Evaluation and visualization of glycemic dysfunction

Abstract

An amount of glycemic dysfunction associated with mis-timing (e.g., delay) of meal boluses based on replay analysis is determined. The amount of dysfunction of historical or estimated bolusing as compared to an optimally timed bolus based on the replay analysis is quantified and visualized. Inferences may be made about diabetes meal management regarding inputs from a patient.

What is claimed is: 
     
         1 . A system for determining an amount of glycemic dysfunction, the system comprising:
 a data processor that receives continuous glucose monitoring (CGM) and insulin data pertaining to a subject, wherein the insulin data comprises an insulin bolus amount and a timing for the insulin bolus amount;   a replay analyzer that generates a replay analysis using the CGM and insulin data to determine an impact of a previously delivered inefficient or suboptimal bolus;   a quantifier that quantifies an amount of glycemic dysfunction using the replay analysis; and   an output device that provides an output representative of the amount of glycemic dysfunction for use in improving diabetes management.   
     
     
         2 . The system of  claim 1 , wherein a first portion of the CGM and insulin data is estimated and a second portion of the CGM and insulin data is reported. 
     
     
         3 . The system of  claim 1 , wherein the CGM and insulin data comprise at least one of an estimated timing of a meal of the subject or an estimated composition of the meal of the subject. 
     
     
         4 . The system of  claim 1 , wherein the CGM and insulin data comprise misinformation about at least one of a timing of a meal of the subject or a composition of the meal of the subject. 
     
     
         5 . The system of  claim 1 , wherein a portion of the CGM and insulin data is received from a computing device of the subject. 
     
     
         6 . The system of  claim 1 , wherein the CGM and insulin data comprise estimated metabolic states in time series form, a reconciled meal history, and a delivered insulin history. 
     
     
         7 . The system of  claim 1 , wherein the CGM and insulin data comprise estimated metabolic states, reconciled estimated metabolic inputs, and known metabolic inputs. 
     
     
         8 . The system of  claim 1 , wherein the CGM and insulin data is discretized in time. 
     
     
         9 . The system of  claim 1 , wherein the replay analyzer isolates an impact of timing, carbohydrate counting, and carbohydrate ratio of an estimated bolusing with respect to a meal. The system of  claim 1 , wherein the replay analyzer uses replay simulation analysis to assess an impact of numerically optimal boluses at historical bolus times by removing inaccurate carbohydrate counts and inappropriate carbohydrate ratios. 
     
     
         11 . The system of  claim 1 , wherein the replay analyzer assesses an impact of numerically optimal boluses at estimated historical meal times. 
     
     
         12 . The system of  claim 1 , wherein the replay analyzer performs replay simulations at times of historical boluses or at times in advance of estimated meals. 
     
     
         13 . The system of  claim 1 , wherein the replay analyzer performs replay simulations with at least one of historical CGM and insulin data, numerically optimal boluses at historical bolus times, or numerically optimal boluses at estimated meal times. 
     
     
         14 . The system of  claim 1 , wherein the replay analyzer is configured to: generate a set of candidate boluses; simulate future blood glucose (BG) values associated with each candidate bolus; score a simulated BG trajectory for each candidate bolus using a risk analysis; pick and implement the best bolus based on the score of each candidate bolus; and continue to replay simulate until the time of the next bolus. 
     
     
         15 . The system of claim  41 , wherein the risk analysis is a velocity dependent risk analysis. 
     
     
         16 . The system of  claim 1 , wherein the quantifier quantifies the amount of dysfunction of estimated bolusing compared to an optimally timed bolusing. 
     
     
         17 . The system of  claim 1 , wherein the quantifier quantifies the amount of dysfunction of historical bolusing compared to an optimally timed bolusing. 
     
     
         18 . The system of  claim 1 , wherein the quantifier quantifies a compliance of the patient with an ideal pre-meal bolus timing. 
     
     
         19 . The system of  claim 1 , wherein the output comprises at least one of a plot or a visualization. 
     
     
         20 . The system of  claim 1 , wherein the output comprises a risk index comprising at least one of high blood glucose risk, low blood glucose risk, or total glycemic risk. 
     
     
         21 . The system of  claim 1 , wherein the output comprises a number and an extent of excursions into an out-of-range blood glucose level. 
     
     
         22 . The system of  claim 1 , wherein the output shows glycemic dysfunction at historical times. 
     
     
         23 . The system of  claim 1 , wherein the output device provides a visualization showing at least one of a behavioral impact of the glycemic dysfunction, historical CGM and insulin data vs. replay simulated CGM with optimal boluses at historical bolus times, or historical CGM and insulin data vs. replay simulated CGM with optimal boluses at estimated meal times. 
     
     
         24 . The system of  claim 1 , further comprising a compliance engine that is configured to provide a visualization of a compliance of the patient with an ideal pre-meal bolus timing. 
     
     
         25 . The system of  claim 1 , wherein the output device provides meal management information to the subject based on the amount of glycemic dysfunction. 
     
     
         26 . The system of  claim 25 , wherein the meal management information comprises pre-bolus timing information for the patient. 
     
     
         27 . The system of  claim 26 , wherein the pre-bolus timing information comprises a recommendation to the patient regarding bolusing before a type of meal in the future.