Glycemic Control System Correlating Glucose and HbA1C
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Solution Overview
Problem
Current glucose monitoring systems for diabetes management lack efficient methods to correlate continuous glucose monitoring data with HbA1C levels, leading to inadequate glycemic control and increased risk of hypoglycemic complications.
Innovation Solution
A system that receives mean glucose value information over a predetermined period, correlates it with the patient's HbA1C level, and determines a target HbA1C level to optimize glycemic control by using continuous analyte monitoring systems with analyte sensors positioned beneath the skin and data processing units for real-time glucose monitoring and therapy management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous glucose monitoring data is collected over extended periods, then glycemic control accuracy is improved, but the complexity of correlating with HbA1C levels increases
Solution Approach 1:
The patent introduces a correlation coefficient as an intermediary parameter that quantifies the relationship between continuous glucose monitoring data and HbA1C levels. This mediator enables the system to bridge the gap between short-term glucose measurements and long-term glycemic control assessment, resolving the complexity of directly correlating these different time-scale data sets.
Solution Approach 2:
The system dynamically adjusts the correlation threshold parameter based on individual patient characteristics and clinical context. By making the threshold a variable parameter rather than a fixed value, the system adapts to different patient populations and clinical scenarios, improving glycemic control accuracy while managing data correlation complexity.
2Productivity
If HbA1C target levels are determined based on correlation analysis, then therapy management is optimized, but the time required for analysis increases
Solution Approach 1:
The system performs preliminary correlation analysis during routine glucose monitoring periods, building a database of relationship patterns between continuous glucose data and HbA1C levels before clinical decisions are needed. This advance preparation allows for rapid determination of personalized HbA1C target levels when therapy management decisions are required, reducing analysis time while maintaining optimization benefits.
Solution Approach 2:
The system implements continuous feedback loops where correlation analysis results from previous monitoring periods inform subsequent therapy adjustments and target setting. This feedback mechanism enables the system to learn from accumulated data, progressively reducing analysis time while improving therapy management efficiency through increasingly accurate predictive models.
Data Source
AI summary
Methods to provide glycemic control and therapy management based on monitored glucose data, and current and/or target HbA1C levels are provided. Systems to provide glycemic control and therapy management based on monitored glucose data, and current and/or target HbA1C levels are provided. Kits to provide glycemic control and therapy management based on monitored glucose data, and current and/or target HbA1C levels are provided.