Computer Simulation Model to Train Medical Personnel on Glucose Clamp Procedures
Pooya Maghoul1, Benoit Boulet1, Annie Tardif2
1Department of Electrical and Computer Engineering, Faculty of Engineering, McGill University, Montreal, Quebec, Canada.
Objective:
A glucose clamp procedure is the most reliable way to quantify insulin pharmacokinetics and pharmacodynamics, but skilled and trained research personnel are required to frequently adjust the glucose infusion rate. A computer environment that simulates glucose clamp experiments can be used for efficient personnel training and development and testing of algorithms for automated glucose clamps.
Methods:
We built 17 virtual healthy subjects (mean age, 25±6 years; mean body mass index, 22.2±3 kg/m2), each comprising a mathematical model of glucose regulation and a unique set of parameters. Each virtual subject simulates plasma glucose and insulin concentrations in response to intravenous insulin and glucose infusions. Each virtual subject provides a unique response, and its parameters were estimated from combined intravenous glucose tolerance test-hyperinsulinemic-euglycemic clamp data using the Bayesian approach. The virtual subjects were validated by comparing their simulated predictions against data from 12 healthy individuals who underwent a hyperglycemic glucose clamp procedure.
Results:
Plasma glucose and insulin concentrations were predicted by the virtual subjects in response to glucose infusions determined by a trained research staff performing a simulated hyperglycemic clamp experiment. The total amount of glucose infusion was indifferent between the simulated and the real subjects (85±18 g vs. 83±23 g; p=NS) as well as plasma insulin levels (63±20 mU/L vs. 58±16 mU/L; p=NS).
Conclusions:
The virtual subjects can reliably predict glucose needs and plasma insulin profiles during hyperglycemic glucose clamp conditions. These virtual subjects can be used to train personnel to make glucose infusion adjustments during clamp experiments.
