Accelerometer Use in the Prevention of Exercise-Associated Hypoglycemia in Type 1 Diabetes: Outpatient Exercise Protocol

Regular aerobic exercise confers a plethora of health benefits to all individuals and is
considered an essential component of the management of type 1 diabetes (T1D) [1]. However,
in contrast to non-diabetic subjects - in whom the increased muscle energy requirement
during exercise leads to suppression of endogenous insulin secretion - patients with T1D are
dependent upon exogenous insulin and are thus at risk for exercise-associated hypoglycemia
[1]. Exercise-associated hypoglycemia is the most frequently reported adverse event related
to exercise in diabetes [2] and hypoglycemia can occur during exercise or several hours
afterwards [3,4]. Although previous research has shown that pre-meal dose reduction of
subcutaneous insulin can be effective at decreasing the incidence of exercise-associated
hypoglycemia [5], patients with T1D often do not perform such adjustments [6,7].

In contrast to subcutaneous insulin injections, which are reliant upon the patient or
caretaker to determine dosage, the insulin pump provides a unique opportunity to avoid
hypoglycemia via user-independent, computer-based algorithms for determining insulin
delivery. Previous research conducted here at Stanford has demonstrated that algorithms
based on continuous glucose monitor (CGM) data can prevent hypoglycemia in the sedentary
setting by inducing insulin pump suspension [8-10]. In addition, a study of children and
adolescents conducted at Stanford (as a center in the DirecNet group) demonstrated that
suspending an insulin pump at the beginning of a period of moderate aerobic exercise reduces
the risk of hypoglycemia during that exercise period and subsequently overnight [11]. Thus,
by utilizing exercise-detecting accelerometers and an algorithm to initiate pump suspension
during exercise, it is likely possible that people with diabetes could avoid
exercise-associated hypoglycemia even if they failed to manually alter their pump settings.
However, to date, no published studies have utilized accelerometer-derived data in an
insulin pump suspension algorithm during exercise.

Accelerometers are light-weight motion-sensing devices that can be worn to provide
information about the intensity and duration of physical activity [12]. They are small,
inexpensive, and could easily be incorporated into current sensors and "patch" pumps. They
can also be used independently or combined with a heart rate monitor (HRM) [13], although
most commercially available HRMs currently require a chest strap that can be uncomfortable
to wear. Previous studies evaluating the effect of physical activity on insulin sensitivity
have utilized accelerometers (worn on a belt at the small of the back, the right side of the
trunk in the mid-axillary line, or the left side of the chest) with and without HRMs for
activity recognition during subjects' everyday lives. These data were used to classify
activity as sedentary, light, moderate, or vigorous based on acceleration signal counts
measured over one-minute intervals [13-17]. One study investigated four different
accelerometers in a clinical research setting and found each to be very accurate in
assessing the intensity of physical activity, regardless of subjects' body habitus [18].
Thus, these devices can provide a reliable means by which the onset, duration, and intensity
of exercise can be recognized and reported in real-time to the other components of an
artificial pancreas. When combined with CGM and insulin delivery data, this exercise
information is a valuable tool in designing an algorithm to decrease or stop insulin
delivery in order to decrease the risk of exercise-associated hypoglycemia.

In the first phase of this study (in press), 22 subjects with type 1 diabetes went about
their everyday lives while wearing an insulin pump, CGM, and accelerometer/heart rate
monitor. After the monitoring period, the devices were downloaded and the data were used to
augment an existing predictive low glucose suspend (PLGS) algorithm to incorporate activity.
In a computer simulator, the PLGS algorithm reduced hypoglycemia by 64%, compared to 73% and
76% reductions for the accelerometer-augmented and HRM-augmented algorithms, respectively.

In the next phase of this study, we seek to test the newly developed algorithm in a
real-life setting in the form of a structured sports (soccer) camp.

Inclusion Criteria:

- Clinical diagnosis of type 1 diabetes for 1-20 years. The diagnosis of type 1
diabetes is based on the investigator's judgment; C peptide level and antibody
determinations are not needed.

- Age 8 to 25 years old.

- On daily use of an insulin pump and not anticipating a change prior to the subject's
completion of the study.

- Willingness to allow for CGM insertion (if not already using a study-designated CGM)
for use during the study.

- HbA1c <10%.

- Parent/guardian and subject understand the study protocol and agree to comply with
it.

- Informed Consent Form signed by the parent/guardian and Child Assent Form signed.

Exclusion Criteria:

- A history of recent injury to body or limb, Addison's disease, muscular disorder,
organ/bone marrow transplant, heart disease, or use of any medication or other
significant medical disorder if that injury, medication or disease in the judgment of
the investigator will affect the completion of the exercise protocol.

- Current use of glucocorticoid medication (by any route of administration).

- Current use of a beta blocker medication.

- Severe hypoglycemia resulting in seizure or loss of consciousness in the four weeks
prior to sports camp (if a severe episode occurs after the first but prior to the
scheduled second admission, the visit will be deferred).

- Active infection (if at the time of the planned second visit an infection is present,
the visit will be deferred).