Improved Glycemic Control in Diabetic Patients in Hemodialysis Using Continuous Glucose Monitoring (CGM)

Hemodialysis Clinical Trial

Official title:

Improved Glycemic Control in Diabetic Patients in Hemodialysis Using Continuous Glucose Monitoring (CGM)

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05678712
• Other study ID #: N-20210070
• Status: Completed
• Phase: N/A
• Start date: March 9, 2022
• Est. completion date: December 18, 2023

Study information

• Verified date: January 2024
• Source: Aalborg University Hospital
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The 16-week trial is an open-label cross-over trial which includes heamodialysis patients with T2D and T1D on insulin therapy. During one period, patients carry a non-blinded CGM. In the other period they follow standard procedures (the last two weeks with a blinded CGM). The patients and the dialysis staff can use the CGM measures to regulate insulin and food intake during the non-blinded weeks. The research group will collect the CGM-data during the trial.

Description:

Background: Managing diabetes is often problematic in haemodialysis (HD) patients. Low blood glucose is especially common during treatment. Typically, the patient's blood sugar is only measured during treatment if considered relevant. Otherwise, HbA1c is used to control diabetes - a method associated with uncertain in HD patients. An alternative or supplement to the current management of diabetes could be CGM which enables closer observation and management of the diabetes disease. Despite the possibilities of using CGM, there are still few studies in the field which examine the importance of CGM data in relation to the management of diabetes in HD patients.

Aims: To investigate whether the use of CGM data can prevent low blood sugar levels during HD and examins whether the use of CGM data can improve the management of diabetes in HD patients. Furthermore, it is found relevant to investigate if CGM data, selected blood test responses, treatment data, personal data and information about medicines can be used to predict low blood sugar during HD using an algorithm. Thus, the study also aims to develop and validate such an algorithm.

Setting: The trial will be conducted at two dialysis wards (Aalborg and Hjørring) at Aalborg University Hospital.

Subjects: Heamodialysis patients with T1D and T2D on insulin therapy.

Study design: The 16-week trial is an open-label cross-over trial. During one period, patients carry a non-blinded CGM. In the other period they follow standard procedures (the last two weeks with a blinded CGM). The patients and the dialysis staff can use the CGM measures to regulate insulin and food intake during the non-blinded weeks. The research group will collect the CGM-data during the trial. The last four weeks include baseline measures (blinded CGM).

Recruitment information / eligibility

• Status: Completed
• Enrollment: 23
• Est. completion date: December 18, 2023
• Est. primary completion date: December 18, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• = 18 years

• Chronically ill heamodialysis patients (heamodialysis or heamodiafiltration - treatment)der modtager HD- eller hæmodiafiltrationsbehandling på dialyseafsnit,--

• Patients at dialysis wards in Aalborg and Hjørring, Aalborg University Hospital (center and home patients)

• T1D or T2D and in treatment with insulin

• Being able to use CGM equipment

• Signed consent

Exclusion Criteria:

• Pregnancy or breastfeeding,

• Terms that, in the opinion of the investigator or subinvestigators, render the participant unfit to conduct the trial, including lack of understanding of the trial or lack of physical or cognitive ability to participate

• Patients undergoing peritoneal dialysis (PD) or heamofiltration dialysis (HF)

• Acute HD treatment

• Gestational diabetes

Related Conditions & MeSH terms

• Diabetes Mellitus
• Hemodialysis
• Type1diabetes

Intervention

Device:
• Access to CGM data (Dexcom G6)
Acces to CGM data (not blinded CGM)

Locations

Country	Name	City	State
Denmark	Department of nephrology (dialysis)	Aalborg

Sponsors (3)

Lead Sponsor	Collaborator
Aalborg University Hospital	Aalborg University, Steno Diabetes Center Nordjylland

Country where clinical trial is conducted

Denmark, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Hypo- and hyperglycemic episodes	Number of hypo- and hyperglycemic episodes (15 minutes)	6 weeks of treatment in each of the two treatment periods
Other	Insulin requirements	Changes in insulin requirements based on detection/memorisation (with help from nurse) of insulin doses and time points	6 weeks of treatment in each of the two treatment periods
Other	Diabetes-related quality of life	Assessing whether there is a difference between intervention and standard treatment. Measured using the Dawn-2 Impact of Diabetes Questionnaire (DIDP) questionnaire	Week 0, week 6, week 8, week 14
Primary	time below range (CGM)	Change in time below range (CGM) (< 3.0 mmol/L)	6 weeks of treatment in each of the two treatment periods
Secondary	Time in range (CGM)	Change in time in range (CGM) (3,9-10,0 mmol/L)	6 weeks of treatment in each of the two treatment periods
Secondary	Time in borderline low range (CGM)	Change in CGM time in low range(3.0 mmol/L = glucose < 3.9 mmol/L)	6 weeks of treatment in each of the two treatment periods
Secondary	Time above range (CGM)	Change in CGM time above range (>10 mmol/L)	6 weeks of treatment in each of the two treatment periods
Secondary	Time above range (CGM) (high)	Change in CGM time above range (>13,9 mmol/L)	6 weeks of treatment in each of the two treatment periods
Secondary	Concentration of HbA1c	Change in HbA1c	6 weeks of treatment in each of the two treatment periods
Secondary	Glucose variability	Glucose variability (variation coefficient or SD)	6 weeks of treatment in each of the two treatment periods
Secondary	Sensitivity and specificity of algorithm	Sensitivity and specificity of algorithm to predict hypoglycemias	Through study completion, an average of one year