The interrelationship of HbA1c and real-time continuous glucose monitoring in children with type 1 diabetes

Ferenci, Tamás; Körner, Anna; Kovács, Levente

doi:10.1016/j.diabres.2015.01.019

Cited by 19 publications

(10 citation statements)

References 36 publications

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“…Therefore, it does not interfere with the patient's every-day life. These emotional and practical factors may have affected patient behavior in previous studies [10][11][12][13]. We believe that these analyses assessing differences between iPro2 and FreeStyle Libre Pro © are important for patient education, since these could be factors for the interpretation of data during CGM.…”

Section: Discussionmentioning

confidence: 95%

Evaluation of the relationship between glycated hemoglobin A1c and mean glucose levels derived from the professional continuous flash glucose monitoring system

et al. 2020

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Previously, we reported that short-term continuous glucose monitoring (CGM) with the professional iPro2 © CGM device is a good clinical indicator of glycated hemoglobin (HbA1c) levels. However, there was no significant correlation between CGM and HbA1c levels when HbA1c levels were >8.0%. To further investigate this issue, we performed a similar study using the FreeStyle Libre Pro © , a newer device that does not require glucose calibration and allows patients to be examined for up to 14 days. Fifty-nine patients (68% women, 32% men) were examined. Twenty-eight and 31 patients presented with type 1 and type 2 diabetes, respectively. Clinically assessed HbA1c levels were compared to blood glucose levels determined by the FreeStyle Libre Pro © for up to 14 days (10.7 ± 3.7 days). We found a significant correlation between HbA1c and CGM levels even when HbA1c levels were >8.0%. Additionally, the correlation between HbA1c and average glucose was identified with the modern CGM and was found to deviate substantially from the new suggested formula. More importantly, we found a more robust correlation between HbA1c and CGM levels in patients with type 2 diabetes. Overestimation or underestimation of blood glucose levels through CGM might increase the risks of inappropriate clinical treatment of diabetes patients. Our results indicate the need for proper CGM data interpretation individualized for each patient to better assist the determination of customized treatments for patients.

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Section: Discussionmentioning

confidence: 95%

Evaluation of the relationship between glycated hemoglobin A1c and mean glucose levels derived from the professional continuous flash glucose monitoring system

et al. 2020

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“…Therefore effective steps are to be taken to identify the disease at the earlier stage and plan effective measures such that, the after impact can be minimized. Lot of activate research has been witnessed in this area and most of the works presented by various authors focus on either identifying the sensitivity of insulin and understanding the impact of exercises on plasma glucose and insulin levels [10] [11]. Models are also presented for critically examining in the patients of type1 and type2 individually and suggestive methods are there by offered with regard to the physical exercises [12].…”

Section: Revised Manuscript Received On October 20 2019mentioning

confidence: 99%

Early Detection of Diabetic Mellitus Based On Modeling Techniques

Laxmikanth,

Ravi

2019

IJEAT

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Rapid growth of population in particular in elderly, signifies the issues of healthcare have become a concern. Also the lifestyle changes together with social and economical factors influences the cause of disease generation among the generated diseases, diabetic disease is mostly populated. Therefore effective measures are to be taken so that the early wakeup with regard to disease treatment helps to minimize the after effects. In this article, a novel methodology based on Gaussian mixture model built for analyzing the patients and help to identify the disease during the primitive stage. The methodology is presented based on PIMA INDIAN DATASET.The Results derived showcase efficacy of the developed method

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“…The control of the blood glucose level of a diabetic patient is crucial, because the uncontrolled disease can lead to several negative effect [8]. Furthermore, the characteristics and quality of the control is also essential [12].…”

Section: Introductionmentioning

confidence: 99%

Discrete LPV Modeling of Diabetes Mellitus for Control Purposes

Eigner

Siket

Szakál

et al. 2018

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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The utilization of modern and advanced control engineering related methods for the control, estimation and assessment of physiological applications is widespread. It is also well-known that this engineering apparatus is executed on digital computers. The current insufficiency of available and accurate discretized models, especially in case of Diabetes Mellitus (DM), provides incentive for this research. The researchers typically approximate the continuous solutions which may not be the best alternative in many cases, in particular considering numerical stability and cost-effectiveness. In this paper we performed an analysis of the available discretization options in order to develop discrete models with a special focus on the Linear Parameter Varying (LPV) systems. LPV techniques are very useful frameworks which allow the application of linear controller, observer and estimator design. In this study, three LPV discretization and two Jacobian based discretization methods are introduced and analyzed to provide a basis for our further investigations in the topic.

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The interrelationship of HbA1c and real-time continuous glucose monitoring in children with type 1 diabetes

Cited by 19 publications

References 36 publications

Evaluation of the relationship between glycated hemoglobin A1c and mean glucose levels derived from the professional continuous flash glucose monitoring system

Evaluation of the relationship between glycated hemoglobin A1c and mean glucose levels derived from the professional continuous flash glucose monitoring system

Early Detection of Diabetic Mellitus Based On Modeling Techniques

Discrete LPV Modeling of Diabetes Mellitus for Control Purposes

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