Classifications

• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
  • A61M5/00—Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
  • A61M5/14—Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
  • A61M5/168—Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body
  • A61M5/172—Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body electrical or electronic
  • A61M5/1723—Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body electrical or electronic using feedback of body parameters, e.g. blood-sugar, pressure
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
  • A61M2205/00—General characteristics of the apparatus
  • A61M2205/18—General characteristics of the apparatus with alarm
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
  • A61M2205/00—General characteristics of the apparatus
  • A61M2205/50—General characteristics of the apparatus with microprocessors or computers
  • A61M2205/502—User interfaces, e.g. screens or keyboards
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
  • A61M2205/00—General characteristics of the apparatus
  • A61M2205/50—General characteristics of the apparatus with microprocessors or computers
  • A61M2205/52—General characteristics of the apparatus with microprocessors or computers with memories providing a history of measured variating parameters of apparatus or patient
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
  • A61M2230/00—Measuring parameters of the user
  • A61M2230/20—Blood composition characteristics
  • A61M2230/201—Glucose concentration
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
  • A61M5/00—Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
  • A61M5/14—Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
  • A61M5/142—Pressure infusion, e.g. using pumps
  • A61M5/14244—Pressure infusion, e.g. using pumps adapted to be carried by the patient, e.g. portable on the body

Definitions

• the present invention relates to diabetes management, and in particular to adjusting insulin pump parameters using blood glucose information.
• pancreas of a normal healthy person produces and releases insulin into the blood stream in response to elevated blood plasma glucose levels.
• Beta cells which reside in the pancreas, produce and secrete the insulin into the blood stream, as it is needed. If ⁇ -cells become incapacitated or die, a condition known as Type I diabetes mellitus (or in some cases if ⁇ -cells produce insufficient quantities of insulin, Type II diabetes), then insulin must be provided to the body from another source.
• infusion pump therapy has been increasing, especially for delivering insulin for diabetics.
• external infusion pumps are worn on a belt, in a pocket, or the like, and deliver insulin into the body via an infusion tube with a percutaneous needle or a cannula placed in the subcutaneous tissue.
• infusion pump therapy As of 1995, less than 5% of Type I diabetics in the United States were using pump therapy, but presently over 25% of the more than 1.12 million Type I diabetics in the U.S. are using infusion pump therapy.
• the infusion pump has improved the way insulin has been delivered, the infusion pump is limited in its ability to replicate all of the functions of the pancreas. Specifically, the infusion pump is still limited to delivering insulin based on user inputted commands and parameters and therefore there is a need to improve the pump to better simulate a pancreas based on current glucose values.
• the present invention relates to an algorithm and method of automatically making a therapy recommendation for an insulin pump parameter based on current blood glucose values and inputted targeted blood glucose levels.
• the pump parameters include basal rates, carbohydrate-to-insulin ratios (CIR), and insulin sensitivity factors (ISF).
• CIR carbohydrate-to-insulin ratios
• ISF insulin sensitivity factors
• the preferred embodiments update a recommended change to the pump parameter based on a previous recommended change to the pump parameter and the difference between the blood glucose value and a target blood glucose level.
• the updated recommended change is compared to a threshold value, and a therapy recommendation is derived if the absolute value of the recommended change exceeds that threshold value.
• the algorithm confirms the therapy recommendation is within safety parameters before displaying the therapy recommendation.
• the therapy recommendation is considered to be within safety parameters if the blood glucose value is relatively consistent with the blood glucose history.
• the determination of whether blood glucose value is relatively consistent is determined by a moving standard deviation analysis.
• the blood glucose values are obtained by a continuous glucose monitor.
• the blood glucose value can be obtained by a glucose strip meter.
• various safety parameters are implemented.
• limits on the therapy recommendation to a particular maximum value are implemented in certain situations.
• limits to an absolute maximum or absolute minimum value for the pump parameter can be implemented.
• Fig. 1 is a flow chart illustrating the intelligent therapy recommendation algorithm for basal rates in accordance with the preferred embodiments of the present invention
• Fig. 2 is a flow chart illustrating the intelligent therapy recommendation algorithm for carbohydrate to insulin ratio in accordance with the preferred embodiments of the present invention
• FIG. 3 is a flow chart illustrating the intelligent therapy recommendation algorithm for insulin sensitivity factor in accordance with the preferred embodiments of the present invention.
• Fig. 4 is an example of a basal rate profile broken up into three hour intervals in accordance with the preferred embodiments of the present invention.
• An insulin pump is designed to mimic the insulin delivery of a normal pancreas. To do so, an insulin pump delivers steady amounts of insulin throughout a day known as a basal rate.
• the basal rate on an insulin pump delivers the amount of insulin needed in the fasting state to maintain target glucose levels.
• the basal rate insulin is intended to account for the baseline insulin needs of the body, and makes up approximately fifty percent of the body's total daily insulin requirements.
• the insulin pump delivers basal rate insulin continuously over the twenty-four hours in the day.
• the insulin pump can be set to provide one or more different rates during different time intervals of the day. These different basal rates at various time intervals during the day usually depend on a patient's lifestyle and insulin requirements.
• a bolus is an extra amount of insulin taken to cover a rise in blood glucose, often related to a meal or snack. Whereas a basal rate provides continuously pumped small quantities of insulin over a long period of time, a bolus provides a relatively large amount of insulin over a fairly short period of time. Most boluses can be broadly put into two categories: meal boluses and correction boluses. A meal bolus is the insulin needed to control the expected rise in glucose levels due to a meal.
• a correction bolus is the insulin used to control unexpected highs in glucose levels. Often a correction bolus is given at the same time as a meal bolus because patients often notice unexpected highs in glucose levels when preparing to deliver a meal bolus related to a meal.
• BG blood glucose
• a target blood glucose value is typically between 70 -120 mg/dL for preprandial BG, and 100 —
• ISF Insulin Sensitivity Factor
• CIR Carbohydrate-to-insulin Ratio
• the bolus estimator will suggest a bolus based on the entry of the estimated carbohydrate intake and current and target blood glucose (BG) levels.
• Preferred embodiments use the following equation:
• One drawback is that currently the pump parameters like ISF, CIR, and basal rates must be consistently and carefully monitored over a period of time by the diabetic individual or physician so adjustments can be made to help achieve and maintain the patient's target glucose level. For example, if fasting morning glucose is systematically higher than the target glucose level set by a health care provider or the diabetic individual himself then the overnight basal rate must be adjusted.
• a patient's body or behavior pattern can change such that additional changes to the pump parameters are needed. These changes require a great deal of record keeping and analysis to determine how much a parameter should be changed.
• Blood glucose monitors such as the blood glucose monitor described in Patent Number 6,809,653, which is incorporated herein in its entirety, have improved many aspects of monitoring blood glucose levels without the need for as many finger sticks, and giving a continuous glucose data that can give a better picture of exactly how the glucose levels change throughout the day.
• the data produced by the blood glucose monitors have been independently used in conjunction with the delivery of insulin using the infusion pump.
• the present invention provides an improved method for monitoring and adjusting insulin pump parameters using blood glucose information obtained either through a glucose meter or a continuous glucose monitor.
• an algorithm provides intelligent therapy recommendations for various pump therapy parameters to help patients more easily adjust those parameters to achieve and maintain a target blood glucose level.
• the algorithm automatically recommends adjustments to insulin pump parameters based on the difference between a glycemic target and actual glucose measurements.
• the algorithms are incorporated in an insulin infusion pump that is able to receive signals from a glucose monitor, an arrangement seen in the MiniMed Paradigm® Real Time Insulin Pump and Continuous Glucose Monitoring System, which is incorporated herein by reference in its entirety.
• the algorithms are stored in the infusion pump's firmware, but can be stored in a separate software routine in the pump's ROM memory.
• the infusion pump controller is able to run the algorithms to perform the necessary steps to provide intelligent therapy recommendations for various pump therapy parameters. Alternatively, these algorithms can be run on a separate device such as a PDA, smart phone, computer, or the like.
• the algorithms can be run on the continuous glucose monitor or combination glucose monitor/infusion pump device or peripheral controller.
• the intelligent therapy recommendations are displayed on the insulin pump, whether the recommendations themselves were calculated by the pump controller or sent from another device either by cable or wireless means.
• the therapy recommendations can also be given on any associated device such as a glucose monitor display, a handheld PDA or smartphone, a computer, etc. Basal Rate
• Figure 1 describes an algorithm used to make adjustment recommendations to a basal rate in accordance with the preferred embodiments of the present invention.
• the algorithm of Figure 1 can be used for both overnight basal rates and daytime basal rates.
• the algorithm begins at block 100.
• Block 110 is used to apply the algorithm to the current day N, and the basal rate interval T is set to 0.
• Each day can be broken up into T number of basal rate intervals where the blood glucose level is recorded at the end of each of the intervals.
• the interval is set to three hours so the glucose values are checked at the end of every three-hour interval throughout the day.
• one basal rate interval T might be from 3 a.m. to 6 a.m.
• the basal rate for that interval will be adapted based on the glucose value at 6 a.m., and the next interval will be from 6 a.m. to 9 a.m. where the glucose value at 9 a.m. is used.
• An example of a basal rate profile broken up into three hour intervals is seen in FIG. 4, where T is represents intervals 1-8.
• a basal rate profile can have various basal rates throughout the day, and the basal rates do not necessarily change at each interval. Based on the running of the algorithm in FIG. 1, adjustments to the specific basal rates can be made for each time interval.
• these intervals can be started at anytime to match the user's schedule and intervals can be greater or less than 3 hours in length.
• the basal rate interval can be as short as the minimum programmable basal rate interval by an insulin pump (e.g. every 30 minutes on a MiniMed Paradigm® Pump) or have a maximum of having one single interval of 24 hours.
• Block 120 is used to apply the algorithm to each basal rate interval T during day N.
• the algorithm at block 130 determines if there was a meal or correction bolus during the basal rate interval T. A meal or correction bolus changes glucose levels unrelated to the basal rate, and so the algorithm proceeds to the next interval because the meal or correction bolus interferes with the analysis required for basal rate calculation.
• the algorithm checks to see if T was the last interval of the day at block 180 and proceeds to the next interval T+l at block 120 to compare the next time interval. IfT was the last interval of the day, then the algorithm moves to the next day at block 1 10.
• a recommended change in basal rate is calculated based on the blood glucose value at the end of the selected basal rate interval.
• this step uses an error integration equation:
• the first step in the error integration equation is to subtract the target glucose level (Target) from the actual glucose level (BG T ) at the end of the basal rate interval T. The difference between those values is then multiplied by a constant (K / ) which is an integral gain coefficient. It determines how fast the algorithm will respond to a glucose concentration over or under the target glucose level. Ki is likely linked to the total insulin requirements of the patient as well as age, gender, and other patient specific parameters, and can be adjusted employing Bayesian statistics once studies of insulin delivery in various segments of the population are performed. K] may also differ depending on the prevailing glucose level (e.g., Ki may be higher for adjustments to hypoglycemia than hyperglycemia).
• the result of the multiplication of K 1 and the blood glucose difference is known as the scaled error.
• This scaled error is then added to the last known proposed change for that particular basal rate interval ( ⁇ / ⁇ ⁇ -1 ) resulting in the new proposed change to the basal rate for that time interval ( AI 13x "). For example, if the basal rate for the interval 3 a.m. to 6 a.m. on Day 70 was being analyzed then the BG ⁇ V/ould be the glucose value at 6 a.m. Next, the scaled error from the 3 a.m. to 6 a.m. basal rate interval of Day 70 would be added to the recommended change from the 3 a.m. to 6 a.m. basal rate interval of Day 69.
• the algorithm compares the absolute value of the recommended change calculated at block 140 to a predefined threshold, typically 0.05 or 0.1 U/h. If the absolute value of the recommended change is less than the predefined threshold, then the algorithm goes to block 125 to move on to the next interval or the next day. However, if the recommended change is greater than the predefined threshold, then the recommendation is evaluated for safety at block 160. In preferred embodiments the safety review of block 160 makes sure that the glucose history is not too variable for a therapy recommendation to be made. A therapy recommendation should only be made if there is a consistent pattern in blood glucose levels to provide a certain level of confidence in the proposed therapy recommendation.
• a predefined threshold typically 0.05 or 0.1 U/h.
• the algorithm determines the variability of the glucose history by using the moving standard deviation, which is the standard deviation of a cluster of the most recent data.
• the moving standard deviation (mSTD(5G)) is compared against the difference between the average glucose value (-3G avg ) and the targeted blood glucose (Target). If the glucose history is too variable for a therapy recommendation to be made (e.g. mSTD(-9G) > BGavg - Target), then no therapy recommendation is made to the user and the logic proceeds to block 180, where the recommended change is reset (e.g. AI g ⁇ is reset to zero). The algorithm then proceeds from block 180 to block
• the safety check is only applied for increases in the basal rate because the immediate risks of hypoglycemia are much greater than hyperglycemia. Hypoglycemia can cause a person to pass out in 15 or 30 minutes while it takes hours for the severe effects of hyperglycemia to become evident and cause problems.
• the algorithm proceeds to block 170 where a therapy recommendation is made to the user.
• a therapy recommendation is tied to the final recommended change calculation that exceeds the threshold, the two values are not necessarily equal.
• the therapy recommendation can be preset to a particular value (e.g. 0.1 Units/hour) such that the therapy recommendation is made when the recommended change exceeds the threshold regardless of what the recommended change value is finally derived.
• the therapy recommendation can be displayed on the infusion pump display and/or combined with different alarms such as vibration, audio, etc.
• the therapy recommendation made to the user in block 170 is capped at a particular maximum as an additional safety precaution.
• the maximum therapy recommendation increase in basal rate is set at 0.1 Unit/hour for an overnight basal rate and 0.2 Unit/hour for daytime basal rate.
• the maximum therapy recommendation can be set at a higher or lower value.
• limits on large decreases in the basal rate can be implemented or upper and lower boundaries for the overall basal rate in addition to limits on the size of changes to the basal rate can be used.
• the therapy recommendation is always rounded to the nearest 0.1 or 0.05 U/h because this is the smallest incremental change currently possible for the MiniMed Paradigm® pumps and other insulin pumps.
• the therapy recommendation may be rounded to the nearest 0.025 U/h as future pumps allow for smaller incremental changes.
• the algorithm advances to the next basal rate interval of the day at block 120. If it is the last basal rate interval of the day then the algorithm proceeds to the next day at block 110 where the process begins again.
• the algorithms can be applied to situations where the insulin pump has multiple basal rate profiles. Specifically, the algorithm can be used to make recommended changes to basal rate profile A by comparing basal rate profile A with only previous basal rate profile A, and making recommended changes to basal rate profile B by comparing basal rate profile B with only previous basal rate profile B 5 etc.
• Figure 2 describes an algorithm used to make adjustment recommendations to a carbohydrate-to-insulin ratio (CIR) in accordance with the preferred embodiments of the present invention.
• the algorithm begins at block 200, where the algorithm reviews the postprandial blood glucose values after each meal before making or not making a recommended change to the ClR.
• Block 210 sets the counter variable so that the algorithm applies to the current meal N.
• the algorithm at block 220 finds the glucose level two hours after meal N. Theoretically, two hours is the ideal time to measure the postprandial blood glucose value, but a longer or shorter time can be used.
• the algorithm at block 230 considers whether another meal was consumed during the two hours after meal N.
• the algorithm searches for meal or error codes within 2 hours after the last meal event, but this interval can be greater or less than 2 hours in length.
• a meal or error code changes glucose levels unrelated to the CIR, and so the algorithm proceeds to the next meal because the meal or error code interferes with the analysis required for ClR calculation. If there was a meal or error code, the algorithm skips the calculation for meal N and goes to block 210 to consider the next meal or move to the next day. If no meal was consumed within two hours of the last meal, the algorithm proceeds to block 240,
• a recommended change in the CIR is calculated based on the postprandial blood glucose value.
• this step uses an error integration equation:
• ACIR* ACIR"-* - K, • ⁇ BG 2h POST - Target
• the first step in the error integration equation is to subtract the target glucose level ⁇ Target) from the actual glucose level (BG 2h posr ) two hours after the meal.
• K, c is the integral gain coefficient for CIR.
• K 1 determines how fast the algorithm will respond to a glucose concentration over or under the target glucose level.
• K jcm is likely linked to the total insulin requirements of the patient as well as age, gender, and other patient specific parameters, and can be adjusted employing Bayesian statistics once studies of insulin delivery in various segments of the population are performed.
• K lcm may also differ depending on the prevailing glucose level (e.g., K 1 may be higher for adjustments to hypoglycemia than hyperglycemia).
• the result of the multiplication of K la ⁇ and the blood glucose difference is known as the scaled error. This scaled error is then subtracted from the last known proposed change for the CIR (ACIR?* '1 ) resulting in the new proposed change to the CIR ( ACIR N ).
• the algorithm compares the absolute value of the recommended change calculated at block 240 to a predefined threshold, typically 5 grams carbohydrates per unit of insulin. If the absolute value of the recommended change is less than the predefined threshold, than the algorithm goes to block 210 to move on to the next meal event. However, if the recommended change is greater than the predefined threshold, then the recommendation is evaluated for safety at block 260. In preferred embodiments, the safety review of block 260 makes sure that the glucose history is not too variable for a therapy recommendation to be made. A therapy recommendation should only be made if there is a consistent pattern in blood glucose levels to provide a certain level of confidence in the proposed therapy recommendation.
• a predefined threshold typically 5 grams carbohydrates per unit of insulin.
• the algorithm determines the variability of the glucose history by using the moving standard deviation, which is the standard deviation of a cluster of the most recent data.
• the moving standard deviation (InSTD(UfG)) is compared against the difference between the average glucose value (SG 3 Vg) and the targeted blood glucose (Target). If the glucose history is too variable for a therapy recommendation to be made (e.g. InSTD(SG) > BG avs - Target), then no therapy recommendation is made to the user and the logic proceeds to block 280, where the recommended change is reset (e.g. ACIR ⁇ is reset to zero). The algorithm then proceeds from block 280 to block 210 to analyze the next meal.
• the safety check is only applied for decreases in CIR because the immediate risks of hypoglycemia are much greater than hyperglycemia.
• the algorithm proceeds to block 270 where a therapy recommendation is made to the user.
• the therapy recommendation is not necessarily equal to the recommended change value that exceeds the threshold.
• the therapy recommendation can be displayed on the infusion pump display and/or combined with different alarms such as vibration, audio, etc.
• the therapy recommendation made to the user in block 270 is capped at a particular maximum as an additional safety precaution. For example, the maximum cap could be set to not modify the current CIR by more than 10 carbohydrates for a Unit of insulin.
• the maximum therapy recommendation decrease can be set at a higher or lower value.
• limits on large increases in the CIR can be implemented or upper and lower boundaries for the overall CIR in addition to limits on the size of therapy recommendations to the CIR can also be used.
• the therapy recommendation is always rounded to the nearest whole number for CIR because this is the smallest incremental change currently possible for the MiniMed Paradigm® pumps and other insulin pumps.
• alternative embodiments may use a loop structure to review every meal in one day before comparing the recommended change to the threshold.
• the recommended change will be refined after each meal in a day to have the most last recommended change compared to the preset threshold.
• Alternative embodiments may use a loop structure for a specific meal only, i.e. breakfast, thus refining the recommended change in CIR for breakfast only.
• the algorithm does not have to have to limit the loop structure to a single day. For example, the algorithm can review all the meals over one week before deciding whether to make a recommendation to the change in CIR, or the algorithm can run continuously until the threshold is passed.
• ISF Insulin Sensitivity Factor
• Figure 3 describes an algorithm used to make adjustment recommendations to the insulin sensitivity factor (ISF) in accordance with the preferred embodiments of the present invention.
• a correction bolus is defined in this algorithm as a bolus to correct for high blood glucose values in isolation of any meal bolus. Therefore, if a bolus was taken for both a meal and to correct for high blood glucose at the same time, the bolus would not be used in this algorithm.
• the algorithm begins at block 300, where the algorithm reviews the blood glucose values after each correction bolus before making or not making a recommended change to the ISF.
• Block 310 sets the counter variable so that the algorithm applies to the current correction bolus N.
• the algorithm at block 320 finds a correction bolus event N and checks the blood glucose value two hours after the correction bolus. The algorithm at block 330 then determines if there were any meals or error codes after the correction bolus event N. In the preferred embodiments, the algorithm searches for meal or error codes within 2 hours after the correction bolus event, but this interval can be greater or less than 2 hours in length. A meal or error code changes glucose levels unrelated to the ISF, and so the algorithm proceeds to the next correction bolus event because the meal or error code interferes with the analysis required for ISF calculation.
• AISF AISF N -> - K. • (BG 2h POST - Target)
• the first step in the error integration equation is to subtract the target glucose level ⁇ Target) from the actual glucose level (BG 2h POSr ) two hours after the correction bolus. The difference between those values is then multiplied by a constant (K, ) which is the integral gain coefficient for ISF.
• K 1 determines how fast the algorithm will respond to a glucose concentration over or under the target glucose level.
• K I/SF is also linked to the total insulin requirements of the patient as well as age, gender, and other patient specific parameters, and can be adjusted employing Bayesian statistics once studies of insulin delivery in various segments of the population are performed. K 1 may also differ depending on the prevailing glucose level (e.g., K 1 may be higher for adjustments to hypoglycemia than hyperglycemia).
• the algorithm compares the absolute value of the recommended change calculated at block 340 to a predefined threshold, typically 5 mg/dl for a Unit of insulin. If the absolute value of the recommended change is less than the predefined threshold, then the algorithm goes to block 310 to move on to the next correction bolus event. However, if the absolute value of the recommended change is greater than the predefined threshold, then the recommendation is evaluated for safety at block 360. In preferred embodiments, the safety review of block 360 makes sure that the glucose history is not too variable for a therapy recommendation to be made. A therapy recommendation should only be made if there is a consistent pattern in blood glucose levels to provide a certain level of confidence in the proposed therapy recommendation.
• a predefined threshold typically 5 mg/dl for a Unit of insulin.
• the algorithm determines the variability of the glucose history by using the moving standard deviation, which is the standard deviation of a cluster of the most recent data.
• the moving standard deviation (mSTD(#(_r)) is compared against the difference between the average glucose value (5G aVg ) and the targeted blood glucose (Target). If the glucose history is too variable for a therapy recommendation to be made (e.g. mSTD(/?G) > BG avg - Target), then no therapy recommendation is made to the user and the logic proceeds to block 280, where the recommended change is reset (e.g. OJSF* is reset to zero). The algorithm then proceeds from block 380 to block 310 to analyze the next correction bolus event.
• the safety check is only applied for decreases in ISF because the immediate risks of hypoglycemia are much greater than hyperglycemia.
• the algorithm proceeds to block 370 where the therapy recommendation is made to the user.
• the therapy recommendation is not necessarily equal to the recommended change value that exceeds the threshold.
• the therapy recommendation can be displayed on the infusion pump display and/or combined with different alarms such as vibration, audio, etc.
• the therapy recommendation is for an decrease in the ISF, the therapy recommendation decrease made to the user in block 370 is capped at a particular maximum as an additional safety precaution.
• the maximum cap could be set to not modify the current ISF by more than 10 mg/dl for a Unit of insulin.
• the maximum therapy recommendation decrease can be set at a higher or lower value.
• limits on large increases in the ISF can be implemented or upper and lower boundaries for the overall ISF in addition to limits on the size of therapy recommendations to the ISF can be used.
• the therapy recommendation is always rounded to the nearest whole number for ISF because this is the smallest incremental change currently possible for the MiniMed Paradigm® pumps and other insulin pumps.
• the algorithm resets the recommended change (e.g. AISF** is reset to zero). The algorithm does not depend on the user accepting or rejecting the therapy recommendation since the recommended change is reset regardless. The algorithm then advances to the next correction bolus event at block 310
• alternative embodiments may use a loop structure to review all the correction boluses in one day before comparing the recommended change to the threshold.
• the recommended change will be refined after each correction bolus calculation such that the last recommended change is then compared to the preset threshold.
• the algorithm does not have to have to limit the loop structure to a single day.
• the algorithm can review all the correction bolus events over one week before deciding whether to make a recommendation to the change in ISF, or be allowed to run continuously until the threshold is met.
• a modified error integration formula can be substituted for the error integration formula described in the preferred embodiments.
• One possibility is to use the area under the glucose curve (AUC) rather than the actual glucose level (BG) at the end of interval T.
• AUC area under the glucose curve
• BG actual glucose level
• the modified error integration formula can be as follows:
• M B ⁇ N AI B ⁇ N ⁇ + K 1 * (AUC T -Target)

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