New insights from continuous glucose monitoring into the route to diabetes

Colás, Ana Fanlo; Vigil, Luis; Castro, Clementina; Vargas, Borja; Varela, Manuel

doi:10.1002/dmrr.3002

Cited by 11 publications

(12 citation statements)

References 34 publications

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“…CGM systems have experienced great surge over the last years, mainly for treatment monitoring, though its use has also been proposed for early diagnosis and phenotyping . In our work, we explore the role of CGM at baseline for the selection of candidates for duodenal exclusion procedures.…”

Section: Discussionmentioning

confidence: 99%

“…Two different prediabetic phenotypes have been described (impaired fasting glucose, IFG and impaired glucose tolerance, IGT), depending on the relative contribution of ß‐cell dysfunction and site of insulin resistance . These differential features might persist once T2DM is established and depict the two possible routes from health to diabetes. In the present article, we refer to loss of tonic or phasic control depending on the predominance of IFG phenotype or IGT phenotype, respectively. Loss of “tonic control” of glycaemia, displayed as an IFG phenotype.…”

Section: Introductionmentioning

confidence: 99%

“…IFG and IGT are conventionally used as qualitative variables, with a distinct threshold (IFG: FBG≥5.5 [or alternatively 6.1 mmol/L] and <7 mmol/L, IGT: glycaemia ≥7.8 mmol/L and <11.1 mmol/L, 2 hours after oral glucose tolerance test). However, a quantitative transformation of these variables increases their sensitivity and may give us new insights into these pathophysiological mechanisms both in prediabetes and T2DM. We therefore analysed two variables: Time under 6.1 mmol/L (TU6.1) (%) assessed the percentage of time the glycaemia levels remained under the 6.1 mmol/L threshold.…”

Section: Introductionmentioning

confidence: 99%

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Influence of glucometric ‘dynamical’ variables on duodenal‐jejunal bypass liner (DJBL) anthropometric and metabolic outcomes

Colás

Varela

Mráz

et al. 2020

Diabetes Metabolism Res

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Background: The endoscopically implanted duodenal-jejunal bypass liner (DJBL) is an attractive alternative to bariatric surgery for obese diabetic patients. This article aims to study dynamical aspects of the glycaemic profile that may influence DJBL effects.Methods: Thirty patients underwent DJBL implantation and were followed for 10 months. Continuous glucose monitoring (CGM) was performed before implantation and at month 10. Dynamical variables from CGM were measured: coefficient of variation of glycaemia, mean amplitude of glycaemic excursions (MAGE), detrended fluctuation analysis (DFA), % of time with glycaemia under 6.1 mmol/L (TU6.1), area over 7.8 mmol/L (AO7.8) and time in range. We analysed the correlation between changes in both anthropometric (body mass index, BMI and waist circumference) and metabolic (fasting blood glucose, FBG and HbA1c) variables and dynamical CGMderived metrics and searched for variables in the basal CGM that could predict successful outcomes.Results: There was a poor correlation between anthropometric and metabolic outcomes. There was a strong correlation between anthropometric changes and changes in glycaemic tonic control (ΔBMI-ΔTU6.1: rho = − 0.67, P < .01) and between metabolic outcomes and glycaemic phasic control (ΔFBG-ΔAO7.8: r = .60, P < .01). Basal AO7.8 was a powerful predictor of successful metabolic outcome (0.85 in patients with AO7.8 above the median vs 0.31 in patients with AO7.8 below the median: Chisquared = 5.67, P = .02). Conclusions:In our population, anthropometric outcomes of DJBL correlate with improvement in tonic control of glycaemia, while metabolic outcomes correlate preferentially with improvement in phasic control. Assessment of basal phasic control may help in candidate profiling for DJBL implantation. K E Y W O R D S diabesity, type 2 diabetes mellitus, continuous glucose monitoring, duodenal-jejunal bypass liner (DJBL), metabolic surgery, detrended fluctuation analysis (DFA)

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Influence of glucometric ‘dynamical’ variables on duodenal‐jejunal bypass liner (DJBL) anthropometric and metabolic outcomes

Colás

Varela

Mráz

et al. 2020

Diabetes Metabolism Res

Self Cite

View full text Add to dashboard Cite

show abstract

“…Generally, the Impaired Fasting Glucose (IFG) phenotype is defined as a categorical variable (fasting glycaemia > 100mg/dl). However, transforming it into a quantitative variable may drastically change its sensitivity [32], so the percentage of time with glycaemia lower than 100 mg/dL has been measured as an indicator of fine fasting glucose control.…”

Section: Methodsmentioning

confidence: 99%

Detrended Fluctuation Analysis in the prediction of type 2 diabetes mellitus in patients at risk: Model optimization and comparison with other metrics

Colás¹,

Vigil²,

Vargas³

et al. 2019

PLoS ONE

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Complexity analysis of glucose time series with Detrended Fluctuation Analysis (DFA) has been proved to be useful for the prediction of type 2 diabetes mellitus (T2DM) development. We propose a modified DFA algorithm, review some of its characteristics and compare it with other metrics derived from continuous glucose monitorization in this setting. Several issues of the DFA algorithm were evaluated: (1) Time windowing: the best predictive value was obtained including all time-windows from 15 minutes to 24 hours. (2) Influence of circadian rhythms: for 48-hour glucometries, DFA alpha scaling exponent was calculated on 24-hour sliding segments (1-hour gap, 23-hour overlap), with a median coefficient of variation of 3.2%, which suggests that analysing time series of at least 24-hour length avoids the influence of circadian rhythms. (3) Influence of pretreatment of the time series through integration: DFA without integration was more sensitive to the introduction of white noise and it showed significant predictive power to forecast the development of T2DM, while the pretreated time series did not. (4) Robustness of an interpolation algorithm for missing values: The modified DFA algorithm evaluates the percentage of missing values in a time series. Establishing a 2% error threshold, we estimated the number and length of missing segments that could be admitted to consider a time series as suitable for DFA analysis. For comparison with other metrics, a Principal Component Analysis was performed and the results neatly tease out four different components. The first vector carries information concerned with variability, the second represents mainly DFA alpha exponent, while the third and fourth vectors carry essentially information related to the two “pre-diabetic behaviours” (impaired fasting glucose and impaired glucose tolerance). The scaling exponent obtained with the modified DFA algorithm proposed has significant predictive power for the development of T2DM in a high-risk population compared with other variability metrics or with the standard DFA algorithm.

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“…Moreover, SMBG cannot capture fluctuations in blood glucose throughout the day and night because of practical limitations on the number and timing of finger sticks. Instead, continuous glucose monitoring (CGM) technology demonstrates clinical details that cannot be disclosed by conventional fasting plasma glucose and HbA 1c and has been widely applied in clinical practice. More importantly, innovative technologies related to CGM, such as wearables, implants, mobile applications, and cloud technology with professional medical intervention, are emerging, which is promising in changing diabetic patients' lives dramatically …”

Section: Introductionmentioning

confidence: 99%

Chinese clinical guidelines for continuous glucose monitoring (2018 edition)

Bao

Chen

et al. 2019

Diabetes Metabolism Res

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Summary Blood glucose monitoring is an important part of diabetes management. Continuous glucose monitoring (CGM) technology has become an effective complement to conventional blood glucose monitoring methods and has been widely applied in clinical practice. The indications for its use, the accuracy of the generated data, the interpretation of the CGM results, and the application of the results must be standardized. In December 2009, the Chinese Diabetes Society (CDS) drafted and published the first Chinese Clinical Guideline for Continuous Glucose Monitoring (2009 edition), providing a basis for the standardization of CGM in clinical application. Based on the updates of international guidelines and the increasing evidence of domestic studies, it is necessary to revise the latest CGM guidelines in China so that the recent clinical evidence can be effectively translated into clinical benefit for diabetic patients. To this end, the CDS revised the Chinese Clinical Guideline for Continuous Glucose Monitoring (2012 Edition) based on the most recent evidence from international and domestic studies.

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New insights from continuous glucose monitoring into the route to diabetes

Cited by 11 publications

References 34 publications

Influence of glucometric ‘dynamical’ variables on duodenal‐jejunal bypass liner (DJBL) anthropometric and metabolic outcomes

Influence of glucometric ‘dynamical’ variables on duodenal‐jejunal bypass liner (DJBL) anthropometric and metabolic outcomes

Detrended Fluctuation Analysis in the prediction of type 2 diabetes mellitus in patients at risk: Model optimization and comparison with other metrics

Chinese clinical guidelines for continuous glucose monitoring (2018 edition)

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