Clinical trial NCT02290600: Feasibility Study Using Run-to-Run Control to Optimize Continuous Glucose Sensor Bias
Official title: Feasibility Study Using Run-to-Run Control to Optimize Continuous Glucose Sensor Bias
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Diabetes
Lead sponsor: Sansum Diabetes Research Institute
Sponsor class: OTHER
First posted: 2014-11-14
Enrollment: 23
Sex: ALL
Minimum age (years): 18
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Type 1 diabetes

Brief summary: The purpose of this 12 week feasibility study is to see how much more accurate a continuous glucose monitor (CGM) might be in individuals with type 1 diabetes if the investigators personalize sensor calibrations to the user, based on previous wear.

Detailed description: The purpose of this 12 week study is to see how much more accurate a continuous glucose monitor (CGM) might be if we personalize the sensor calibration algorithm for each individual. The calibration algorithm is a mathematical calculation built into the CGM. Currently, the CGM asks for a regular blood test (finger stick) measurement twice a day in order to make its calibration algorithm more accurate. Our goal is to keep refining the calculating ability so that it will provide personalized blood sugar control throughout the day for each individual using the sensor with the CGM.

Eligibility criteria: Inclusion Criteria:

* Clinical diagnosis of type 1 diabetes for at least one year.
* The diagnosis of type 1 diabetes is based on the investigator's judgment; C peptide level and antibody determinations are not needed.
* Actively using an insulin pump (CSII therapy) for the last 6 months, and will continue to use an insulin pump throughout the trial.
* Age 18 to 75 years.
* For females, not currently known to be pregnant or nursing.
* HbA1c \< 9.5%, as measured with DCA2000 or equivalent device.
* Willing to perform the calibration of the study CGMs using a finger stick only and willing to follow instructions for CGM wear.
* Able to and agrees to avoid the following medication starting 24 hours before sensor wear through completion of the study: acetaminophen, prednisone.
* An understanding of and willingness to follow the protocol and sign the informed consent.

Exclusion Criteria:

* Pregnancy (as determined by a positive blood pregnancy test performed in females of childbearing capacity during screening visit and before phase II) or nursing mother.
* Diabetic ketoacidosis in the past 6 months prior to enrollment requiring emergency room visit or hospitalization.
* Severe hypoglycemia resulting in seizure or loss of consciousness in the 6 months prior to enrollment.
* Current treatment for a seizure disorder: Subjects with a history of seizures may be included in the study if they receive written clearance from their neurologist.
* A known medical condition that in the judgment of the investigator might interfere with the completion of the protocol such as cognitive deficit.
* Mental incapacity, unwillingness or language barriers precluding adequate understanding or co-operation, including subjects not able to read or write.
* Active coronary artery disease or heart failure
* Active gastroparesis
* If on antihypertensive, thyroid, anti-depressant or lipid lowering medication, lack of stability on the medication for the past 2 months prior to enrollment in the study.
* Uncontrolled thyroid disease: Adequately treated thyroid disease and celiac disease do not exclude subjects from enrollment.
* Abuse of alcohol.
* A recent injury to body or limb, muscular disorder, use of any medication, any carcinogenic disease, or other significant medical disorder if that injury, medication or disease in the judgment of the investigator will affect the completion of the protocol.
* Current use of a beta blocker medication.
* Laboratory results:
* Hematocrit \< 30% or \>55%.
* A1C ≥ 9.5%
* Abnormal liver or renal function (Transaminase \>2 times the upper limit of normal, Creatinine\> 1.5 mg/dL)
* Labs drawn at screening visit or within two months prior to screening (for other purposes) will suffice for enrollment purposes.
* Subject has skin conditions that, in the determination of the investigator, would preclude wearing the study devices (CGM sensor), in the abdomen or upper buttocks. Examples include but are not limited to: psoriasis, burns, scaring, eczema, tattoos, and significant hypertrophy at sites of device wear; any known allergy to medical adhesives.
* Current participation in another investigational trial or has previously participated in this study. However, for this study, if the augmented calibration algorithm is modified or more data is needed to update the calibration algorithm, subjects will be allowed to re-consent for additional studies at the judgment of the investigator. Similarly, if there is missing data from the data collection due to device failure, transmission errors or other problems, the subject will be allowed to extend the time required to continue each phase as per the judgment of the investigator and will not be excluded from continuing the study.

Primary outcomes:
measure: Accuracy of continuous glucose sensor output by individualizing sensor bias in subjects with type 1 diabetes, assessed by quantifying the improvement in CGM accuracy as measured by MARD (mean absolute relative difference).
timeFrame: 3 months
Secondary outcomes:
measure: Continuous Glucose Monitor sensor bias
timeFrame: 3 months
measure: Continuous Glucose Monitor sensor failure
timeFrame: 3 months
Other outcomes:
Locations:
city: Santa Barbara
country: United States
facility: Sansum Diabetes Research Institute
state: California
Study officials:
affiliation: Sansum Diabetes Research Institute
name: Jordan Pinsker, M.D.
role: PRINCIPAL_INVESTIGATOR
References:
citation: Zavitsanou S, Lee JB, Pinsker JE, Church MM, Doyle FJ 3rd, Dassau E. A Personalized Week-to-Week Updating Algorithm to Improve Continuous Glucose Monitoring Performance. J Diabetes Sci Technol. 2017 Nov;11(6):1070-1079. doi: 10.1177/1932296817734367. Epub 2017 Oct 16.