Hypo-METRICS: Hypoglycaemia - Measurement, ThResholds and ImpaCtS

Diabetes Mellitus, Type 2 Clinical Trial

— Hypo-METRICS  

Official title:

Hypo-METRICS: Hypoglycaemia - Measurement, ThResholds and ImpaCtS A Clinical Study to Determine the Optimal Threshold and Duration of Low Interstitial Glucose Events That Have an Impact on Patient Experienced Hypoglycaemia, Quality of Life and Health Economic Outcomes.

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04304963
• Other study ID #: 259415
• Status: Completed
• Start date: October 1, 2020
• Est. completion date: October 31, 2022

Study information

• Verified date: July 2023
• Source: King's College London
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Hypoglycaemia or low blood glucose, and its fear are major barriers to achieving optimal glucose control. New technology, such as continuous glucose monitors (CGM), help to better identify hypoglycaemia and develop strategies to avoid it. These devices measure glucose in the skin, rather than in the blood, and provide information not only on how low glucose is, but also for how long. Recent studies showed that over half of episodes of low glucose with these systems are not recognised by people with diabetes, and even people without diabetes have sensor values that are below the current thresholds for hypoglycaemia [ low blood glucose] that we measure with traditional monitors. In this study, the investigators will evaluate the impact of symptomatic as well as asymptomatic episodes of low sensor glucose on a variety of clinical, patient-related and health economic outcomes such as mood, quality of sleep and productivity. The investigators will test different levels and durations of low sensor glucose to identify the one that best matches episodes that are symptomatic to best define hypoglycaemia using these systems. The investigators will also look at factors that influence this such as sleep or activity as well as diabetes management behaviours (such as insulin dosing, carb counting, etc). At the end of this study, the investigators will be able to provide a better definition of clinically relevant low sensor glucose readings that will help inform clinical as well as academic interpretation of CGM data.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 602
• Est. completion date: October 31, 2022
• Est. primary completion date: October 31, 2022
• Gender: All
• Age group: 18 Years to 85 Years

Eligibility

Inclusion Criteria:

1. Age 18 - 85 years

2. HbA1c 5 - 10% [31 - 86 mmol/mol]

3. Confirmed diagnosis of type 1 or type 2 diabetes

4. Using > 1 injection of insulin / day or insulin pump.

5. Ability to provide written informed consent

6. Performing regular SMBG [ > 1 / day on a 4-week download] . For those using flash or continuous glucose monitoring, this should be used at least 70% of the time.

7. At least 1 episode of hypoglycaemia [ either biochemical or symptomatic] in the last month

8. On stable therapy for at least 3 months.

9. Willing to complete study procedures including wearing the Fitbit and CGM devices and completing the EMA questionnaires on the uMotif app three times a day for 10 weeks ( we expect minimum 80% data completeness)

Exclusion Criteria:

1. Concurrent conditions that can affect glucose readings [renal impairment GFR < 30 ml/min, hepatic impairment, untreated adrenal or thyroid insufficiency, as judged by the investigator.

2. Severe cognitive impairment or psychological illness that can impair performance of EMA tasks, visual impairment that will preclude use of the EMA or sensors.

3. Severe psychiatric / psychological illness including extreme fear of hypo- or hyper- glycaemia ( in the opinion of the investigator)

4. Pregnant or plans for pregnancy in the next 6 months

5. Use of automated insulin delivery systems such as closed loop or automated threshold suspend or predictive low glucose suspend insulin pumps.

6. Known allergies to adhesives required for the CGM systems

7. People who work regular night shifts

8. Any other condition which in the opinion of the study team would impair their ability to complete the study

Related Conditions & MeSH terms

• Diabetes Mellitus
• Diabetes Mellitus, Type 1
• Diabetes Mellitus, Type 2
• Hypoglycemia
• Hypoglycemia Unawareness

Intervention

Other:
• NO intervention - observational study
NO intervention - observational study

Locations

Country	Name	City	State
United Kingdom	King's College London	London

Sponsors (16)

Lead Sponsor

Collaborator

King's College London

Abbott Diabetes Care, Cambridge University Hospitals NHS Foundation Trust, Innovative Medicines Initiative, International Diabetes Federation, Juvenile Diabetes Research Foundation, Medical University of Graz, Medtronic Diabetes, Ninewells Hospital, Nordsjaellands Hospital, Novo Nordisk A/S, Radboud University Medical Center, Sheffield Teaching Hospitals NHS Foundation Trust, The Leona M. and Harry B. Helmsley Charitable Trust, University Hospital, Montpellier, University of Southern Denmark

Country where clinical trial is conducted

United Kingdom, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	LIG optimum detection of hypoglycemia	To determine the Low Interstitial Glucose (LIG) parameters that have the optimum performance for detection and identification of patient-reported-hypoglycemia (PRH); ?LIG?_PRH (h_opt,t_opt).	week 10
Secondary	Secondary outcome 1	To evaluate the impact of symptomatic and asymptomatic hypoglycaemia on different domains of Quality of Life (QoL) and health economic variables measured by a bespoke mobile phone application.; We will use the definition of LIG identified in the primary objective, ?LIG?_PRH (h_opt,t_opt), to evaluate the impact of symptomatic and asymptomatic hypoglycaemia on various outcome variables. To do this, we will divide the days into one of 4 categories LIG-PRH- :no hypoglycaemia LIG+PRH- :asymptomatic biochemical hypoglycaemia ( CGM false positive) LIG+PRH+ :symptomatic biochemical hypoglycaemia LIG-PRH+ :symptomatic without biochemical hypoglycaemia (CGM false negative) We will then compare the scores in different domains collected on the app ( eg reported mood, quality of sleep, alertness, productivity, time off work) between the 4 categories.	week 10
Secondary	Secondary outcome 2	To evaluate the impact of adding co-variates such as change of glucose for 30 minutes prior to the event and area under the curve to the threshold and duration parameters to see if this can improve the sensitivity and specificity of ?LIG?_PRH (h_opt,t_opt),	week 10
Secondary	Secondary outcome 3	To evaluate the impact on these optimal parameters [?LIG?_PRH (h_opt,t_opt ] on Type of diabetes ( Type 1 with normal awareness, Type 2, Type 1 with impaired awareness) Awake vs sleeping ( as determined by Fitbit) Usual Mode of glucose monitoring (SMBG vs Flash vs CGM) Rate of ?LIG?_PRH during the study	week 10
Secondary	Secondary outcome 4	To evaluate the impact of the rate of ?LIG?_PRH over the whole study duration on Rate of Patient reported hypoglycaemia ( non-severe) Rate of severe hypoglycaemia Overall EQ-5D-5L scores WPAI ( productivity) PROMIS - (sleep quality) Hypo fear scores Baseline C-peptide levels	week 10
Secondary	Secondary outcome 5	To determine the parameters (threshold and duration) of low interstitial glucose (LIG) that best identify a pre-specified reduction/ change in QoL. [ 0.07 reduction in EQ-5D-5L] ?LIG?_(EQ-5D) (h_opt,t_opt).	week 10
Secondary	Secondary outcome 6	To determine the parameters ( threshold and duration) of low interstitial glucose (LIG) that best identify a pre-specified health economic outcome. [1.5 hour loss of effective work/ activity] ?LIG?_productivity (h_opt,t_opt).	week 10
Secondary	Secondary outcome 7	Determining the predictors of ?LIG?_PRH by looking at variables such as mean glucose, variability, activity (step count and intensity).	week 10
Secondary	Secondary outcome 8	We will evaluate the impact of activity ( step count) on the risk of ?LIG?_PRH the following night. A generalized linear mixed models (GLMM) with step count as the independent variable and the rate of LIG_PRH as the response variable will address this research question	week 10
Secondary	Secondary outcome 9	We will try to understand some of the causes of hypoglycaemia. To do this we will look at the 4 hours prior to every available ?LIG?_PRH (h_opt,t_opt) and PRH and describe the category of events (if also insulin data is available) by classifying them into those with Bolus within range [ < 10 mmol/l] within 4 hours Bolus and correction [ > 10 mmol/l ] within 4 hours No bolus within 4 hours Activity [ as identified by the Fitbit charge 3] within 2 hours.	week 10
Secondary	Secondary outcome 10	Evaluating the effect of personality (assessed by DS-14) on number and severity of hypoglycaemia and the effect of hypoglycaemia on quality of life measures	week 10