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Applications of Variability Analysis Techniques for Continuous Glucose Monitoring Derived Time Series in Diabetic Patients.

ABSTRACT: Methods from non-linear dynamics have enhanced understanding of functional dysregulation in various diseases but received less attention in diabetes. This retrospective cross-sectional study evaluates and compares relationships between indices of non-linear dynamics and traditional glycemic variability, and their potential application in diabetes control. Continuous glucose monitoring provided data for 177 subjects with type 1 (n = 22), type 2 diabetes (n = 143), and 12 non-diabetic subjects. Each time series comprised 576 glucose values. We calculated Poincaré plot measures (SD1, SD2), shape (SFE) and area of the fitting ellipse (AFE), multiscale entropy (MSE) index, and detrended fluctuation exponents (?1, ?2). The glycemic variability metrics were the coefficient of variation (%CV) and standard deviation. Time of glucose readings in the target range (TIR) defined the quality of glycemic control. The Poincaré plot indices and ? exponents were higher (p < 0.05) in type 1 than in the type 2 diabetes; SD1 (mmol/l): 1.64 ± 0.39 vs. 0.94 ± 0.35, SD2 (mmol/l): 4.06 ± 0.99 vs. 2.12 ± 1.04, AFE (mmol²/l²): 21.71 ± 9.82 vs. 7.25 ± 5.92, and ?1: 1.94 ± 0.12 vs. 1.75 ± 0.12, ?2: 1.38 ± 0.11 vs. 1.30 ± 0.15. The MSE index decreased consistently from the non-diabetic to the type 1 diabetic group (5.31 ± 1.10 vs. 3.29 ± 0.83, p < 0.001); higher indices correlated with lower %CV values (r = -0.313, p < 0.001). In a subgroup of type 1 diabetes patients, insulin pump therapy significantly decreased SD1 (-0.85 mmol/l), SD2 (-1.90 mmol/l), and AFE (-16.59 mmol²/l²), concomitantly with %CV (-15.60). The MSE index declined from 3.09 ± 0.94 to 1.93 ± 0.40 (p = 0.001), whereas the exponents ?1 and ?2 did not. On multivariate regression analyses, SD1, SD2, SFE, and AFE emerged as dominant predictors of TIR (? = -0.78, -1.00, -0.29, and -0.58) but %CV as a minor one, though ?1 and MSE failed. In the regression models, including SFE, AFE, and ?2 (? = -0.32), %CV was not a significant predictor. Poincaré plot descriptors provide additional information to conventional variability metrics and may complement assessment of glycemia, but complexity measures produce mixed results.

SUBMITTER: Kohnert KD

PROVIDER: S-EPMC6136234 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Applications of Variability Analysis Techniques for Continuous Glucose Monitoring Derived Time Series in Diabetic Patients.

Kohnert Klaus-Dieter KD Heinke Peter P Vogt Lutz L Augstein Petra P Salzsieder Eckhard E

Frontiers in physiology 20180906

Methods from non-linear dynamics have enhanced understanding of functional dysregulation in various diseases but received less attention in diabetes. This retrospective cross-sectional study evaluates and compares relationships between indices of non-linear dynamics and traditional glycemic variability, and their potential application in diabetes control. Continuous glucose monitoring provided data for 177 subjects with type 1 (<i>n</i> = 22), type 2 diabetes (<i>n</i> = 143), and 12 non-diabeti ...[more]

PMID: 30237767

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Project description:Diabetes in pregnancy is a major burden with acute and long-term consequences. Its treatment requires adequate diagnosis and monitoring of therapy. Many experimental research on diabetes during pregnancy has been performed in rats. Recently, continuous blood glucose monitoring of non-pregnant diabetic rats revealed an increased circadian variability of blood glucose that made a single blood glucose measurement per day inappropriate to reflect glycemic status. Continuous blood glucose measurement has never been performed in pregnant rats. We wanted to perform continuous blood glucose monitoring in pregnant rats to decipher the influence of pregnancy on blood glucose in diabetic and normoglycemic status.We used the transgenic Tet29 diabetes rat model with an inducible knock down of the insulin receptor via RNA interference upon application of doxycycline (DOX) leading to insulin resistant type II diabetes. All Tet29 rats received a HD-XG telemetry implant (Data Sciences International, USA) that measured blood glucose and activity continuously. Rats were divided into four groups and blood glucose was monitored until end of pregnancy or the corresponding period: Tet29?+?DOX (diabetic) non-pregnant, Tet29?+?DOX (diabetic) pregnant, Tet29 (normoglycemic) non-pregnant, Tet29 (normoglycemic) pregnant.All analyzed rats displayed a circadian variation in blood glucose concentration. Circadian variability was much more pronounced in pregnant diabetic rats than in normoglycemic pregnant rats. Pregnancy ameliorated variation in blood glucose in diabetic situation. Pregnancy continuously decreased blood glucose during normoglycemic pregnancy. Diabetic rats were less active than normoglycemic rats. We performed a calculation showing that application of continuous blood glucose measurement reduces animal numbers needed to detect a given effect in experimental setting by decreasing variability and SD.Continuous blood glucose monitoring via a telemetry device in pregnant rats provides a more informative picture of the glycemic situation in comparison to single measurements. This could improve diagnosis and therapy of diabetes, decrease animal numbers within experimental settings, and add another physiological parameter (activity) to the analysis that could be helpful in testing therapeutic concepts targeting blood glucose levels and peripheral muscle function. We propose continuous glucose monitoring as a new tool for the evaluation of pregnant diabetic rats.

Project description:AimsCVD is the main cause of morbidity and mortality in individuals with diabetes. It is currently unclear whether daily glucose variability contributes to CVD. Therefore, we investigated whether glucose variability is associated with arterial measures that are considered important in CVD pathogenesis.MethodsWe included participants of The Maastricht Study, an observational population-based cohort, who underwent at least 48 h of continuous glucose monitoring (CGM) (n = 853; age: 59.9 ± 8.6 years; 49% women, 23% type 2 diabetes). We studied the cross-sectional associations of two glucose variability indices (CGM-assessed SD [SDCGM] and CGM-assessed CV [CVCGM]) and time in range (TIRCGM) with carotid-femoral pulse wave velocity (cf-PWV), carotid distensibility coefficient, carotid intima-media thickness, ankle-brachial index and circumferential wall stress via multiple linear regression.ResultsHigher SDCGM was associated with higher cf-PWV after adjusting for demographics, cardiovascular risk factors and lifestyle factors (regression coefficient [B] per 1 mmol/l SDCGM [and corresponding 95% CI]: 0.413 m/s [0.147, 0.679], p = 0.002). In the model additionally adjusted for CGM-assessed mean sensor glucose (MSGCGM), SDCGM and MSGCGM contributed similarly to cf-PWV (respective standardised regression coefficients [st.βs] and 95% CIs of 0.065 [-0.018, 0.167], p = 0.160; and 0.059 [-0.043, 0.164], p = 0.272). In the fully adjusted models, both higher CVCGM (B [95% CI] per 10% CVCGM: 0.303 m/s [0.046, 0.559], p = 0.021) and lower TIRCGM (B [95% CI] per 10% TIRCGM: -0.145 m/s [-0.252, -0.038] p = 0.008) were statistically significantly associated with higher cf-PWV. Such consistent associations were not observed for the other arterial measures.ConclusionsOur findings show that greater daily glucose variability and lower TIRCGM are associated with greater aortic stiffness (cf-PWV) but not with other arterial measures. If corroborated in prospective studies, these results support the development of therapeutic agents that target both daily glucose variability and TIRCGM to prevent CVD.

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Applications of Variability Analysis Techniques for Continuous Glucose Monitoring Derived Time Series in Diabetic Patients.

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Applications of Variability Analysis Techniques for Continuous Glucose Monitoring Derived Time Series in Diabetic Patients.

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