Computer-Based versus Paper-Based Insulin Infusion Algorithms in Diabetic Ketoacidosis

Author(s): Moustafa Younis*, John Pham, Hussein Asad, Majdi S. Hamarshi

Journal Name: Current Diabetes Reviews

Volume 16 , Issue 6 , 2020

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Abstract:

Background: Paper-based and computer-based insulin infusion algorithms facilitate appropriate glycemic therapy. The data comparing these algorithms in the management of diabetic ketoacidosis in the intensive care unit (ICU) setting are limited. We aimed to determine the differences in time to diabetic ketoacidosis resolution and incidence of hypoglycemia between computer and paper-based insulin infusion.

Methods: Single-institution retrospective review of patients admitted to the ICU with diabetic ketoacidosis between 4/1/2015 and 7/20/2018. Our institution introduced computer-based insulin infusion (Glucommander) to the intensive care unit on 3/28/2016. Patients were grouped into either paper-based group (preintervention) or a computer-based group (postintervention). Summary and univariate analyses were performed.

Results: A total of 620 patients (paper-based=247; computer-based=373) with a median (IQR) age of 40 (26-56) years were included; 46% were male. Patients in the computer-based group were significantly older (p=0.003); otherwise, there were no significant differences in gender, race, body mass index and HbA1c. The mean (±SD) time to diabetic ketoacidosis resolution in the computer-based group was significantly lower than the paper-based group (p=0.02). The number of patients in the paper-based group who developed severe hypoglycemia (<50 mg/dl) was significantly higher {8% vs 1%; p<0.0001}.

Conclusion: Our analyses demonstrate statistically significant decreases in time to DKA resolution and hypoglycemic events in DKA patients who were managed using a computer-based insulin infusion algorithm providing a more effective and safer option when compared to paper-based insulin infusion.

Keywords: Diabetic ketoacidosis, insulin, glucommander, hypoglycemia, algorithm, diabetes.

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Article Details

VOLUME: 16
ISSUE: 6
Year: 2020
Page: [628 - 634]
Pages: 7
DOI: 10.2174/1573399815666190712191932
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