What question did this study set out to answer?

The aim is to assess the systemic bias in carbohydrate-to-insulin ratio estimates using continuous glucose data for diabetes management.

February 8, 2026Open Access

Assessment of Carbohydrate-to-Insulin Ratio by Comparing Retrospective Carbohydrate Estimation Using Continuous Glucose Monitoring with Preprandial Carbohydrate Counting

Key Points

The aim is to assess the systemic bias in carbohydrate-to-insulin ratio estimates using continuous glucose data for diabetes management.
Retrospective analysis of blood glucose levels using continuous glucose monitoring data.
Development of equation to estimate carbohydrate using pre- and postprandial glucose levels.
Comparison of retrospective estimates to patient-measured preprandial carbohydrate estimates.
Focus on data with minimal differences in pre- and postprandial glucose levels.
Statistical assessments of carbohydrate-to-insulin ratios were conducted at 7 and 10 months post-diagnosis.
Significant systemic bias was identified, indicating inappropriate current carbohydrate-to-insulin ratios.
Novel method supports better clinical decision-making for carbohydrate counting in diabetes management.

Abstract

Introduction: With the advent and increasing availability of continuous glucose monitoring (CGM), patients are now able to more easily and frequently determine their blood glucose levels than they would have using the finger prick blood test. Health care professionals can also review the patient’s prandial glucose profiles stored in the CGM system without intentional checking of glucose levels. However, given the large amount of data stored, methods for the utilization of such information need to be developed for better diabetes management. Methods: This study shows the retrospective estimation of carbohydrate amount using pre- and postprandial blood glucose levels via the following derived equation: (patient’s current carbohydrate-to-insulin ratio) × injected bolus insulin + (postprandial blood glucose − preprandial blood glucose)/correction factor. Accordingly, the retrospective estimates are systemically biased when the carbohydrate-to-insulin ratio (CIR) is not set appropriately. Insufficient adjustment of the correction factor (CF) also results in retrospective estimation bias for meals with large differences in pre- and postprandial blood glucose levels. We compared these retrospective estimates with patient-measured preprandial carbohydrate estimates to assess the bias. By using only meal data with small differences in pre- and postprandial blood glucose levels, the influence of CF on the bias was limited, and only the systemic bias caused by CIR was assessed. In the presence of a statistically significant systemic bias, the data suggest that the current CIR is set inappropriately. Results: We present the method by assessing CIR in a patient with newly diagnosed type 1 diabetes. CIR parameter assessments at 7 and 10 months from diagnosis are presented. Conclusion: A novel method for statistically assessing CIR was introduced. This method can support clinical decision-making when adjusting CIR for patients with insulin-dependent diabetes who engage in carbohydrate counting.

Assessment of Carbohydrate-to-Insulin Ratio by Comparing Retrospective Carbohydrate Estimation Using Continuous Glucose Monitoring with Preprandial Carbohydrate Counting

Key Points

Abstract

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