berg, Erika Gebel ;
Saraco, Mindy ;
Petersen, Matthew P. ;
Uelmen, Sacha ;
Robinson, Shamera .
DIABETES CARE, 2019, 42 :S34-S45
[9]   Prevalence of hypertension and obesity in patients with type 2 diabetes mellitus in observational studies: a systematic literature review [J].
Colosia, Ann D. ;
Palencia, Roberto ;
Khan, Shahnaz .
DIABETES METABOLIC SYNDROME AND OBESITY-TARGETS AND THERAPY, 2013, 6 :327-338
[10]   The Effects of Type 2 Diabetes Mellitus on Organ Metabolism and the Immune System [J].
Daryabor, Gholamreza ;
Atashzar, Mohamad Reza ;
Kabelitz, Dieter ;
Meri, Seppo ;
Kalantar, Kurosh .
FRONTIERS IN IMMUNOLOGY, 2020, 11