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Trial record 38 of 38 for:    alternans

Predicting Hypoglycaemia and Arrhythmias in the Vulnerable Patient With Diabetes and Chronic Kidney Disease (HypoArrhyth)

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ClinicalTrials.gov Identifier: NCT02315300
Recruitment Status : Completed
First Posted : December 11, 2014
Last Update Posted : June 15, 2016
Sponsor:
Information provided by (Responsible Party):
RWTH Aachen University

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.

Condition or disease Intervention/treatment Phase
Electrocardiography Device: medilog® DARWIN FD12 Device: Continuous Glucose Monitoring Not Applicable

  Show Detailed Description

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Study Type : Interventional  (Clinical Trial)
Actual Enrollment : 62 participants
Intervention Model: Single Group Assignment
Masking: None (Open Label)
Primary Purpose: Prevention
Official Title: Predicting Hypoglycaemia and Arrhythmias in the Vulnerable Patient With Diabetes and Chronic Kidney Disease
Study Start Date : November 2014
Actual Primary Completion Date : May 2016
Actual Study Completion Date : May 2016

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Arm Intervention/treatment
Experimental: Study Tretament
Long term ECG measurement is performed with the 12-lead ECG system medilog® DARWIN FD12 from Schillermed to detect different ECG parameter. The continuous glucose monitoring (CGM) system G4 from Dexcom use a tiny sensor inserted under the skin to check glucose levels in tissue fluid. The sensor stays in place for 7 days in parallel to the ECG measurement. A transmitter sends information about glucose levels via radio waves from the sensor to a pagerlike wireless monitor.
Device: medilog® DARWIN FD12
Other Name: ECG

Device: Continuous Glucose Monitoring
Other Name: CGM




Primary Outcome Measures :
  1. heart rate [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG

  2. cardiac rhythm abnormalities [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG

  3. AV block [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG

  4. QT length [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG

  5. QT dispersion [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG

  6. heart-rate variability [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG

  7. T-wave alternans [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG

  8. late potentials [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG

  9. left or right bündle branch blocks [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG

  10. Glucose Levels < 65 mg/dl [ Time Frame: 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 ]
    Changes of ECG parameters during 7 days long term ECG


Secondary Outcome Measures :
  1. Association anf temporal coincidence of glycemic variability as assessed by changes in glucose excursion as well as mean amplitude of glycemic excursion (MAGE) [ Time Frame: 18 months ]
    • occurence of clinically relevant hypoglycemia
    • occurence of symptomatic hypotension
    • occurence of hypertensive urgency & emergency



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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT02315300


Locations
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Germany
Medizinische Klinik I
Aachen, North Rhine Westphalia, Germany, 52074
Sponsors and Collaborators
RWTH Aachen University
Investigators
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Principal Investigator: Nikolaus Marx, Prof. Uniklinik RWTH Aachen

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Responsible Party: RWTH Aachen University
ClinicalTrials.gov Identifier: NCT02315300     History of Changes
Other Study ID Numbers: 14-030
First Posted: December 11, 2014    Key Record Dates
Last Update Posted: June 15, 2016
Last Verified: May 2016
Keywords provided by RWTH Aachen University:
ECG, CGM, Hypoglycaemia, Sudden Cardiac Death
Additional relevant MeSH terms:
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Kidney Diseases
Renal Insufficiency, Chronic
Hypoglycemia
Urologic Diseases
Renal Insufficiency
Glucose Metabolism Disorders
Metabolic Diseases