Design and Clinical Evaluation of a Novel Low-Glucose Prediction Algorithm with Mini-Dose Stable Glucagon Delivery in Post-Bariatric Hypoglycemia

Abstract

Background: Postbariatric hypoglycemia (PBH) is a complication of bariatric surgery with limited therapeutic options. We developed an event-based system to predict and detect hypoglycemia based on continuous glucose monitor (CGM) data and recommend delivery of minidose liquid glucagon.

Methods: We performed an iterative development clinical study employing a novel glucagon delivery system: a Dexcom CGM connected to a Windows tablet running a hypoglycemia prediction algorithm and an Omnipod pump filled with an investigational stable liquid glucagon formulation. Meal tolerance testing was performed in seven participants with PBH and history of neuroglycopenia. Glucagon was administered when hypoglycemia was predicted. Primary outcome measures included the safety and feasibility of this system to predict and prevent severe hypoglycemia. Secondary outcomes included hypoglycemia prediction by the prediction algorithm, minimization of time below hypoglycemia threshold using glucagon, and prevention of rebound hyperglycemia.

Results: The hypoglycemia prediction algorithm alerted for impending hypoglycemia in the postmeal state, prompting delivery of glucagon (150 μg). After observations of initial incomplete efficacy to prevent hypoglycemia in the first two participants, system modifications were implemented: addition of PBH-specific detection algorithm, increased glucagon dose (300 μg), and a second glucagon dose if needed. These modifications, together with rescue carbohydrates provided to some participants, contributed to progressive improvements in glucose time above the hypoglycemia threshold (75 mg/dL).

Conclusions: Preliminary results indicate that our event-based automatic monitoring algorithm successfully predicted likely hypoglycemia. Minidose glucagon therapy was well tolerated, without prolonged or severe hypoglycemia, and without rebound hyperglycemia.

Trial registration: ClinicalTrials.gov NCT02733588.

Keywords: Bariatric surgery; Glucagon; Hypoglycemia.

Conflict of interest statement

A.J.L.S., C.M.M., K.M.F., E.C., S.D., F.J.D., E.D., and M.E.P. report no conflicts; B.N., M.C., and S.J.P. are all employed by Xeris Pharmaceuticals. P.S. is a consultant for Xeris Pharmaceuticals. H.Z. is employed by Verily Life Sciences. Work was performed when A.B.G., now employed at Novartis, was an employee of Joslin Diabetes Center.

Figures

FIG. 1.

Stages of system development. Updated characteristics are highlighted in red for each stage.

FIG. 2.

(A) Flowchart of the PBH-DSv002. After acquisition of each new CGM sensor glucose value, the logic here described is followed, which results in either issuance of an alarm or return to standby. (B) Blocks of PBH and LGP* alarm systems. Secondary flowcharts for the two processes for hypoglycemia detection implemented in the PBH-DS, corresponding to the nested boxes in (A). Left chart describes the logic flow after meal detection (PBH detection). Right chart describes the logic flow if CGM sensor signal approaches the hypoglycemia threshold, even if no meal had been detected. CGM, continuous glucose monitor; LGP, Low Glucose Predictor; PBH, postbariatric hypoglycemia; PBH-DS, PBH detection system.

FIG. 3.

Flowchart of the PBH-DS states. The algorithm sequentially switches between three modes of operation depending on the glucose history at each time stamp.

FIG. 4.

(A–D) Data from a representative participant from each stage of system development (stages A–D corresponding to A–D). For each, the top plot shows sensor (black) and plasma (blue) glucose and glucagon concentrations (orange). The bottom plot displays insulin (blue) and C-peptide (orange) concentrations (A–C). Insulin and C-peptide concentrations were unavailable from the participant in stage D due to technical assay issues. The time stamps for the algorithm alarm and glucagon delivery are indicated by marks on the top of each plot.

FIG. 5.

(A) Sensor glucose at time of hypoglycemia prediction alarm (blue symbols) and at nadir (red symbols). Blue symbols indicate individual (solid circle) and mean (outlined circle) sensor glucose at time of the hypoglycemia prediction alarm. Red symbols indicate individual (solid square) and mean (outlined square) nadir sensor glucose values during the 2 h observation period after the hypoglycemia alert. (B) Percentage time when the sensor glucose was ≤75 mg/dL during the 2 h observation period after glucagon delivery. Bar height represents mean percentage time and error bars represent the standard error of the mean.

FIG. 6.

Modified Edinburgh Symptom Score. Autonomic, neuroglycopenic, and nonspecific symptoms were collected at baseline, at the time of the hypoglycemia prediction alarm, and at 15, 30, and 60 min after glucagon bolus. Panels A, B, C, and D correspond to a representative participant visit in each stage of the system development. Panels A and D are from the same participant who enrolled in the first and final stages of system development.

FIG. 7.

A posteriori simulation of data from study visit A-1. The simulated alarm by the PBH-DSv001 algorithm is indicated by the cyan circle. The alarms simulated by PBH-DSv002 are displayed in orange (triangle) and in purple (square). The cyan circle alarm coincides with the alarm that was used in the study visit. Nadir sensor glucose is highlighted in gray. indicates the time difference between the first (and only) alarm of PBH-DSv001 and the first alarm given by PBH-DSv002. Positive values of correspond to PBH-DSv002 alarms occurring before PBH-DSv001 alarms. The value of for the displayed simulation is 25 (min). indicates the time difference between the time of the nadir sensor glucose value and the second alarm given by PBH-DSv002. Positive values of correspond to the second alarm occurring before the nadir glucose. The value of for the displayed simulation is 20 (min).