Abstract

T (i) Is the PLGS algorithm safe? (ii) Does the PLGS algorithm add to efficacy in preventing hypoglycemia?
It is expected that preventing an episode of hypoglycemia using a PLGS algorithm should be better than with use of the LGS algorithm, as it reduces insulin in advance of hypoglycemia rather than waiting for hypoglycemia to occur. Having a previous hypoglycemic episode is one of the main factors in predicting a hypoglycemic episode (hypoglycemia begets hypoglycemia). 6 Catecholamine release is spared by preventing an episode and likely helps to prevent further episodes. The current report 7 is observational and nonrandomized, so it cannot be used to evaluate the effectiveness of a PLGS system, although it confirms safety. The authors note that the mean glucose values in the 18 subjects with prestudy continuous glucose monitor values, or in the 38 subjects with prestudy blood glucose values, were not different in comparison with study values. This could occur with fewer low glucose values and more subsequent high values secondary to insulin suspension.
In relation to safety, the inclusion criteria used in the current report are not provided, but likely excluded people with recent severe hypoglycemic events (as most studies do). As a result, most studies do not determine the true protective effect in the most vulnerable high-risk population.
The “2–3 hours of training by investigators and staff” used in the current report likely added to safety—as did watching the training materials online. One wonders how many physician offices will have 2–3 h to train prospective patients/families, and if family members will take the time to view the online training? This is a concern with most research projects in comparison with real-world use.
In summary, the first question relating to safety of the PLGS system in this population would seem to be answered favorably. Although there is no comment about episodes of severe hypoglycemia or of ketoacidosis in the current article, it is presumed that they did not occur, as only four minor adverse events were reported. There have likewise been no severe hypoglycemia or ketoacidosis episodes in the referenced previous PLGS studies of select populations (see below Refs. 8 –10 ).
The second question, relating to the effectiveness of the PLGS system in relation to CGM use alone, or to use of the LGS system alone, cannot be answered from this report. Effectiveness is best evaluated by comparing the duration of time spent below a given hypoglycemic threshold (e.g., 60 mg/dL or 3.3 mmol/L) in comparison with a randomized control period when the system was not in use, and this was not done.
Among the three previous reports referenced by the authors, 8 –10 the study of Danne et al. 8 evaluated in silico modeling of PLGS as well as an exercise stimulus to evaluate the clinical success of the PLGS system. There was no control group and subjects having a severe hypoglycemic event in the previous 3 months were excluded. The study was a daytime study with no report of subsequent nocturnal hypoglycemia. In the clinical trial, the hypoglycemic threshold was reached in 16 of the 23 subjects and hypoglycemia was prevented in 13 of the 16 subjects. From their in silico modeling and the daytime data on 16 subjects, the PLGS system would seem effective.
In the reference to Buckingham et al. 9 using a unique PLGS algorithm, and in the groups more recent publication, 11 1,912 nights were randomized in the home setting in subjects 15–45 years of age. Overnight hypoglycemia (<60 mg/dL [<3.2 mmol/L]) occurred in 322 of the 970 control nights (33%, an occurrence similar to the U.S. national JDRF trial 12 ). In contrast, during the randomized nights of using a PLGS algorithm, hypoglycemia occurred during 196 of 942 nights (21%; P < 0.001). Hypoglycemia lasting >2 h (the most dangerous 13 ) was reduced by 74% with use of the PLGS system. The study clearly showed the benefit of the PLGS algorithm in the home setting.
The third reference 10 related to PLGS provided in the article is an abstract describing 10 patients with type 1 diabetes who were randomized to control or to study nights of PLGS use, both with their basal insulin rates increased by 180%. As in this study, and in the study of Danne et al., 8 the Medtronic PLGS system was evaluated. During control nights, 9 of the 10 participants had glucose levels <2.8 mmol/L (<50 mg/dL). In contrast, subjects reached this nadir in only 2 of the 10 nights in which the PLGS system was used. The investigators concluded that “the predictive algorithm in the Medtronic MiniMed™ 640G has potential to reduce overnight hypoglycemia exposure in patients on insulin pump therapy.”
A more recent abstract (presented at the Advanced Technologies and Treatment for Diabetes in Milan 14 ) used the MiniMed 640G insulin pump system and described 69 subjects whose daytime basal insulin rates were gradually increased to induce hypoglycemia. The PLGS system was activated in 68 cases, resulting in a 60.2% success rate (41 cases) in preventing hypoglycemia. Hypoglycemia was not avoided in the remaining 27 cases. There were no severe adverse events.
In summary, the PLGS algorithm has been shown effective to date in only one large randomized home trial. The PLGS algorithm clearly adds both safety and efficacy in the prevention of hypoglycemia. It is important that future studies focus on the vulnerable populations at high risk for severe hypoglycemia, including patients with recent episodes of severe hypoglycemia, those with hypoglycemia unawareness, and in the very young and elderly with type 1 diabetes.
Footnotes
Author Disclosure Statement
No competing financial interests exist.
