Predicting Factors Associated with Hypoglycemia Reduction with Automated Predictive Insulin Suspension in Patients at High Risk of Severe Hypoglycemia: An Analysis from the SMILE Randomized Trial

Aklilu Habteab, Javier Castañeda, Harold De Valk, Pratik Choudhary, Emanuele Bosi, Sandrine Lablanche, Simona De Portu, Julien Da Silva, Linda Vorrink-De Groot, John Shin, Ohad Cohen

Research output: Contribution to journalArticlepeer-review

Abstract

Background: This analysis from the SMILE randomized study was performed to identify predictive factors associated with the greatest reductions in hypoglycemia with the Medtronic MiniMed™ 640G Suspend before low feature in adults with type 1 diabetes at high risk of severe hypoglycemia. Methods: Clinical and treatment-related factors associated with decreased sensor hypoglycemia (SH) were identified in participants from the intervention arm by univariate and multivariate analyses. Results: The reduction in SH events <54 mg/dL (<3.0 mmol/L) in the intervention group was significantly (P < 0.0001) associated with the baseline mean number of sensor hypoglycemic events (MNSHE) <54 mg/dL. When excluding continuous glucose monitoring (CGM) factors not readily available (MNSHE, duration of SH events, area under the curve, mean amplitude of glycemic excursions), only the baseline mean time spent <54 mg/dL was found to be a significant independent predictor factor (P < 0.0001). Baseline HbA1c, mean self-monitoring of blood glucose (SMBG), and coefficient of variation of SMBG were significant, although weak, predictors in the absence of any CGM data. Conclusions: The greatest reductions in SH events achieved with the MiniMed 640G system with the Suspend before low feature were seen in participants with higher baseline MNSHE. Measuring these (usually uncollected) events can be a useful tool to predict hypoglycemia reduction. ClinicalTrials.gov Registration Identifier NCT02733991.

Original languageEnglish
Pages (from-to)681-685
Number of pages5
JournalDiabetes Technology and Therapeutics
Volume22
Issue number9
DOIs
Publication statusPublished - Sep 1 2020

Keywords

  • Diabetes mellitus
  • Hypoglycemia
  • Insulin infusion systems
  • Predictive low glucose management
  • Severe hypoglycemia
  • Type 1

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Endocrinology
  • Medical Laboratory Technology

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