Novel Inpatient Automated Self-Adjusting Subcutaneous Insulin Algorithm: 3-Year Experience. An Observational Study

Area of Science:

• Inpatient glycemic management
• Medical device technology
• Electronic Medical Record (EMR) integration

Background:

• Managing blood glucose in hospitalized patients who are nil per os (NPO), on enteral tube feeds (TF), or total parenteral nutrition (TPN) is complex.
• Conventional insulin treatment (CI) often struggles to maintain optimal glycemic control in these patient populations.

Purpose of the Study:

• To evaluate the efficacy of a novel automated self-adjusting subcutaneous rapid acting insulin algorithm (SQIA) for inpatient hyperglycemia management.
• To compare glucose control outcomes between SQIA and CI in NPO, TF, or TPN patients.

Main Methods:

• Retrospective cohort study utilizing EMR data from September 2020 to September 2023.
• Compared point-of-care (POC) glucose measurements in adult inpatients on SQIA versus CI.
• Analyzed proportions of POC glucose levels in hypoglycemic, in-range, and hyperglycemic categories (q4 hour intervals).

Main Results:

• The SQIA group demonstrated significantly lower proportions of hypoglycemic (0.65% vs. 1.10%) and severely hyperglycemic (5.40% vs. 6.65%) glucose values compared to the CI group.
• SQIA showed particular benefit in reducing severe hyperglycemia in patients receiving glucocorticoids, especially at high doses (-11.1%).
• The study analyzed 5,031 intervals across 4310 hospitalizations.

Conclusions:

• Automated SQIA significantly improves glycemic control in hospitalized patients unable to eat, drink, or take oral medications.
• SQIA reduces the risk of both hypoglycemia and severe hyperglycemia compared to conventional insulin orders.
• This technology offers a promising advancement in managing challenging inpatient glycemic control scenarios.