Systems and methods for managing glycemic variability

Abstract

Methods and apparatus, including computer program products, are provided for processing analyte data. In some example implementations, a method may include generating glucose sensor data indicative of a host's glucose concentration using a glucose sensor; calculating a glycemic variability index (GVI) value based on the glucose sensor data; and providing output to a user responsive to the calculated glycemic variability index value. The GVI may be a ratio of a length of a line representative of the sensor data and an ideal length of the line. Related systems, methods, and articles of manufacture are also disclosed.

What is claimed is: 
     
         1 . A computer-implemented method comprising:
 generating glucose sensor data indicative of a host's glucose concentration using a glucose sensor;   calculating a glycemic variability index value based on the glucose sensor data; and   providing output to a user responsive to the calculated glycemic variability index value.   
     
     
         2 . The method of  claim 1 , wherein the glycemic variability index (GVI) is defined as equal to L/L o , wherein L is a length of a line representative of the host's glucose concentration over a period of time and L o  is an ideal line length for the given period of time. 
     
     
         3 . The method of  claim 1 , further comprising calculating a patient glycemic status, wherein patient glycemic status (PGS) is defined as equal to GVI*MG*(1−PTIR)+Penalty, wherein MG is a mean glucose value of the sensor data, PTIR is a percentage of time the sensor data is within a predefined range of glucose concentration values, and the Penalty is a non-linear hyperbolic function that asymptotes with a predetermined number of determined episodes of severe hypoglycemia within a predetermined amount of time. 
     
     
         4 . The method of  claim 3 , wherein the predefined range of glucose concentration values is from about 80 mg/dL to about 180 mg/dL. 
     
     
         5 . The method of  claim 2 , wherein the providing output is responsive to the GVI calculation and the PSG calculation. 
     
     
         6 . The method of  claim 1 , wherein the providing output comprises generating a report to a user, wherein the report includes a calculated GVI numerical value. 
     
     
         7 . The method of  claim 1 , wherein the providing output comprises triggering an alert to a user when the GVI exceeds a predetermined threshold, wherein the alert is one or more of an audible alert, visual alert and tactile alert. 
     
     
         8 . The method of  claim 1 , wherein the calculating is automatically performed periodically on a defined window of time of sensor data. 
     
     
         9 . The method of  claim 1 , wherein the calculating comprising calculating a plurality of GVI values based on the sensor data, wherein each of the GVI values is based on a different period of time of the sensor data. 
     
     
         10 . The method of  claim 1 , wherein the method is performed by a processor executing code embodied in a non-transitory computer-readable medium. 
     
     
         11 . A non-transitory computer-readable medium including code which when executed by at least one processor provides operations comprises:
 providing a scoring map that converts glucose values to a clinical relevance score;   converting glucose values generated using a continuous glucose sensor from units of glucose concentration to clinical relevance scores using the scoring map;   applying a statistical algorithm to the clinical relevance scores to generate a processed clinical relevance score; and   outputting information based on the processed clinical relevance score to a user interface of an electronic device.   
     
     
         12 . The non-transitory computer-readable medium of  claim 11 , wherein the scoring map is embodied as one or more mathematical equations. 
     
     
         13 . The non-transitory computer-readable medium of  claim 11 , wherein the scoring map comprises an above target coordinate space and a below target coordinate space. 
     
     
         14 . The non-transitory computer-readable medium of  claim 11 , wherein a scale of the clinical relevance score is linear and a scale of the glucose concentration is non-linear. 
     
     
         15 . The non-transitory computer-readable medium of  claim 11 , wherein the statistical algorithm comprises one or more of a sum, mean, average and standard deviation of the clinical relevance scores. 
     
     
         16 . The non-transitory computer-readable medium of  claim 11 , wherein the outputted information comprises one or more of a numerical clinical relevance score and a graph of the clinical relevance scores over time. 
     
     
         17 . A system comprising:
 at least one processor;   at least one memory including code which when executed by the at least one processor provides operations comprising
 analyzing glucose data generated by a continuous glucose sensor over a time period, 
 identifying an event based on the analyzing, and 
 outputting information to a user via a user interface of the system, the information based on the identified event. 
   
     
     
         18 . The system of  claim 17 , wherein the event is a missed meal event, and wherein the information includes a prompt for a user to enter meal information. 
     
     
         19 . The system of  claim 17 , wherein the event is a missed insulin administration event, and wherein the identifying includes monitoring whether a rate of change of the host's measured glucose levels exceeds a threshold for a predetermined period of time. 
     
     
         20 . The system of  claim 17 , wherein the information comprises an indication of glucose control associated with the wear of an insulin infusion pump. 
     
     
         21 . The system of  claim 17 , wherein the information comprises a message indicating a percentage of measured glucose values falling within a target range over a predetermined time period.