ArticleJournal of diabetes science and technology2012
Importance of blood glucose meter and carbohydrate estimation accuracy.
Article in Journal of diabetes science and technology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Mitigating iftar-related glycemic excursions in adolescents and young adults with type 1 diabetes on MiniMed™ 780G advanced hybrid closed loop system: a randomized clinical trial for adjunctive oral vildagliptin therapy during Ramadan fasting.Diabetology & metabolic syndrome · 2023Article
- Impact of Carbohydrate Counting Error on Glycemic Control in Open-Loop Management of Type 1 Diabetes: Quantitative Assessment Through an In Silico Trial.Journal of diabetes science and technology · 2022Article
- Do We Need the Replacement of YSI 2300? A View from the Clinical Laboratory.Journal of diabetes science and technology · 2022Article
- Modeling Carbohydrate Counting Error in Type 1 Diabetes Management.Diabetes technology & therapeutics · 2020Article
- User Performance Evaluation of Four Blood Glucose Monitoring Systems Applying ISO 15197:2013 Accuracy Criteria and Calculation of Insulin Dosing Errors.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2018Article
- Bolus Insulin Dose Error Distributions Based on Results From Two Clinical Trials Comparing Blood Glucose Monitoring Systems.Journal of diabetes science and technology · 2017Article
- A Model of Self-Monitoring Blood Glucose Measurement Error.Journal of diabetes science and technology · 2017Article
- Analytical Performance Evaluation of Infopia Element™ Auto-coding Blood Glucose Monitoring System for Self-Monitoring of Blood Glucose.Journal of clinical laboratory analysis · 2016Article
- Performance Evaluation of Three Blood Glucose Monitoring Systems Using ISO 15197: 2013 Accuracy Criteria, Consensus and Surveillance Error Grid Analyses, and Insulin Dosing Error Modeling in a Hospital Setting.Journal of diabetes science and technology · 2015Article
- How Should Blood Glucose Meter System Analytical Performance Be Assessed?Journal of diabetes science and technology · 2015Article
- Performance of Cleared Blood Glucose Monitors.Journal of diabetes science and technology · 2015Review
- Analysis: New point-of-care blood glucose monitoring system for the hospital demonstrates satisfactory analytical accuracy using blood from critically ill patients--an important step toward improved blood glucose control in the hospital.Journal of diabetes science and technology · 2013Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe clinical significance of blood glucose meter (BGM) error in the presence of increasing carbohydrate errors in diabetes patients who use both the BGM result and the carbohydrate estimation to dose insulin is unknown.
methodsThis Monte Carlo simulation modeled diabetes patients who calculate insulin dosages based on BGM results and carbohydrate estimations. It evaluated the likelihood of on-target insulin dosing and clinically significant insulin dose errors based on data from five BGMs with different levels of performance (expressed as bias and imprecision [coefficient of variation (%CV)]) and increasing levels of carbohydrate estimation errors. The study was performed across three separate preprandial glucose (PPG) ranges (90-150, 150-270, and 270-450 mg/dl).
resultsWhen carbohydrate estimation is accurate (%CV = 0%), the likelihood for on-target insulin doses ranged 50.1-98.5%. The likelihood depended on BGM performance and PPG range. In the presence of carbohydrate estimation errors (%CV = 5-20%), the likelihood of on-target insulin dosages markedly decreased (range, 27.2-80.1%) for all BGMs, the likelihood of insulin underdosing (range, 0-12.8%) and overdosing (range, 0-32.3%) increased, and the influence of BGM error on insulin dosing accuracy was blunted. Even in the presence of carbohydrate error, the BGM with the best performance (bias 1.35% and %CV = 4.84) had the highest probability for on-target insulin dosages.
conclusionsBoth BGM and carbohydrate estimation error contribute to insulin dosing inaccuracies. The BGM with the best performance was associated with the most on-target insulin dosages.
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