Clinical trial NCT02315300: Predicting Hypoglycaemia and Arrhythmias in the Vulnerable Patient With Diabetes and Chronic Kidney Disease
Official title: Predicting Hypoglycaemia and Arrhythmias in the Vulnerable Patient With Diabetes and Chronic Kidney Disease
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Electrocardiography
Keywords: ECG, CGM, Hypoglycaemia, Sudden Cardiac Death
Lead sponsor: RWTH Aachen University
Sponsor class: OTHER
First posted: 2014-12-11
Enrollment: 62
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: PREVENTION

Brief summary: Patients with insulin-dependent diabetes mellitus (DM) and chronic kidney disease (CKD) exhibit an excessive risk for cardiac arrhythmias, in particular sudden cardiac death (SCD). Hypoglycemia is a frequent problem in insulin-treated patients, especially in those with CKD, and various studies have shown that hypoglycemic episodes are strong predictors of cardiovascular mortality in both type 1 and type 2 diabetic patients. Experimental data and small clinical studies link hypoglycemia with ECG changes and SCD, but little is known about the direct association of hypoglycemic events and/or rapid swings in blood glucose with arrhythmias in this high risk population. Ideally, an algorithm should help to identify patients at risk for hypoglycemia-associated arrhythmias and SCD, but hitherto systematic analyses of blood glucose values and 12-channel ECGs are lacking in these patients.

Detailed description: Patients with diabetes mellitus (DM), especially those with a long duration of diabetes, insulin treatment and chronic kidney disease (CKD) are vulnerable patients exhibiting a high risk for cardiac arrhythmias and sudden cardiac death (SCD) \[1, 2\]. Various factors such as the presence of coronary heart disease, diabetic cardiomyopathy as well autonomic neuropathy are underlying pathologies associated with the development of potentially fatal arrhythmias in these patients while hypoglycemic events are considered to directly trigger these arrhythmias. In 1991, Tattersall and colleagues were the first to describe the phenomenon of sudden nocturnal death in young patients with type 1 diabetes and reported that many of these patients had recent nocturnal hypoglycemia episodes \[3\]. Therefore it has been postulated that severe hypoglycemia may lead to cardiac arrhythmias, later summarized as the "dead in bed" syndrome \[4\]. In addition, recent data from large cardiovascular outcome trials in patients with type 2 diabetes suggest that severe hypoglycemia is associated with an increased risk of cardiovascular events and cardiovascular related death \[5\]. Moreover, CKD markedly increases the risk for hypoglycemia and even a moderate impairment of kidney function (eGFR \< 60 ml/min) is associated with a significant increase in SCD \[6\].

Various pathophysiological mechanisms may contribute to the increased cardiovascular mortality after hypoglycemia including hypoglycemia-induced release of catecholamines, pro-arrhythmogenic ECG alterations, inflammatory changes, direct effects in the vascular wall such as impaired endothelial function as well as abnormalities in coagulation and platelet function \[7, 8\].

Morphological and functional alterations of the heart occurring in CKD further contribute to these mechanisms. Several small studies performing simultaneous glucose monitoring and ECG recordings addressed the question whether spontaneous hypoglycemic events in patients with diabetes directly lead to cardiac arrhythmias \[9-11\], but hitherto no clear association has been found. These studies were limited by a short duration of glucose and ECG monitoring and by the fact that only 3 lead Holter-ECGs were used, thus not allowing the assessment of more sophisticated ECG abnormalities such as QT dispersion, T-wave alternans, or late potentials. Therefore no clear data exist to predict arrhythmias and SCD and its relation to hypoglycemia in patients with diabetes. Ideally, a SCD risk score could identify and characterize high-risk patients but to date little is known about hypoglycemia-associated ECG markers for the identification of patients at risk for arrhythmias and SCD.

In the general population, various ECG risk markers for SCD have been identified such as heart rate, cardiac rhythm abnormalities, AV block, QT length, QT dispersion, heart-rate variability (HRV), T-wave alternans, late potentials, as well as left- (LBBB) or right-bundle branch block (RBBB) (reviewed in \[12\]). In patients with diabetes hypoglycemia, diabetic cardiomyopathy, as well as the presence of autonomic neuropathy may lead to such ECG abnormalities. Under experimental conditions some of these ECG surrogate parameters have been studied in patients with diabetes in association with hypoglycemia. As such, clamp studies revealed that hypoglycemia prolongs the QT interval and increases QT dispersion (difference between the longest and shortest QT interval in a 12-lead Holter ECG) \[10, 13\], which in conjunction with an increased release of catecholamines during hypoglycemia may promote ventricular arrhythmias. In addition, controlled hypoglycemia in patients with type 1 diabetes alters cardiac repolarization by changing the T-wave amplitude \[11\]. Sparse data exist on the effect of spontaneous hypoglycemic episodes and changes in ECG parameters with only a small study in patients with type 1 diabetes demonstrating that nocturnal hypoglycemia is associated with a decrease in the low-frequency component of heart rate variability \[14\]. To date, more sophisticated markers such as QT dispersion (difference between the longest and shortest QT interval in a 12-lead Holter ECG), late potentials, or T-wave alternans (periodic beat-to-beat variation in the morphology, amplitude or timing of the T waves in ECGs) were not examined in a "real-life setting", most likely because these markers require a 12 lead ECG registration of longer duration.

However, for the establishment of a risk algorithm for the prediction of hypoglycemia-associated arrhythmias it is mandatory to perform long duration simultaneous glucose monitoring and 12 lead ECG registration to capture these ECG risk markers for SCD.

Eligibility criteria: Inclusion Criteria:

1. Insulin-treated diabetes mellitus (type 1 or 2)
2. CKD with eGFR \< 40 ml/min (determined using the MDRD formula)
3. Stable anti-diabetic and cardiac medication prior to inclusion
4. Male or female aged \> 18 years
5. Written informed consent prior to study participation

Exclusion Criteria:

1. Pregnancy or women without sufficient contraception, adapted specifically to amenorrhoic hemodialysis patients
2. Life expectancy below 6 months
3. Participation in another clinical trial within the previous 2 months
4. History of any other illness, which, in the opinion of the investigator, might pose an unacceptable risk when administering study medication
5. Any current or past medical condition and/or required medication to treat a condition that could affect the evaluation of the study
6. Alcohol or drug abuse
7. Patient has been committed to an institution by legal or regulatory order
8. Expected non-compliance
9. Patients unwilling or unable to give informed consent, or with limited ability to comply with instructions for this study
10. Participation in a parallel interventional clinical trial

Primary outcomes:
measure: heart rate
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
measure: cardiac rhythm abnormalities
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
measure: AV block
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
measure: QT length
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
measure: QT dispersion
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
measure: heart-rate variability
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
measure: T-wave alternans
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
measure: late potentials
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
measure: left or right bündle branch blocks
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
measure: Glucose Levels < 65 mg/dl
timeFrame: not a single event or change of the parameter will be assessed after 18 months patterns of this parameter during a 7 days long-term ECG will screened for potential correlation with hypoglycaemic events
Secondary outcomes:
measure: Association anf temporal coincidence of glycemic variability as assessed by changes in glucose excursion as well as mean amplitude of glycemic excursion (MAGE)
timeFrame: 18 months
Other outcomes:
Locations:
city: Aachen
country: Germany
facility: Medizinische Klinik I
state: North Rhine Westphalia
Study officials:
affiliation: Uniklinik RWTH Aachen
name: Nikolaus Marx, Prof.
role: PRINCIPAL_INVESTIGATOR
References: