Investigators fashioned a zone-model predictive controller to evaluate adjustment of closed-loop glycemic control during pregnancy, as both glycemic control and insulin adjustment continually change throughout gestation.
Investigators have shown that a model of closed-loop control (CLC) for type 1 diabetes (T1D) resulting in pregnancy complications may be a potential new tool for optimizing glycemic control and insulin adjustment in a pregnant population, according to new research published in Frontiers in Endocrinology.
The Harvard-based investigators fashioned a zone-model predictive controller (zone-MPC) to evaluate adjustment of closed-loop glycemic control during pregnancy, as both glycemic control and insulin adjustment continually change throughout gestation.
“In this paper, we tailor a zone-MPC, an optimization-based control strategy that uses model predictions, for use during pregnancy and verify its robustness in-silico through a broad range of scenarios,” the authors wrote. “The emphasis is on leveraging the flexible design of zone-MPC to obtain a controller that satisfies glycemic outcomes recommended for pregnancy based on clinical insight.”
The current guideline-directed pregnancy glucose target range is 63 to 140 mg/dL (vs 70 to 80 mg/dL for nonpregnant persons), according to the authors, but for their study they lowered this to a daytime range of 80 to 110 mg/dL and an overnight range of 80 to 100 mg/dL. Additional customizations for their zone-MPC were a more assertive correction bolus in instances of hyperglycemia and more aggressive postprandial insulin delivery via a control strategy.
Following evaluation and implementation of their zone-MPC among 10 study subjects and 13 scenarios (from ideal metabolic/treatment parameters to high-risk cases), each comprising 3 daily meals and 40 grams of carbohydrates, positive results were seen for both time in pregnancy target range and time above the target range.
There was a mean (SD) 10.3% (5.3%) increase seen for the time in pregnancy target range (P < .001). At baseline, the mean measure using the zone-MPC was 70.6% (15.0%), and this rose to 80.8% (11.3%) during pregnancy.
For time above the target range, there was a 10.7% (4.8%) overall reduction (P < .001). Whereas the baseline zone-MPC showed a measure of 29.0% (15.4%), the pregnancy-specific zone MPC was 18.3% (12.0%). Consensus guidelines recommend time above range to come in below 25%.
Time below range did not change significantly (P = .1), the authors highlighted. The mean baseline zone-MPC was 0.5% (1.2%), rising to 3.5% (1.9%) as shown via pregnancy-specific zone-MPC. Guidelines advise time below range to come in below 4%.
The investigators’ primary outcome was “glucose profiles that satisfy clinical requirements across a comprehensive set of scenarios under which the system may operate,” and their zone-MPC aimed to accomplish this by helping to stabilize glucose levels within a target range through optimization of insulin injections levels using model predictions. Tighter glucose control is recommended for pregnant women with diabetes, they added.
Limitations on their findings include that glucose-insulin-meal metabolism changes are not yet be precisely defined due to a lack of pregnancy-related T1D mathematical models and that the scenarios they utilized did not cover diurnal sensitivity changes, the influence of other insulin- related metabolism changes during pregnancy, and body weight.
“Future research that focuses on modeling the glucose-insulin metabolism during pregnancy could facilitate building simulation platforms tailored to this cohort, which would facilitate the development of optimal insulin treatment strategies and systems for this cohort,” they concluded. “As the use of CLC systems becomes more prevalent, understanding how these systems can be customized to the needs of specific sub-populations will be critical to extend the reach and ensuring satisfactory performance.”
Ozaslan B, Deshpande S, Doyle FJ III, Dassau E. Zone-MPC automated insulin delivery algorithm tuned for pregnancy complicated by type 1 diabetes. Front Endocrinol (Lausanne). Published online March 22, 2022. doi:10.3389/fendo.2021.768639