QT Measurement and Heart Rate Correction during Hypoglycemia: Is There a Bias?

Autor: Ebbe Eldrup, Jette Randløv, Toke Folke Christensen, Johannes J. Struijk, Leif Engmann Kristensen, Ole K. Hejlesen

Publikováno v: Christensen, T F, Randløv, J, Christensen, L E, Eldrup, E, Hejlesen, O K & Struijk, J 2010, ' QT measurement and heart rate correction during hypoglycemia : is there a bias? ', Cardiology Research and Practice, vol. 1, no. 1, pp. Article No. 961290 . https://doi.org/10.4061/2010/961290
Cardiology Research and Practice, Vol 2010 (2010)
Cardiology Research and Practice

Introduction. Several studies show that hypoglycemia causes QT interval prolongation. The aim of this study was to investigate the effect of QT measurement methodology, heart rate correction, and insulin types during hypoglycemia.Methods. Ten adult s

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https://doi.org/10.4061/2010/961290

Modeling the Effect of Blood Glucose and Physical Exercise on Plasma Adrenaline in People with Type 1 Diabetes

Autor: Jette Randløv, Toke Folke Christensen, Ole K. Hejlesen, Jonas Kildegaard, Mette Dencker Johansen

Publikováno v: Kildegaard, J, Christensen, T F, Johansen, M D, Randløv, J & Hejlesen, O K 2007, ' Modeling the effect of blood glucose and physical exercise on plasma adrenaline in people with type 1 diabetes ', Diabetes Technology & Therapeutics, vol. 9, no. 6, pp. 501-507 . https://doi.org/10.1089/dia.2007.0242

Adrenaline is often studied in people with type 1 diabetes during hypoglycemic episodes. Adrenaline is difficult and costly to measure, and therefore a pharmacokinetic model of adrenaline can be a supportive tool that adds information and saves measu

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https://doi.org/10.1089/dia.2007.0242

Hypoglycaemia and QT interval prolongation in type 1 diabetes:Bridging the gap between clamp studies and spontaneous episodes

Autor: Toke Folke Christensen, E. Eldrup, Johannes J. Struijk, Leif Engmann Kristensen, Jette Randløv, Simon Lebech Cichosz, Lise Tarnow, Ole K. Hejlesen

Publikováno v: Christensen, T F, Cichosz, S L, Tarnow, L, Randløv, J, Kristensen, L E, Struijk, J, Eldrup, E & Hejlesen, O 2014, ' Hypoglycaemia and QT interval prolongation in type 1 diabetes : Bridging the gap between clamp studies and spontaneous episodes ', Journal of Diabetes and its Complications, vol. 28, no. 5, pp. 723–728 . https://doi.org/10.1016/j.jdiacomp.2014.03.007

We propose a study design with controlled hypoglycaemia induced by subcutaneous injection of insulin and matched control episodes to bridge the gap between clamp studies and studies of spontaneous hypoglycaemia. The observed prolongation of the heart

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https://vbn.aau.dk/da/publications/f0e32a50-92a9-4e7e-8d20-eb9394cc54ae

QT interval prolongation during spontaneous episodes of hypoglycaemia in type 1 diabetes:the impact of heart rate correction

Autor: Leif Engmann Kristensen, Ole K. Hejlesen, E. Eldrup, Jette Randløv, Lise Tarnow, Toke Folke Christensen, Johannes J. Struijk

Publikováno v: Christensen, T F, Tarnow, L, Randløv, J, Kristensen, L E, Struijk, J, Eldrup, E & Hejlesen, O K 2010, ' QT interval prolongation during spontaneous episodes of hypoglycaemia in type 1 diabetes : the impact of heart rate correction ', Diabetologia, vol. 53, no. 9, pp. 2036-2041 . https://doi.org/10.1007/s00125-010-1802-0

Prolongation of the heart rate corrected QT interval (QTc) is seen during episodes of hypoglycaemia in type 1 diabetes. We studied the relationship between spontaneous hypoglycaemia and the QT interval and hypothesised that the choice of heart rate c

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https://vbn.aau.dk/da/publications/39ceca29-0f56-4cff-b068-8443cf131664

The impact of non-model-related variability on blood glucose prediction

Autor: Jette Randløv, Ole K. Hejlesen, Jonas Kildegaard, Jens Ulrik Poulsen

Publikováno v: Kildegaard, J, Randløv, J, Poulsen, J U & Hejlesen, O K 2007, ' The impact of non-model-related variability on blood glucose prediction ', Diabetes Technology & Therapeutics, vol. 9, no. 4, pp. 363-371 . https://doi.org/10.1089/dia.2006.0039

Physiological models are frequently used to predict blood glucose values from insulin and meal data of people with diabetes. Obviously, errors in the input data used result in prediction errors. A more complex problem is that no model may include all

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https://vbn.aau.dk/da/publications/fe0162f0-91c9-11dc-8188-000ea68e967b