Location of insulin delivery matters for Type 1 patents in fully-automated artificial pancreas study
By Lisa Foster-McNulty, MSN, RN, CDE
Some new research sought to compare intraperitoneal (IP) delivery to subcutaneous (SC) delivery of insulin in an artificial pancreas (AP). This research was published in Diabetes, Obesity, and Metabolism in May of 2017.
Intraperitoneal means that the insulin was administered within or through the peritoneum, which is a thin membrane lining the walls of the abdominal (peritoneal) cavity. It covers the organs of the abdomen, such as the stomach and the intestines.
The research was NOT randomized, and NOT blinded. Ten adult Type 1 patients participated in a sequential AP study that utilized the same SC glucose sensing and Zone Model Predictive Control (ZMPC) algorithm, which was adjusted for clearance of insulin. In the first part of the study, patients experienced closed-loop control with a fast-acting insulin analog delivered SC for 24 hours. They later had a DiaPort IP insulin delivery system implanted into the body. An identical 24 hour study was then done using IP regular insulin delivery. There were three “unannounced” meals with 70, 40, and 70 gm of carbohydrate as part of the clinical protocol. The time that blood glucose (BG) spent in the 80-140 mg/dl (4.4-7.7 mmol/L) was the primary endpoint of this study.
The percent of time spent with the BG between 80 and 140 was significantly higher with IP delivery as compared to SC delivery. Additionally, the percentage of time spent within the broader range of 70-180, as well as the mean BG, was significantly better with IP insulin delivery. The better BG control with IP insulin delivery was a result of less time spent in hyperglycemia. The IP route used higher daily doses of insulin, and there was no increase in time spent with BG levels <70 mg/dl.
The bottom line?
Using a fully-automated AP with IP insulin delivery, glucose regulation was superior to that seen with SC delivery. This was a pilot study, and it gives us proof-of-concept for an AP system which utilizes IP insulin delivery in combination with a ZMPC algorithm. We’re curious to see what results future research yields!
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