Insulin optimization systems and testing methods with adjusted exit criterion accounting for system noise associated with biomarkers
First Claim
1. A testing method for optimizing a therapy to a diabetic patient via a device comprising a processor, the testing method comprising the steps of:
- querying a diabetic patient via the device to confirm that entry criteria have been satisfied;
collecting at least one sampling set of biomarker data if entry criteria have been satisfied, wherein each sampling set comprises one or more sampling instances recorded over a collection period and each sampling instance comprises one or more biomarker readings;
evaluating whether the collection of the sampling set satisfies adherence criteria;
computing a probability distribution function, a hazard function, a risk function, and a risk value for the sampling set of biomarker data wherein,the probability distribution function is calculated to approximate the probability distribution of the biomarker data,the hazard function is a function which yields higher hazard values for biomarker readings in the sampling set indicative of higher risk of complications, wherein the hazard function H(B) is defined by the equation H(B)=Hhypo(B)+Hhyper(B), wherein B is a biomarker reading in the sampling set, Hhypo(B) is the hazard function associated with hypoglycemic events, Hhyper(B) is the hazard function associated with hyperglycemic events,the risk function is the product of the probability distribution function and the hazard function, andthe risk value J is calculated by the integral of the risk function
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Abstract
Embodiments of a testing method for optimizing a therapy to a diabetic patient comprise collecting at least one sampling set of biomarker data, computing a probability distribution function, a hazard function, a risk function, and a risk value for the sampling set of biomarker data wherein, wherein the probability distribution function is calculated to approximate the probability distribution of the biomarker data, the hazard function is a function which yields higher hazard values for biomarker readings in the sampling set indicative of higher risk of complications, the risk function is the product of the probability distribution function and the hazard function, and the risk value is calculated by the integral of the risk function, minimizing the risk value by adjusting the diabetic patient'"'"'s therapy, and exiting the testing method when the risk value for at least one sampling set is minimized to an optimal risk level.
165 Citations
61 Claims
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1. A testing method for optimizing a therapy to a diabetic patient via a device comprising a processor, the testing method comprising the steps of:
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querying a diabetic patient via the device to confirm that entry criteria have been satisfied; collecting at least one sampling set of biomarker data if entry criteria have been satisfied, wherein each sampling set comprises one or more sampling instances recorded over a collection period and each sampling instance comprises one or more biomarker readings; evaluating whether the collection of the sampling set satisfies adherence criteria; computing a probability distribution function, a hazard function, a risk function, and a risk value for the sampling set of biomarker data wherein, the probability distribution function is calculated to approximate the probability distribution of the biomarker data, the hazard function is a function which yields higher hazard values for biomarker readings in the sampling set indicative of higher risk of complications, wherein the hazard function H(B) is defined by the equation H(B)=Hhypo(B)+Hhyper(B), wherein B is a biomarker reading in the sampling set, Hhypo(B) is the hazard function associated with hypoglycemic events, Hhyper(B) is the hazard function associated with hyperglycemic events, the risk function is the product of the probability distribution function and the hazard function, and the risk value J is calculated by the integral of the risk function - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 41, 42)
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33. A device configured to guide a diabetic patient through a testing plan directed to optimizing an administration dosage of insulin, comprising:
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a processor coupled to memory, wherein the memory comprises collection procedures; and software having instructions that when executed by the processor causes the processor to; determine whether entry criteria for the diabetic patient to begin the testing plan have been met; instruct the diabetic patient to collect one or more sampling sets of biomarker data in accordance with the collection procedures, wherein each sampling set comprises one or more sampling instances recorded over a collection period, and each sampling instance comprises one or more biomarker readings; evaluate whether the collection of the sampling set satisfies adherence criteria; and compute a probability distribution function, a hazard function, a risk function, and a risk value for the sampling set of biomarker data wherein, the probability distribution function is calculated to approximate the probability distribution of the biomarker data, the hazard function is a function which yields higher hazard values for biomarker readings in the sampling set indicative of higher risk of complications, wherein the hazard function H(B) is defined by the equation H(B)=Hhypo(B)+Hhyper(B), wherein B is a biomarker reading in the sampling set, Hhypo(B) is the hazard function associated with hypoglycemic events, Hhyper(B) is the hazard function associated with hyperglycemic events, the risk function is the product of the probability distribution function and the hazard function, and the risk value J is calculated by the integral of the risk function - View Dependent Claims (34, 35, 36, 37, 38, 39, 40)
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43. A testing method for optimizing a therapy to a diabetic patient via a device comprising a processor, the testing method comprising the steps of:
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querying a diabetic patient via the device to confirm that entry criteria have been satisfied; collecting at least one sampling set of biomarker data if entry criteria have been satisfied, wherein each sampling set comprises one or more sampling instances recorded over a collection period and each sampling instance comprises one or more biomarker readings; evaluating whether the collection of the sampling set satisfies adherence criteria; computing a probability distribution function, a hazard function, a risk function, and a risk value for the sampling set of biomarker data wherein, the probability distribution function is calculated to approximate the probability distribution of the biomarker data, the hazard function is a function which yields higher hazard values for biomarker readings in the sampling set indicative of higher risk of complications, wherein the hazard function H(B) is defined by the equation H(B)=Hhypo(B)+Hhyper(B), wherein B is a biomarker reading in the sampling set, Hhypo(B) is the hazard function associated with hypoglycemic events, Hhyper(B) is the hazard function associated with hyperglycemic events, wherein - View Dependent Claims (44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56)
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57. A testing method for optimizing a therapy to a diabetic patient via a device comprising a processor, the testing method comprising the steps of:
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querying a diabetic patient via the device to confirm that entry criteria have been satisfied; collecting at least one sampling set of biomarker data if entry criteria have been satisfied, wherein each sampling set comprises one or more sampling instances recorded over a collection period and each sampling instance comprises one or more biomarker readings; evaluating whether the collection of the sampling set satisfies adherence criteria; computing a probability distribution function, a hazard function, a risk function, and a risk value for the sampling set of biomarker data wherein, the probability distribution function is calculated to approximate the probability distribution of the biomarker data, the hazard function is a function which yields higher hazard values for biomarker readings in the sampling set indicative of higher risk of complications, the risk function is the product of the probability distribution function and the hazard function, and the risk value is calculated by the integral of the risk function, minimizing the risk value by adjusting the diabetic patient'"'"'s insulin dosage according to an insulin adjustment regimen, which is determined by comparing the mean of the current completed sampling set to the target biomarker level, the insulin adjustment regimen being defined as the number of insulin dosage adjustments required to achieve a target insulin level and the amount of each adjusted insulin dosage, wherein the target insulin level is the amount required to achieve the target biomarker level, wherein the insulin adjustment regimen is determined by calculating the requisite insulin dosage to achieve the target biomarker level, Dtarget, is calculated by the equation Dtarget=Dk+m·
(Btarget−
Bk), wherein m is the rate of change from a first biomarker reading Bk−
1 to a subsequent second biomarker reading Bk based on the adjustment of insulin from a first dosage Dk−
1 to a subsequent second dosage Dk as defined by the equation - View Dependent Claims (58, 59, 60, 61)
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Specification