Predicting Hypoglycaemia and Arrhythmias in the Patient With Diabetes and CKD - Validation Study

NCT ID: NCT02778269

Last Updated: 2017-04-07

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

7 participants

Study Classification

INTERVENTIONAL

Study Start Date

2016-06-30

Study Completion Date

2017-03-31

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

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). 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.

In this validation study a 12-lead ECG T-shirt consisting of textile electrodes and a data logging device wich can record long-term 12-lead ECG data will be tested. The purpose of the T-shirt is to improve the patient's comfort for long-term recordings and to prevent adverse effects of regular ECG electrodes. Current systems are limited by the use of ECG electrodes involving disadvantages like severe direct side effects on the skin such as rash and bullous lesions as well as slipping electrodes. By the means of the proposed ECG T-shirt those drawbacks will be avoided.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

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). 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. It has been postulated that severe hypoglycemia may lead to cardiac arrhythmias, later summarized as the "dead in bed" syndrome. 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. Moreover, CKD markedly increases the risk for hypoglycemia and even a moderate impairment of kidney function (eGFR \< 45 ml/min) is associated with a significant increase in SCD.

Various pathophysiological mechanisms may contribute to the increased cardiovascular mortality after hypoglycemia including hypoglycemia-induced release of catecholamines, pro-arrhythmogenic ECG alterations as well as inflammatory changes. Morphological and functional alterations of the heart occurring in CKD further contribute to these mechanisms. So far performed 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, atrioventriculare (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). In patients with diabetes hypoglycemia, diabetic cardiomyopathy, as well as the presence of autonomic neuropathy may lead to such ECG abnormalities. Merely 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. To date, more sophisticated markers such as QT dispersion, late potentials, or T-wave alternans 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.

In an actually running project the investigators are evaluating the association of hypoglycemic events/glucose swings and arrhythmias/ECG predictors for SCD a clinical study will be performed in 50 patients with insulin-treated diabetes and moderate to severe CKD. These patients receive 7 days continuous glucose and ECG registration and data will be used for the development of the risk assessment model.

The current validation study seeks to confirm the risk assessment model developed in collaboration with AICES - Aachen Institute for Advanced Study in Computational Engineering Science and to approve the capacitive ECG registration device obtained in collaboration with Philips Chair for Medical Information Technology at University Clinical Center Aachen (UKA). To this end, 10 patients with insulin-treated diabetes and moderate to severe CKD will be included. Seven day glucose monitoring as well as data of capacitive ECG recordings will be generated in this study, thus allowing validation and adjustment of the developed medical hardware and the mathematic models. The study item is a 12-lead ECG T-shirt consisting of textile electrodes and a data logging device. The device can record long-term 12-lead ECG data. The purpose of the T-shirt is to improve the patient's comfort for long-term recordings and to prevent adverse effects of regular ECG electrodes. Current systems are limited by the use of ECG electrodes, which are hardly tolerated by the patients because of severe direct side effects on the skin such as rash and bullous lesions. These side effects are a result of skin preparation and electrode gel. The proposed ECG T-shirt does not need these problematic preparations. Another benefit is the fixed placement of the electrodes on the T-shirt. In regular 12-lead ECG long-term recordings, the electrodes may fall off and the patient needs to reattach them. Therefore, faulty positioning of the electrodes may occur.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Diabetes Hypoglycaemia Chronic Kidney Disease

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

PREVENTION

Blinding Strategy

NONE

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

Study Treatment

The patients wear a 12-lead ECG T-shirt for 7 days. During this time period ECG data are measured continuously. In addition the continous glucose monitoring system (CGM) records glucose levels via Dexcom G4-System.

Group Type EXPERIMENTAL

12-lead ECG T-shirt

Intervention Type DEVICE

The 12-lead ECG T-shirt system consists of three parts: the recording device, amplifier boards and the T-shirt.The T-shirt has 10 textile ECG electrode patches. The patches should be in contact with the patient's skin to record the electrical activity of the heart. The electrodes are made of electrically conductive textile. They are sewn into the inside of the T-shirt and are padded with foam. The cables to the device can be attached to snap fasteners on the outer side of the T-shirt on the ECG electrode patches.

Dexcom G4-System

Intervention Type DEVICE

Continuous Glucose Monitoring

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

12-lead ECG T-shirt

The 12-lead ECG T-shirt system consists of three parts: the recording device, amplifier boards and the T-shirt.The T-shirt has 10 textile ECG electrode patches. The patches should be in contact with the patient's skin to record the electrical activity of the heart. The electrodes are made of electrically conductive textile. They are sewn into the inside of the T-shirt and are padded with foam. The cables to the device can be attached to snap fasteners on the outer side of the T-shirt on the ECG electrode patches.

Intervention Type DEVICE

Dexcom G4-System

Continuous Glucose Monitoring

Intervention Type DEVICE

Other Intervention Names

Discover alternative or legacy names that may be used to describe the listed interventions across different sources.

CGM

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

1. Insulin-treated diabetes mellitus (type 1 or 2)
2. CKD with eGFR \< 45 ml/min, determined using the Modification of Diet in Renal Disease (MDRD) formula
3. Stable anti-diabetic and cardiac medication prior to inclusion
4. Male aged ≥ 18 years
5. Written informed consent prior to study participation
6. Adults who are contractually capable and mentally able to understand and follow the instructions of the study personnel.

Exclusion Criteria

1. Pregnancy or women without sufficient contraception, adapted specifically to amenorrhoeic 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. Patients with any kind of pacemakers
9. Expected non-compliance
10. Patients unwilling or unable to give informed consent, or with limited ability to comply with instructions for this study
11. Participation in a parallel interventional clinical trial
Minimum Eligible Age

18 Years

Eligible Sex

MALE

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

RWTH Aachen University

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Responsibility Role SPONSOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

Nikolaus Marx, Prof. Dr.

Role: PRINCIPAL_INVESTIGATOR

Uniklinik RWTH Aachen

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Medizinische Klinik I

Aachen, North Rhine-Westphalia, Germany

Site Status

Countries

Review the countries where the study has at least one active or historical site.

Germany

References

Explore related publications, articles, or registry entries linked to this study.

Causes of death. USRDS. United States Renal Data System. Am J Kidney Dis. 1997 Aug;30(2 Suppl 1):S107-17. No abstract available.

Reference Type BACKGROUND
PMID: 9259696 (View on PubMed)

Carrero JJ, de Mutsert R, Axelsson J, Dekkers OM, Jager KJ, Boeschoten EW, Krediet RT, Dekker FW; NECOSAD Study Group. Sex differences in the impact of diabetes on mortality in chronic dialysis patients. Nephrol Dial Transplant. 2011 Jan;26(1):270-6. doi: 10.1093/ndt/gfq386. Epub 2010 Jul 9.

Reference Type BACKGROUND
PMID: 20621930 (View on PubMed)

Tattersall RB. Brittle diabetes revisited: the Third Arnold Bloom Memorial Lecture. Diabet Med. 1997 Feb;14(2):99-110. doi: 10.1002/(SICI)1096-9136(199702)14:23.0.CO;2-I.

Reference Type BACKGROUND
PMID: 9047086 (View on PubMed)

Gill GV, Woodward A, Casson IF, Weston PJ. Cardiac arrhythmia and nocturnal hypoglycaemia in type 1 diabetes--the 'dead in bed' syndrome revisited. Diabetologia. 2009 Jan;52(1):42-5. doi: 10.1007/s00125-008-1177-7. Epub 2008 Oct 30.

Reference Type BACKGROUND
PMID: 18972096 (View on PubMed)

Rana OA, Byrne CD, Greaves K. Intensive glucose control and hypoglycaemia: a new cardiovascular risk factor? Heart. 2014 Jan;100(1):21-7. doi: 10.1136/heartjnl-2013-303871. Epub 2013 May 22.

Reference Type BACKGROUND
PMID: 23697655 (View on PubMed)

Shamseddin MK, Parfrey PS. Sudden cardiac death in chronic kidney disease: epidemiology and prevention. Nat Rev Nephrol. 2011 Mar;7(3):145-54. doi: 10.1038/nrneph.2010.191. Epub 2011 Feb 1.

Reference Type BACKGROUND
PMID: 21283136 (View on PubMed)

Hanefeld M, Duetting E, Bramlage P. Cardiac implications of hypoglycaemia in patients with diabetes - a systematic review. Cardiovasc Diabetol. 2013 Sep 21;12:135. doi: 10.1186/1475-2840-12-135.

Reference Type BACKGROUND
PMID: 24053606 (View on PubMed)

Giorgino F, Leonardini A, Laviola L. Cardiovascular disease and glycemic control in type 2 diabetes: now that the dust is settling from large clinical trials. Ann N Y Acad Sci. 2013 Apr;1281(1):36-50. doi: 10.1111/nyas.12044. Epub 2013 Feb 6.

Reference Type BACKGROUND
PMID: 23387439 (View on PubMed)

Schachinger H, Port J, Brody S, Linder L, Wilhelm FH, Huber PR, Cox D, Keller U. Increased high-frequency heart rate variability during insulin-induced hypoglycaemia in healthy humans. Clin Sci (Lond). 2004 Jun;106(6):583-8. doi: 10.1042/CS20030337.

Reference Type BACKGROUND
PMID: 14717655 (View on PubMed)

Landstedt-Hallin L, Englund A, Adamson U, Lins PE. Increased QT dispersion during hypoglycaemia in patients with type 2 diabetes mellitus. J Intern Med. 1999 Sep;246(3):299-307. doi: 10.1046/j.1365-2796.1999.00528.x.

Reference Type BACKGROUND
PMID: 10475998 (View on PubMed)

Koivikko ML, Karsikas M, Salmela PI, Tapanainen JS, Ruokonen A, Seppanen T, Huikuri HV, Perkiomaki JS. Effects of controlled hypoglycaemia on cardiac repolarisation in patients with type 1 diabetes. Diabetologia. 2008 Mar;51(3):426-35. doi: 10.1007/s00125-007-0902-y. Epub 2007 Dec 19.

Reference Type BACKGROUND
PMID: 18097646 (View on PubMed)

Junttila MJ, Castellanos A, Huikuri HV, Myerburg RJ. Risk markers of sudden cardiac death in standard 12-lead electrocardiograms. Ann Med. 2012 Nov;44(7):717-32. doi: 10.3109/07853890.2011.594807. Epub 2011 Jul 11.

Reference Type BACKGROUND
PMID: 21745092 (View on PubMed)

Robinson RT, Harris ND, Ireland RH, Lee S, Newman C, Heller SR. Mechanisms of abnormal cardiac repolarization during insulin-induced hypoglycemia. Diabetes. 2003 Jun;52(6):1469-74. doi: 10.2337/diabetes.52.6.1469.

Reference Type BACKGROUND
PMID: 12765959 (View on PubMed)

Koivikko ML, Tulppo MP, Kiviniemi AM, Kallio MA, Perkiomaki JS, Salmela PI, Airaksinen KE, Huikuri HV. Autonomic cardiac regulation during spontaneous nocturnal hypoglycemia in patients with type 1 diabetes. Diabetes Care. 2012 Jul;35(7):1585-90. doi: 10.2337/dc11-2120. Epub 2012 May 18.

Reference Type BACKGROUND
PMID: 22611064 (View on PubMed)

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

14-030 MPG

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.