Algorithms Outperform Diabetics at Blood Sugar Control
Small real-world trials hint at automated diabetes treatment devices
The study's authors conducted parallel 10-day trials with 52 participants. One trial tested adolescents at a summer camp. A parallel trial consisted of adults with only minor restriction on their activity or diet.
For five days, all of the participants wore continuous glucose monitors and a pump for insulin and glucagon, hormones which regulate blood sugar levels. The devices communicated with mobile phones, where an experimental application monitored blood sugar levels and governed the delivery of the hormones. The participants also recorded some of their meals in the application during the five-day period of the intervention. The team compared results with those from a five-day period during which the same participants managed their own care.
The researchers, from Boston University and Massachusetts General Hospital, among other institutions, report in the New England Journal of Medicine that the adults using the algorithm spent around 4.8 percent of the time with blood sugar lower than 70 milligrams per deciliter, compared with about 7.4 percent of the time when they managed their own care. Adolescents showed a smaller difference: 6.1 percent with the algorithm vs. 7.6 percent on their own. The adults also had to take emergency sugar interventions with lower frequency: once every 2.3 days versus every 1.5 days in the control setup. Adolescents, who were more active than adults, took sugar interventions every 1.6 days while using the algorithm instead of every 0.8 days on their own.
Automated monitoring and intervention for Type 1 diabetes is a busy research area and a Food and Drug Administration (FDA) priority. Another team at the ADA meeting reported positive results from a small feasibility trial of its own artificial pancreas algorithm. And a study published last month in Diabetes Care focused on overnight automated blood sugar monitoring and intervention. In that trial, 45 participants compared the algorithm to no interventions over an average of 42 nights. On the nights they used the software, the participants averaged 81 percent less time with low blood sugar.
Such devices take a long time to get from trial to market, but that kind of math should help Type 1 diabetes sufferers one day get a better night's rest.
Lucas Laursen is a journalist covering global development by way of science and technology with special interest in energy and agriculture. He has lived in and reported from the United States, United Kingdom, Switzerland, and Mexico.