Method, system and computer program product for CGM-based prevention of hypoglycemia via hypoglycemia risk assessment and smooth reduction insulin delivery
An aspect of an embodiment or partial embodiment of the present invention (or combinations of various embodiments in whole or in part of the present invention) comprises, but not limited thereto, a method end system (and related computer program product) for continually assessing the risk of hypoglycemia for a patient and then determining what action to take based on that risk assessment. A further embodiment results in two outputs: (1) an attenuation factor to be applied to the insulin rate command sent to the pump (either via conventional therapy or via open or closed loop control) and/or (2) a red/yellow/green light hypoglycemia alarm providing to the patient an indication of the risk of hypoglycemia. The two outputs of the CPHS can be used in combination or individually.
1. A computer-implemented method for preventing or mitigating hypoglycemia in a patient, the method comprising:
determining, by a glucose meter, blood glucose concentration by continuously making direct metabolic measurements using a non-invasive technique;
continuously assessing, by a processor, a risk of hypoglycemia based on at least the blood glucose concentration, the processor being configured to communicate with the glucose meter;
evaluating, by the processor or another processor which is different from the processor, risk of hypoglycemia based on the assessed risk of hypoglycemia, the another processor being configured to communicate with the processor; and
outputting, by the processor or the another processor, to an output device a result of said evaluation.
2. The method of claim 1 , wherein the determining of the blood glucose concentration comprises:
using a near-infrared radiation (IR) diffuse-reflection laser spectroscopy.
3. The method of claim 1 , wherein the determining of the blood glucose concentration comprises:
facilitating transdermal movement of glucose along a concentration gradient by using a permeability enhancer.
4. The method of claim 3 , wherein the permeability enhancer includes at least one of a sodium cholate, sodium glycocholate, sodium glycodeoxycholate, taurodeoxycholate, sodium deoxycholate, sodium lauryl sulfate, salt, natural bile salt, derivatives of saturated and unsaturated fatty acids, surfactants, bile salt analogs, derivatives of bile salts, or synthetic permeation enhancers.
5. The method of claim 1 , wherein the determining of the blood glucose concentration comprises:
collecting perspiration through a skin patch.
6. The method of claim 5 , comprising:
stimulating a secretion associated with the perspiration using a cholinergic agent from the eccrine sweat gland.
7. The method of claim 1 , wherein the determining of the blood glucose concentration comprises:
sampling a substance through skin into a receptacle on a surface of the skin using iontophoresis.
8. The method of claim 7 , comprising:
coupling the sampling with a glucose-specific biosensor or glucose-specific electrodes to monitor blood glucose.
9. The method of claim 7 , wherein the iontophoresis comprises:
moving an analyte into a collection reservoir; and
detecting the analyte in the collection reservoir using a biosensor.
10. The method of claim 1 , wherein the assessing of the risk of hypoglycemia is based on the blood glucose concentration and data obtained from the patient's insulin pump.
11. The method of claim 1 , wherein the assessing of the risk of hypoglycemia is based on the blood glucose concentration and at least one of meal information, physical activity, or a heart rate.
12. The method of claim 11 , wherein the physical activity causes variable insulin sensitivity.
13. The method of claim 1 , wherein the result is selected from one of:
a) no action being needed;
b) attenuation of insulin delivery being needed;
c) additional patient intervention being needed; and
d) attenuation of insulin delivery and additional patent intervention being needed.
14. The method of claim 13 , wherein the attenuation or intervention, or both, are in part determined using a model predictive control.
15. The method of claim 13 , wherein the attenuation or intervention, or both, are in part determined using a proportional-integral-derivative (PID) control.
16. The method of claim 13 , wherein the attenuation or intervention, or both, are in part determined using a neural network.