Prospective External Validation of an Algorithm Predicting Hourly Basal Insulin Infusion Rates from Characteristics of Patients with Type 1 Diabetes Treated with Insulin Pumps

Abstract

Background We previously published an algorithm predicting 24 h basal insulin infusion profiles in insulin pump-treated subjects with type 1 diabetes profiles from six subject characteristics. This algorithm was to be externally validated in an independent environment and patient population.

Methods Thirty-two patients with pump-treated type diabetes were switched to their individually algorithm-derived basal insulin infusion profile, and the appropriateness of fasting glycemic control was scrutinized by means of a supervised 24 h fast. Primary endpoint was appropriate fasting glycemic control according to pre-defined criteria in at least 80% of the cohort.

Results In 24 out of 32 patients switching to the algorithm-derived basal insulin infusion rate and undergoing a 24-h fasting period, appropriate glycemic control was achieved (=75%, lower than the pre-defined threshold of 80%), two patients discontinued the fast due to hyperglycemia, and six finished the fasting period, however, with inappropriate fasting glycemic control (entirely due to hyperglycemic episodes). There were no obvious differences in baseline characteristics between those with appropriate vs. inappropriate fasting glycemic control on the basal insulin infusion rate provided by the algorithm.

Conclusion In conclusion, when testing fasting glycemic control with an algorithm-derived individual basal insulin infusion profile during a 24 h fasting period in a cohort unrelated in terms of the hospital environment and catchment area, the success rate was lower than a pre-defined threshold for concluding utility of this algorithm. Therefore, applying this algorithm in order to initiate or optimize basal insulin infusion profiles in type 1 diabetes cannot be generally recommended.

Key words

type 1 diabetes - insulin pump (CSII: Continuous subcutaneous insulin infusion) - basal rate profiles - dawn phenomenon - dusk phenomenon

Publikationsverlauf

Eingereicht: 04. März 2023
Eingereicht: 13. Juni 2023

Angenommen: 20. Juni 2023

Artikel online veröffentlicht:
20. Juli 2023

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