Effect of atenolol on QTc interval lengthening during hypoglycaemia in type 1 diabetes

Lee, S. P.; Harris, Nigel; Robinson, R.; Davies, Clare C.; Ireland, R.H.; Macdonald, I. A.; Heller, Simon

doi:10.1007/s00125-005-1796-1

Cited by 39 publications

(26 citation statements)

References 16 publications

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“…The changes in TCRT tended to be even more evident in the diabetic patients than those occurring in their healthy counterparts. The changes in TCRT were not associated with changes in the autonomic regulation of heart rate, sympatho-adrenal activation or changes in the potassium level, suggesting that hypoglycaemia as such also exerts an influence on cardiac repolarisation patterns by other In several previous studies [3][4][5][6][7][8][9], a prolonged QT c interval and an increased QT dispersion have been reported during hypoglycaemia. According to earlier studies [10], the most often used formula, i.e.…”

Section: Discussionmentioning

confidence: 74%

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Effects of controlled hypoglycaemia on cardiac repolarisation in patients with type 1 diabetes

et al. 2007

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Aims/hypothesis Nocturnal hypoglycaemia may contribute to sudden death in diabetic patients. However, it is not well known why hypoglycaemia makes these patients prone to death. Methods We assessed the effects of controlled hypoglycaemia on cardiac repolarisation using novel electrocardiographic descriptors of T-wave and QRS complex morphology in 16 type 1 diabetic patients and eight healthy counterparts. Several electrocardiographic variables characterising repolarisation were analysed from digitised 12-lead electrocardiograms during a euglycaemic and a hypoglycaemic clamp. Results Hypoglycaemia did not result in significant changes either in the QT interval corrected for heart rate by the nomogram method or in QT dispersion. However, the morphology of the T-wave changed significantly during hypoglycaemia. The T-wave amplitude and area in precordial leads decreased significantly in both groups (p<0.05 to p<0.001). The spatial QRS-T angle (total cosine R to T) (p<0.05) and the height and the width of the T-wave loop (p<0.05 and p<0.01, respectively) were also reduced in the diabetic patients. The changes in the repolarisation parameters did not exhibit any significant association with changes in catecholamine levels or in heart rate variability in either group. Conclusions/interpretation Hypoglycaemia results in distinct alterations in cardiac repolarisation, which may increase the vulnerability to arrhythmic events.

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Section: Discussionmentioning

confidence: 74%

“…Observational and experimental studies have demonstrated that hypoglycaemia results in a prolonged QT interval and an increased QT dispersion in healthy individuals and in patients with type 1 and type 2 diabetes [3][4][5][6][7][8][9]. This may partly explain the proarrhythmic effects of hypoglycaemia.…”

Section: Introductionmentioning

confidence: 99%

Effects of controlled hypoglycaemia on cardiac repolarisation in patients with type 1 diabetes

et al. 2007

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“…Many studies in either healthy subjects or (type 1 and 2) diabetic patients have investigated the effect of hypoglycaemia on the QT interval. Marques et al [23] and Lee et al [24] have demonstrated a significant QTc prolongation during hypoglycaemia episodes in patients with type 1 diabetes mellitus, and other investigators have found consistent results [25,26] .…”

Section: Hypoglycaemia and The Qt Intervalmentioning

confidence: 77%

Electrocardiological Features in Obesity: The Benefits of Body Surface Potential Mapping

Simonyi¹

2014

Cardiorenal Med

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Background: Various ECG abnormalities are commonly observed in obesity and in metabolic syndrome. Summary: Some of these abnormalities are caused by the pushed-up position of the diaphragm due to obesity and others occur as a result of the complications of the condition. The position of the R wave may change, various arrhythmias may develop or the QT interval may be prolonged, which increases the tendency to malignant arrhythmias. In obesity, the ECG signs of ventricular hypertrophy are less informative due to the accumulation of epicardial and subcutaneous adipose tissue. In general, it can be concluded that a microcirculation disorder is present in metabolic syndrome that may primarily be associated with ST-T wave abnormalities. Key Messages: Body surface potential mapping is a more sensitive method than traditional ECG with potentially greater use for diagnosis mainly in the early phase of non-ST elevation myocardial infarctions.

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“…Not only QTc interval prolongation has a significant impact on hypoglycemia, but an increase in heart rate (HR) also may influence the onset of hypoglycemia. A summary of the mean QTc lengthening during hypoglycemia [23], [24], [25], [26], [27], [28], [29] is shown in Table. I. It can be distantly seen that all the techniques produce a highly significant change of QTc for euglycemia and hypoglycemia conditions.…”

Section: A Electrocardiography (Ecg)mentioning

confidence: 99%

Non-invasive hypoglycemia monitoring system using extreme learning machine for Type 1 diabetes

2016

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Hypoglycemia (low blood glucose level) is a medical emergency and is a very common in type 1 diabetic persons and can occur at any age. It is the major limiting factor to maintain tight glycemic control. The deficiency in glucose counter-regulation may even lead to severe hypoglycaemia. It is always threatening to the well-being of patients with Type 1 diabetes mellitus (T1DM) since more severe hypoglycemia leads to seizures or loss of consciousness and the possible development of permanent brain dysfunction under certain circumstances . Because of that, an accurate continuing hypoglycemia monitoring system is a very important medical device for diabetic patients. Traditionally, different electrochemical glucose meters are adopted to measure the blood glucose. However, they are invasive, discontinuing and uncomfortable methods or painful for patients. In this paper, we proposed a noninvasive hypoglycemia monitoring system using the physiological parameters of electrocardiography (ECG) signal such as heart rate and corrected QT intervals. To enhance the detection accuracy of the hypoglycemia, a new emerging technology called extreme learning machine (ELM) is developed to recognize the presence of hypoglycemic episodes. ELM have both universal approximation and classification capabilities and provides efficient unified solutions to generalize feed-forward neural networks. A real clinical study of sixteen children with T1DM are given in this paper to illustrate the performance of ELM and successfully applied to a non-invasive hypoglycemia monitoring system. The natural occurrence of nocturnal hypoglycemic episodes are associated with increased heart rates (p < 0.06) and increased corrected QT intervals (p < 0.001). For comparison purpose, different computational intelligence technologies such as swarm based neural network, multiple regression based-fuzzy inference system, and fuzzy system were applied to this hypoglycemia monitoring system. By using the proposed ELM-based neural network (ELM-NN), the testing sensitivity (true positive) and specificity (true negative) for detection of hypoglycemia is better than the other intelligence methods with faster training time.

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Effect of atenolol on QTc interval lengthening during hypoglycaemia in type 1 diabetes

Cited by 39 publications

References 16 publications

Effects of controlled hypoglycaemia on cardiac repolarisation in patients with type 1 diabetes

Effects of controlled hypoglycaemia on cardiac repolarisation in patients with type 1 diabetes

Electrocardiological Features in Obesity: The Benefits of Body Surface Potential Mapping

Non-invasive hypoglycemia monitoring system using extreme learning machine for Type 1 diabetes

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