Evaluation of an Artificial Pancreas with Enhanced Model Predictive Control and a Glucose Prediction Trust Index with Unannounced Exercise
We investigated the safety and efficacy of the addition of a trust index to enhanced Model Predictive Control (eMPC) Artificial Pancreas (AP) that works by adjusting the responsiveness of the controller's insulin delivery based on the confidence intervals around predictions of glucose trends. T...
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| Veröffentlicht in: | Diabetes technology & therapeutics 2018-07, Vol.20 (7), p.455-464 |
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| creator | Pinsker, Jordan E Laguna Sanz, Alejandro J Lee, Joon Bok Church, Mei Mei Andre, Camille Lindsey, Laura E Doyle, 3rd, Francis J Dassau, Eyal |
| description | We investigated the safety and efficacy of the addition of a trust index to enhanced Model Predictive Control (eMPC) Artificial Pancreas (AP) that works by adjusting the responsiveness of the controller's insulin delivery based on the confidence intervals around predictions of glucose trends. This constitutes a dynamic adaptation of the controller's parameters in contrast with the widespread AP implementation of individualized fixed controller tuning.
After 1 week of sensor-augmented pump (SAP) use, subjects completed a 48-h AP admission that included three meals/day (carbohydrate range 29-57 g/meal), a 1-h unannounced brisk walk, and two overnight periods. Endpoints included sensor glucose percentage time 70-180, 180 mg/dL, number of hypoglycemic events, and assessment of the trust index versus standard eMPC glucose predictions.
Baseline characteristics for the 15 subjects who completed the study (mean ± SD) were age 46.1 ± 17.8 years, HbA1c 7.2% ± 1.0%, diabetes duration 26.8 ± 17.6 years, and total daily dose (TDD) 35.5 ± 16.4 U/day. Mean sensor glucose percent time 70-180 mg/dL (88.0% ± 8.0% vs. 74.6% ± 9.4%), |
| doi_str_mv | 10.1089/dia.2018.0031 |
| format | Article |
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After 1 week of sensor-augmented pump (SAP) use, subjects completed a 48-h AP admission that included three meals/day (carbohydrate range 29-57 g/meal), a 1-h unannounced brisk walk, and two overnight periods. Endpoints included sensor glucose percentage time 70-180, <70, >180 mg/dL, number of hypoglycemic events, and assessment of the trust index versus standard eMPC glucose predictions.
Baseline characteristics for the 15 subjects who completed the study (mean ± SD) were age 46.1 ± 17.8 years, HbA1c 7.2% ± 1.0%, diabetes duration 26.8 ± 17.6 years, and total daily dose (TDD) 35.5 ± 16.4 U/day. Mean sensor glucose percent time 70-180 mg/dL (88.0% ± 8.0% vs. 74.6% ± 9.4%), <70 mg/dL (1.5% ± 1.9% vs. 7.8% ± 6.0%), and number of hypoglycemic events (0.6 ± 0.6 vs. 6.3 ± 3.4), all showed statistically significant improvement during AP use compared with the SAP run-in (P < 0.001). On average, the trust index enhanced controller responsiveness to predicted hyper- and hypoglycemia by 26% (P < 0.005).
In this population of well-controlled patients, we conclude that eMPC with trust index AP achieved nearly 90% time in the target glucose range. Additional studies will further validate these results.</description><identifier>ISSN: 1520-9156</identifier><identifier>EISSN: 1557-8593</identifier><identifier>DOI: 10.1089/dia.2018.0031</identifier><identifier>PMID: 29958023</identifier><language>eng</language><publisher>United States: Mary Ann Liebert, Inc</publisher><subject>Adult ; Blood Glucose - analysis ; Blood Glucose Self-Monitoring ; Diabetes ; Diabetes Mellitus, Type 1 - blood ; Diabetes Mellitus, Type 1 - drug therapy ; Exercise ; Female ; Glucose ; Humans ; Hyperglycemia ; Hypoglycemia ; Hypoglycemia - blood ; Hypoglycemia - diagnosis ; Hypoglycemic Agents - therapeutic use ; Insulin ; Insulin - therapeutic use ; Insulin Infusion Systems ; Male ; Middle Aged ; Original ; Pancreas, Artificial ; Sensors</subject><ispartof>Diabetes technology & therapeutics, 2018-07, Vol.20 (7), p.455-464</ispartof><rights>(©) Copyright 2018, Mary Ann Liebert, Inc.</rights><rights>Copyright 2018, Mary Ann Liebert, Inc. 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c415t-ebd7e58898189bc1c157dd7ceb65ff6af01c13f591fc0bdfdee55e8636ae1d33</citedby><cites>FETCH-LOGICAL-c415t-ebd7e58898189bc1c157dd7ceb65ff6af01c13f591fc0bdfdee55e8636ae1d33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29958023$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pinsker, Jordan E</creatorcontrib><creatorcontrib>Laguna Sanz, Alejandro J</creatorcontrib><creatorcontrib>Lee, Joon Bok</creatorcontrib><creatorcontrib>Church, Mei Mei</creatorcontrib><creatorcontrib>Andre, Camille</creatorcontrib><creatorcontrib>Lindsey, Laura E</creatorcontrib><creatorcontrib>Doyle, 3rd, Francis J</creatorcontrib><creatorcontrib>Dassau, Eyal</creatorcontrib><title>Evaluation of an Artificial Pancreas with Enhanced Model Predictive Control and a Glucose Prediction Trust Index with Unannounced Exercise</title><title>Diabetes technology & therapeutics</title><addtitle>Diabetes Technol Ther</addtitle><description>We investigated the safety and efficacy of the addition of a trust index to enhanced Model Predictive Control (eMPC) Artificial Pancreas (AP) that works by adjusting the responsiveness of the controller's insulin delivery based on the confidence intervals around predictions of glucose trends. This constitutes a dynamic adaptation of the controller's parameters in contrast with the widespread AP implementation of individualized fixed controller tuning.
After 1 week of sensor-augmented pump (SAP) use, subjects completed a 48-h AP admission that included three meals/day (carbohydrate range 29-57 g/meal), a 1-h unannounced brisk walk, and two overnight periods. Endpoints included sensor glucose percentage time 70-180, <70, >180 mg/dL, number of hypoglycemic events, and assessment of the trust index versus standard eMPC glucose predictions.
Baseline characteristics for the 15 subjects who completed the study (mean ± SD) were age 46.1 ± 17.8 years, HbA1c 7.2% ± 1.0%, diabetes duration 26.8 ± 17.6 years, and total daily dose (TDD) 35.5 ± 16.4 U/day. Mean sensor glucose percent time 70-180 mg/dL (88.0% ± 8.0% vs. 74.6% ± 9.4%), <70 mg/dL (1.5% ± 1.9% vs. 7.8% ± 6.0%), and number of hypoglycemic events (0.6 ± 0.6 vs. 6.3 ± 3.4), all showed statistically significant improvement during AP use compared with the SAP run-in (P < 0.001). On average, the trust index enhanced controller responsiveness to predicted hyper- and hypoglycemia by 26% (P < 0.005).
In this population of well-controlled patients, we conclude that eMPC with trust index AP achieved nearly 90% time in the target glucose range. Additional studies will further validate these results.</description><subject>Adult</subject><subject>Blood Glucose - analysis</subject><subject>Blood Glucose Self-Monitoring</subject><subject>Diabetes</subject><subject>Diabetes Mellitus, Type 1 - blood</subject><subject>Diabetes Mellitus, Type 1 - drug therapy</subject><subject>Exercise</subject><subject>Female</subject><subject>Glucose</subject><subject>Humans</subject><subject>Hyperglycemia</subject><subject>Hypoglycemia</subject><subject>Hypoglycemia - blood</subject><subject>Hypoglycemia - diagnosis</subject><subject>Hypoglycemic Agents - therapeutic use</subject><subject>Insulin</subject><subject>Insulin - therapeutic use</subject><subject>Insulin Infusion Systems</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Original</subject><subject>Pancreas, Artificial</subject><subject>Sensors</subject><issn>1520-9156</issn><issn>1557-8593</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkUtvEzEURi0EoqWwZIsssWEzwY94xt4gVVEolVq1i7C2PPY1cTWxiz0Tyl_gV-MhJaKs_LjHR_f6Q-gtJQtKpProglkwQuWCEE6foVMqRNdIofjzec9Io6hoT9CrUu4IIR1n9CU6YUoJSRg_Rb_WezNMZgwp4uSxifg8j8EHG8yAb020GUzBP8K4xeu4rWdw-Do5qMUMLtgx7AGvUhxzGuprhw2-GCabChyBat7kqYz4Mjp4OLi-RhNjmv7o1g-QbSjwGr3wZijw5nE9Q5vP683qS3N1c3G5Or9q7JKKsYHedSCkVJJK1Vtqqeic6yz0rfC-NZ7UK-6Fot6S3nkHIATIlrcGqOP8DH06aO-nfgfOQu3dDPo-h53JP3UyQT-txLDV39Jet2RZv01VwYdHQU7fJyij3oViYRhMhDQVzUjLJGeMiIq-_w-9S1OOdbqZooKqli0r1Rwom1MpGfyxGUr0HLKuIes5ZD2HXPl3_05wpP-myn8D3uCmKg</recordid><startdate>201807</startdate><enddate>201807</enddate><creator>Pinsker, Jordan E</creator><creator>Laguna Sanz, Alejandro J</creator><creator>Lee, Joon Bok</creator><creator>Church, Mei Mei</creator><creator>Andre, Camille</creator><creator>Lindsey, Laura E</creator><creator>Doyle, 3rd, Francis J</creator><creator>Dassau, Eyal</creator><general>Mary Ann Liebert, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>201807</creationdate><title>Evaluation of an Artificial Pancreas with Enhanced Model Predictive Control and a Glucose Prediction Trust Index with Unannounced Exercise</title><author>Pinsker, Jordan E ; Laguna Sanz, Alejandro J ; Lee, Joon Bok ; Church, Mei Mei ; Andre, Camille ; Lindsey, Laura E ; Doyle, 3rd, Francis J ; Dassau, Eyal</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c415t-ebd7e58898189bc1c157dd7ceb65ff6af01c13f591fc0bdfdee55e8636ae1d33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Adult</topic><topic>Blood Glucose - analysis</topic><topic>Blood Glucose Self-Monitoring</topic><topic>Diabetes</topic><topic>Diabetes Mellitus, Type 1 - blood</topic><topic>Diabetes Mellitus, Type 1 - drug therapy</topic><topic>Exercise</topic><topic>Female</topic><topic>Glucose</topic><topic>Humans</topic><topic>Hyperglycemia</topic><topic>Hypoglycemia</topic><topic>Hypoglycemia - blood</topic><topic>Hypoglycemia - diagnosis</topic><topic>Hypoglycemic Agents - therapeutic use</topic><topic>Insulin</topic><topic>Insulin - therapeutic use</topic><topic>Insulin Infusion Systems</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Original</topic><topic>Pancreas, Artificial</topic><topic>Sensors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pinsker, Jordan E</creatorcontrib><creatorcontrib>Laguna Sanz, Alejandro J</creatorcontrib><creatorcontrib>Lee, Joon Bok</creatorcontrib><creatorcontrib>Church, Mei Mei</creatorcontrib><creatorcontrib>Andre, Camille</creatorcontrib><creatorcontrib>Lindsey, Laura E</creatorcontrib><creatorcontrib>Doyle, 3rd, Francis J</creatorcontrib><creatorcontrib>Dassau, Eyal</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Diabetes technology & therapeutics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pinsker, Jordan E</au><au>Laguna Sanz, Alejandro J</au><au>Lee, Joon Bok</au><au>Church, Mei Mei</au><au>Andre, Camille</au><au>Lindsey, Laura E</au><au>Doyle, 3rd, Francis J</au><au>Dassau, Eyal</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of an Artificial Pancreas with Enhanced Model Predictive Control and a Glucose Prediction Trust Index with Unannounced Exercise</atitle><jtitle>Diabetes technology & therapeutics</jtitle><addtitle>Diabetes Technol Ther</addtitle><date>2018-07</date><risdate>2018</risdate><volume>20</volume><issue>7</issue><spage>455</spage><epage>464</epage><pages>455-464</pages><issn>1520-9156</issn><eissn>1557-8593</eissn><abstract>We investigated the safety and efficacy of the addition of a trust index to enhanced Model Predictive Control (eMPC) Artificial Pancreas (AP) that works by adjusting the responsiveness of the controller's insulin delivery based on the confidence intervals around predictions of glucose trends. This constitutes a dynamic adaptation of the controller's parameters in contrast with the widespread AP implementation of individualized fixed controller tuning.
After 1 week of sensor-augmented pump (SAP) use, subjects completed a 48-h AP admission that included three meals/day (carbohydrate range 29-57 g/meal), a 1-h unannounced brisk walk, and two overnight periods. Endpoints included sensor glucose percentage time 70-180, <70, >180 mg/dL, number of hypoglycemic events, and assessment of the trust index versus standard eMPC glucose predictions.
Baseline characteristics for the 15 subjects who completed the study (mean ± SD) were age 46.1 ± 17.8 years, HbA1c 7.2% ± 1.0%, diabetes duration 26.8 ± 17.6 years, and total daily dose (TDD) 35.5 ± 16.4 U/day. Mean sensor glucose percent time 70-180 mg/dL (88.0% ± 8.0% vs. 74.6% ± 9.4%), <70 mg/dL (1.5% ± 1.9% vs. 7.8% ± 6.0%), and number of hypoglycemic events (0.6 ± 0.6 vs. 6.3 ± 3.4), all showed statistically significant improvement during AP use compared with the SAP run-in (P < 0.001). On average, the trust index enhanced controller responsiveness to predicted hyper- and hypoglycemia by 26% (P < 0.005).
In this population of well-controlled patients, we conclude that eMPC with trust index AP achieved nearly 90% time in the target glucose range. Additional studies will further validate these results.</abstract><cop>United States</cop><pub>Mary Ann Liebert, Inc</pub><pmid>29958023</pmid><doi>10.1089/dia.2018.0031</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Diabetes technology & therapeutics, 2018-07, Vol.20 (7), p.455-464 |
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| subjects | Adult Blood Glucose - analysis Blood Glucose Self-Monitoring Diabetes Diabetes Mellitus, Type 1 - blood Diabetes Mellitus, Type 1 - drug therapy Exercise Female Glucose Humans Hyperglycemia Hypoglycemia Hypoglycemia - blood Hypoglycemia - diagnosis Hypoglycemic Agents - therapeutic use Insulin Insulin - therapeutic use Insulin Infusion Systems Male Middle Aged Original Pancreas, Artificial Sensors |
| title | Evaluation of an Artificial Pancreas with Enhanced Model Predictive Control and a Glucose Prediction Trust Index with Unannounced Exercise |
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