Adaptive Basal Insulin Titration for Hypoglycemia Risk Reduction
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Solution Overview
Problem
Current insulin titration systems rely on fixed targets set by healthcare practitioners, which do not account for changes in physiological parameters or adherence, leading to potential overdosing and hypoglycemic events due to forgotten injections or inaccurate glucose measurements.
Innovation Solution
A titrator with a variable target fasting blood glucose level, adjusted based on glucose and insulin data, including total glucose level variability, fasting glucose variance, minimum glucose values, insulin sensitivity, and adherence to the insulin regimen, to autonomously adjust long-acting insulin dosages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed target fasting blood glucose level is used for insulin titration, then the titration process is simple and easy to implement, but it leads to hypoglycemic events when patients miss injections or have inaccurate glucose measurements
Solution Approach 1:
The patent implements dynamic target glucose levels that automatically adjust based on adherence metrics and glucose variability. Instead of a fixed target, the system calculates adaptive targets that rise when adherence is poor or variability is high, and fall when adherence is good and variability is low. This dynamic adjustment prevents hypoglycemia while maintaining simplicity for the user.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor adherence data and glucose measurements, then adjust the target glucose level accordingly. The feedback mechanism uses adherence thresholds and variability metrics to automatically modify treatment targets, creating a closed-loop control system that responds to patient behavior and physiological responses.
2Reliability
If the target glucose level is adjusted dynamically based on multiple parameters, then the reliability and safety of insulin titration is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The patent changes the parameters used for titration from a single fixed target to multiple dynamic parameters including adherence metrics, glucose variability measures, and adaptive target levels. The system monitors adherence thresholds and variability thresholds, then adjusts the target glucose parameter accordingly. This approach maintains safety while using computationally manageable parameter changes.
Solution Approach 2:
The system segments the titration process into distinct phases: an initial phase with higher targets for patients with poor adherence or high variability, and a subsequent phase with lower targets for patients with good adherence and low variability. This segmentation allows complex adaptive logic to be implemented through manageable阶段性 protocols.
3Adaptability or versatility
If traditional fixed target titration is used, then treatment adherence monitoring is not required, but adherence to the insulin regimen directly impacts glucose control and safety
Solution Approach 1:
The system implements self-service adherence monitoring where the titration algorithm automatically detects and responds to adherence patterns. The system monitors whether patients are taking their insulin as prescribed and automatically adjusts targets based on this information, eliminating the need for manual adherence assessment by healthcare providers.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor adherence data and glucose measurements, then adjust the target glucose level accordingly. The feedback mechanism uses adherence thresholds and variability metrics to automatically modify treatment targets, creating a closed-loop control system that responds to patient behavior and physiological responses.
Data Source
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AI summary
Systems and methods are provided for adjusting long acting insulin medicament dosages for a subject. A plurality of timestamped glucose measurements of the subject and insulin injection data is obtained. A first glycaemic risk measures is determined, where the first risk glycaemic risk measure is i) glucose level variability across the glucose measurements, (ii) a variability in fasting glucose levels calculated from the glucose measurements, (iii) a minimum observed glucose measurement in the plurality of glucose measurements (iv) rate of change in ISF, or (v) adherence values. A fasting blood glucose target function is computed based upon at least the first glycaemic risk measure thereby obtaining an updated target fasting blood glucose level that is between a minimum and maximum target fasting blood glucose level. The long acting insulin medicament dosage is adjusted based upon the updated target fasting blood glucose level.