Sensitivity of the Predictive Hypoglycemia Minimizer System to the Algorithm Aggressiveness Factor
Background: The Predictive Hypoglycemia Minimizer System (“Hypo Minimizer”), consisting of a zone model predictive controller (the “controller”) and a safety supervision module (the “safety module”), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucos...
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Published in | Journal of diabetes science and technology Vol. 10; no. 1; pp. 104 - 110 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Los Angeles, CA
SAGE Publications
01.01.2016
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Subjects | |
Online Access | Get full text |
ISSN | 1932-2968 1932-3107 |
DOI | 10.1177/1932296815593292 |
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Abstract | Background:
The Predictive Hypoglycemia Minimizer System (“Hypo Minimizer”), consisting of a zone model predictive controller (the “controller”) and a safety supervision module (the “safety module”), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The “aggressiveness factor,” a pivotal variable in the system, governs the speed and magnitude of the controller’s insulin dosing characteristics in response to changes in CGM levels.
Methods:
Twelve adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 24 hours. This analysis focused primarily on the effect of the aggressiveness factor on the automated insulin-delivery characteristics of the controller, and secondarily on the glucose control results.
Results:
As aggressiveness increased from “conservative” to “medium” to “aggressive,” the controller recommended less insulin (–3.3% vs –14.4% vs –19.5% relative to basal) with a higher frequency (5.3% vs 14.4% vs 20.3%) during the critical times when the CGM was reading 90-120 mg/dl and decreasing. Blood glucose analyses indicated that the most aggressive setting resulted in the most desirable combination of the least time spent <70 mg/dl and the most time spent 70-180 mg/dl, particularly in the overnight period. Hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia did not occur with any of the aggressiveness values.
Conclusion:
The Hypo Minimizer’s controller took preemptive action to prevent hypoglycemia based on predicted changes in CGM glucose levels. The most aggressive setting was quickest to take action to reduce insulin delivery below basal and achieved the best glucose metrics. |
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AbstractList | Background:
The Predictive Hypoglycemia Minimizer System (“Hypo Minimizer”), consisting of a zone model predictive controller (the “controller”) and a safety supervision module (the “safety module”), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The “aggressiveness factor,” a pivotal variable in the system, governs the speed and magnitude of the controller’s insulin dosing characteristics in response to changes in CGM levels.
Methods:
Twelve adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 24 hours. This analysis focused primarily on the effect of the aggressiveness factor on the automated insulin-delivery characteristics of the controller, and secondarily on the glucose control results.
Results:
As aggressiveness increased from “conservative” to “medium” to “aggressive,” the controller recommended less insulin (–3.3% vs –14.4% vs –19.5% relative to basal) with a higher frequency (5.3% vs 14.4% vs 20.3%) during the critical times when the CGM was reading 90-120 mg/dl and decreasing. Blood glucose analyses indicated that the most aggressive setting resulted in the most desirable combination of the least time spent <70 mg/dl and the most time spent 70-180 mg/dl, particularly in the overnight period. Hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia did not occur with any of the aggressiveness values.
Conclusion:
The Hypo Minimizer’s controller took preemptive action to prevent hypoglycemia based on predicted changes in CGM glucose levels. The most aggressive setting was quickest to take action to reduce insulin delivery below basal and achieved the best glucose metrics. The Predictive Hypoglycemia Minimizer System ("Hypo Minimizer"), consisting of a zone model predictive controller (the "controller") and a safety supervision module (the "safety module"), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The "aggressiveness factor," a pivotal variable in the system, governs the speed and magnitude of the controller's insulin dosing characteristics in response to changes in CGM levels. Twelve adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 24 hours. This analysis focused primarily on the effect of the aggressiveness factor on the automated insulin-delivery characteristics of the controller, and secondarily on the glucose control results. As aggressiveness increased from "conservative" to "medium" to "aggressive," the controller recommended less insulin (-3.3% vs -14.4% vs -19.5% relative to basal) with a higher frequency (5.3% vs 14.4% vs 20.3%) during the critical times when the CGM was reading 90-120 mg/dl and decreasing. Blood glucose analyses indicated that the most aggressive setting resulted in the most desirable combination of the least time spent <70 mg/dl and the most time spent 70-180 mg/dl, particularly in the overnight period. Hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia did not occur with any of the aggressiveness values. The Hypo Minimizer's controller took preemptive action to prevent hypoglycemia based on predicted changes in CGM glucose levels. The most aggressive setting was quickest to take action to reduce insulin delivery below basal and achieved the best glucose metrics. The Predictive Hypoglycemia Minimizer System ("Hypo Minimizer"), consisting of a zone model predictive controller (the "controller") and a safety supervision module (the "safety module"), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The "aggressiveness factor," a pivotal variable in the system, governs the speed and magnitude of the controller's insulin dosing characteristics in response to changes in CGM levels.BACKGROUNDThe Predictive Hypoglycemia Minimizer System ("Hypo Minimizer"), consisting of a zone model predictive controller (the "controller") and a safety supervision module (the "safety module"), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The "aggressiveness factor," a pivotal variable in the system, governs the speed and magnitude of the controller's insulin dosing characteristics in response to changes in CGM levels.Twelve adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 24 hours. This analysis focused primarily on the effect of the aggressiveness factor on the automated insulin-delivery characteristics of the controller, and secondarily on the glucose control results.METHODSTwelve adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 24 hours. This analysis focused primarily on the effect of the aggressiveness factor on the automated insulin-delivery characteristics of the controller, and secondarily on the glucose control results.As aggressiveness increased from "conservative" to "medium" to "aggressive," the controller recommended less insulin (-3.3% vs -14.4% vs -19.5% relative to basal) with a higher frequency (5.3% vs 14.4% vs 20.3%) during the critical times when the CGM was reading 90-120 mg/dl and decreasing. Blood glucose analyses indicated that the most aggressive setting resulted in the most desirable combination of the least time spent <70 mg/dl and the most time spent 70-180 mg/dl, particularly in the overnight period. Hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia did not occur with any of the aggressiveness values.RESULTSAs aggressiveness increased from "conservative" to "medium" to "aggressive," the controller recommended less insulin (-3.3% vs -14.4% vs -19.5% relative to basal) with a higher frequency (5.3% vs 14.4% vs 20.3%) during the critical times when the CGM was reading 90-120 mg/dl and decreasing. Blood glucose analyses indicated that the most aggressive setting resulted in the most desirable combination of the least time spent <70 mg/dl and the most time spent 70-180 mg/dl, particularly in the overnight period. Hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia did not occur with any of the aggressiveness values.The Hypo Minimizer's controller took preemptive action to prevent hypoglycemia based on predicted changes in CGM glucose levels. The most aggressive setting was quickest to take action to reduce insulin delivery below basal and achieved the best glucose metrics.CONCLUSIONThe Hypo Minimizer's controller took preemptive action to prevent hypoglycemia based on predicted changes in CGM glucose levels. The most aggressive setting was quickest to take action to reduce insulin delivery below basal and achieved the best glucose metrics. |
Author | Kovatchev, Boris P. Dassau, Eyal Breton, Marc D. Patek, Stephen D. Doyle, Francis J. Levy, Brian L. McCann, Thomas W. Venugopalan, Ramakrishna Finan, Daniel A. |
AuthorAffiliation | 2 University of California, Santa Barbara, Santa Barbara, CA, USA 3 Sansum Diabetes Research Institute, Santa Barbara, CA, USA 4 University of Virginia, Center for Diabetes Technology, Charlottesville, VA, USA 1 Animas Corporation, Chesterbrook, PA, USA |
AuthorAffiliation_xml | – name: 1 Animas Corporation, Chesterbrook, PA, USA – name: 4 University of Virginia, Center for Diabetes Technology, Charlottesville, VA, USA – name: 2 University of California, Santa Barbara, Santa Barbara, CA, USA – name: 3 Sansum Diabetes Research Institute, Santa Barbara, CA, USA |
Author_xml | – sequence: 1 givenname: Daniel A. surname: Finan fullname: Finan, Daniel A. email: dfinan@its.jnj.com – sequence: 2 givenname: Eyal surname: Dassau fullname: Dassau, Eyal – sequence: 3 givenname: Marc D. surname: Breton fullname: Breton, Marc D. – sequence: 4 givenname: Stephen D. surname: Patek fullname: Patek, Stephen D. – sequence: 5 givenname: Thomas W. surname: McCann fullname: McCann, Thomas W. – sequence: 6 givenname: Boris P. surname: Kovatchev fullname: Kovatchev, Boris P. – sequence: 7 givenname: Francis J. surname: Doyle fullname: Doyle, Francis J. – sequence: 8 givenname: Brian L. surname: Levy fullname: Levy, Brian L. – sequence: 9 givenname: Ramakrishna surname: Venugopalan fullname: Venugopalan, Ramakrishna |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26134834$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1089_dia_2017_0035 crossref_primary_10_1016_j_jpeds_2017_02_055 crossref_primary_10_1080_17434440_2022_2150546 crossref_primary_10_17925_EE_2019_15_2_70 crossref_primary_10_1089_dia_2018_0278 crossref_primary_10_1111_dom_12999 |
Cites_doi | 10.2337/dc13-2911 10.2337/dc12-1965 10.1177/193229680800200518 10.1089/dia.2009.0031 10.2337/dc13-1631 10.2337/dc12-0948 10.1177/193229681000400513 10.1056/NEJMoa1206881 10.1177/1932296814534589 10.1056/NEJMoa1314474 10.1109/TBME.2012.2192930 10.2337/db11-1445 10.2337/dc13-2644 10.2337/dc13-2076 10.1016/S2213-8587(14)70114-7 10.1136/bmjdrc-2014-000025. 10.1177/193229681300700515 10.1109/TBME.2014.2323248 10.2337/dc13-2108 10.1177/1932296813511730 10.2337/dc14-0147 10.1210/jc.2013-4151 |
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Keywords | model predictive control Aggressiveness factor type 1 diabetes closed-loop control artificial pancreas algorithm |
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Snippet | Background:
The Predictive Hypoglycemia Minimizer System (“Hypo Minimizer”), consisting of a zone model predictive controller (the “controller”) and a safety... The Predictive Hypoglycemia Minimizer System ("Hypo Minimizer"), consisting of a zone model predictive controller (the "controller") and a safety supervision... |
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SubjectTerms | Adult Algorithms Blood Glucose - analysis Blood Glucose Self-Monitoring - methods Diabetes Mellitus, Type 1 - blood Diabetes Mellitus, Type 1 - drug therapy Feasibility Studies Female Humans Hypoglycemia - blood Hypoglycemia - prevention & control Hypoglycemic Agents - administration & dosage Infusion Pumps, Implantable Insulin - administration & dosage Insulin Infusion Systems Male Middle Aged Original Pancreas, Artificial |
Title | Sensitivity of the Predictive Hypoglycemia Minimizer System to the Algorithm Aggressiveness Factor |
URI | https://journals.sagepub.com/doi/full/10.1177/1932296815593292 https://www.ncbi.nlm.nih.gov/pubmed/26134834 https://www.proquest.com/docview/1753010474 https://pubmed.ncbi.nlm.nih.gov/PMC4738202 |
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