Empiric validation of simulation models for estimating glucose meter performance criteria for moderate levels of glycemic control

Brad S. Karon, James C. Boyd, George G. Klee

Research output: Contribution to journalArticle

14 Scopus citations


Background: We used simulation modeling to relate glucose meter performance criteria to insulin dosing errors for patients on a moderate glycemic control protocol (glucose target, 110-150 mg/dL) and empirically validated assumptions from simulation models using observed glucose meter and laboratory glucose values obtained nearly simultaneously. Subjects and Methods: The 25,948 glucose values from 1,513 patients on a moderate glycemic control protocol were used to represent the expected distribution of glucose values in this patient population. Simulation models were used to relate glucose meter analytical performance to insulin dosing errors assuming 10%, 15%, or 20% total allowable error (TEa). In addition, 4,017 paired glucose meter and serum laboratory glucose measurements drawn within 5 min of each other were used to generate an empiric dataset to validate simulation model assumptions relating glucose meter performance to insulin dosing errors. Results: Large (three or more category) insulin dosing errors are predicted to occur only under the 20% TEa condition. Two category insulin dosing errors were common (6-20% of all insulin dosing decisions) when 20% TEa was assumed, but frequency decreased to only 0.2% of dosing decisions when 10% TEa was modeled. When insulin dosing error rates were measured empirically by comparing paired glucose meter and laboratory glucose values, insulin dosing error rates were very similar to those predicted for the 20% TEa condition. Conclusions: Both simulation models and empiric data demonstrate that glucose meters that perform at ≥20% TEa allow large insulin dosing errors during a moderate glycemic control protocol.

Original languageEnglish (US)
Pages (from-to)996-1003
Number of pages8
JournalDiabetes Technology and Therapeutics
Issue number12
StatePublished - Dec 1 2013


ASJC Scopus subject areas

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

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