A modular safety system for an insulin dose recommender: a feasibility study

Delivering insulin in type 1 diabetes is a challenging, and potentially risky, activity; hence the importance of including safety measures as part of any insulin dosing or recommender system. This work presents and clinically evaluates a modular safety system that is part of an intelligent insulin d...

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Autores: Liu, Chengyuan, Avari, Parizad, Leal Moncada, Yenny Teresa, Wos, Marzena, Sivasithamparam, Kumuthine, Pantelis, Georgiou, Reddy, Monika, Fernández-Real Lemos, José Manuel, Martin, Clare, Fernández-Balsells, Mercè, Oliver, Nick, Herrero i Viñas, Pau
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2020
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/18038
Acceso en línea:http://hdl.handle.net/10256/18038
Access Level:acceso abierto
Palabra clave:Diabetis
Diabetes
Intel·ligència artificial -- Aplicacions a la medicina
Artificial intelligence -- Medical applications
Sistemes d'ajuda a la decisió
Decision support systems
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spelling A modular safety system for an insulin dose recommender: a feasibility studyLiu, ChengyuanAvari, ParizadLeal Moncada, Yenny TeresaWos, MarzenaSivasithamparam, KumuthinePantelis, GeorgiouReddy, MonikaFernández-Real Lemos, José ManuelMartin, ClareFernández-Balsells, MercèOliver, NickHerrero i Viñas, PauDiabetisDiabetesIntel·ligència artificial -- Aplicacions a la medicinaArtificial intelligence -- Medical applicationsSistemes d'ajuda a la decisióDecision support systemsDelivering insulin in type 1 diabetes is a challenging, and potentially risky, activity; hence the importance of including safety measures as part of any insulin dosing or recommender system. This work presents and clinically evaluates a modular safety system that is part of an intelligent insulin dose recommender platform developed within the EU-funded PEPPER project. METHODS: The proposed safety system is composed of four modules which use a novel glucose forecasting algorithm. These modules are predictive glucose alerts and alarms; a predictive low-glucose basal insulin suspension module; an advanced rescue carbohydrate recommender for resolving hypoglycemia; and a personalized safety constraint applied to insulin recommendations. The technical feasibility of the proposed safety system was evaluated in a pilot study including eight adult subjects with type 1 diabetes on multiple daily injections over a duration of six weeks. Glycemic control and safety system functioning were compared between the two-weeks run-in period and the end point at eight weeks. A standard insulin bolus calculator was employed to recommend insulin doses. RESULTS: Overall, glycemic control improved over the evaluated period. In particular, percentage time in the hypoglycemia range (<3.0 mmol/l) significantly decreased from 0.82% (0.05-4.79) at run-in to 0.33% (0.00-0.93) at endpoint ( P = .02). This was associated with a significant increase in percentage time in target range (3.9-10.0 mmol/l) from 52.8% (38.3-61.5) to 61.3% (47.5-71.7) ( P = .03). There was also a reduction in number of carbohydrate recommendations. CONCLUSION: A safety system for an insulin dose recommender has been proven to be a viable solution to reduce the number of adverse events associated to glucose control in type 1 diabetesThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 689810.SAGE PublicationsEuropean Commission2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionpeer-reviewedapplication/pdfhttp://hdl.handle.net/10256/18038© Journal of Diabetes Science and Technology, 2020, vol. 14, núm. 1, p.87-96Articles publicats (IdIBGi)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.1177/1932296819851135info:eu-repo/semantics/altIdentifier/issn/1932-2968info:eu-repo/grantAgreement/EC/H2020/689810Tots els drets reservatsinfo:eu-repo/semantics/openAccessoai:recercat.cat:10256/180382026-05-29T05:05:01Z
dc.title.none.fl_str_mv A modular safety system for an insulin dose recommender: a feasibility study
title A modular safety system for an insulin dose recommender: a feasibility study
spellingShingle A modular safety system for an insulin dose recommender: a feasibility study
Liu, Chengyuan
Diabetis
Diabetes
Intel·ligència artificial -- Aplicacions a la medicina
Artificial intelligence -- Medical applications
Sistemes d'ajuda a la decisió
Decision support systems
title_short A modular safety system for an insulin dose recommender: a feasibility study
title_full A modular safety system for an insulin dose recommender: a feasibility study
title_fullStr A modular safety system for an insulin dose recommender: a feasibility study
title_full_unstemmed A modular safety system for an insulin dose recommender: a feasibility study
title_sort A modular safety system for an insulin dose recommender: a feasibility study
dc.creator.none.fl_str_mv Liu, Chengyuan
Avari, Parizad
Leal Moncada, Yenny Teresa
Wos, Marzena
Sivasithamparam, Kumuthine
Pantelis, Georgiou
Reddy, Monika
Fernández-Real Lemos, José Manuel
Martin, Clare
Fernández-Balsells, Mercè
Oliver, Nick
Herrero i Viñas, Pau
author Liu, Chengyuan
author_facet Liu, Chengyuan
Avari, Parizad
Leal Moncada, Yenny Teresa
Wos, Marzena
Sivasithamparam, Kumuthine
Pantelis, Georgiou
Reddy, Monika
Fernández-Real Lemos, José Manuel
Martin, Clare
Fernández-Balsells, Mercè
Oliver, Nick
Herrero i Viñas, Pau
author_role author
author2 Avari, Parizad
Leal Moncada, Yenny Teresa
Wos, Marzena
Sivasithamparam, Kumuthine
Pantelis, Georgiou
Reddy, Monika
Fernández-Real Lemos, José Manuel
Martin, Clare
Fernández-Balsells, Mercè
Oliver, Nick
Herrero i Viñas, Pau
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv European Commission
dc.subject.none.fl_str_mv Diabetis
Diabetes
Intel·ligència artificial -- Aplicacions a la medicina
Artificial intelligence -- Medical applications
Sistemes d'ajuda a la decisió
Decision support systems
topic Diabetis
Diabetes
Intel·ligència artificial -- Aplicacions a la medicina
Artificial intelligence -- Medical applications
Sistemes d'ajuda a la decisió
Decision support systems
description Delivering insulin in type 1 diabetes is a challenging, and potentially risky, activity; hence the importance of including safety measures as part of any insulin dosing or recommender system. This work presents and clinically evaluates a modular safety system that is part of an intelligent insulin dose recommender platform developed within the EU-funded PEPPER project. METHODS: The proposed safety system is composed of four modules which use a novel glucose forecasting algorithm. These modules are predictive glucose alerts and alarms; a predictive low-glucose basal insulin suspension module; an advanced rescue carbohydrate recommender for resolving hypoglycemia; and a personalized safety constraint applied to insulin recommendations. The technical feasibility of the proposed safety system was evaluated in a pilot study including eight adult subjects with type 1 diabetes on multiple daily injections over a duration of six weeks. Glycemic control and safety system functioning were compared between the two-weeks run-in period and the end point at eight weeks. A standard insulin bolus calculator was employed to recommend insulin doses. RESULTS: Overall, glycemic control improved over the evaluated period. In particular, percentage time in the hypoglycemia range (<3.0 mmol/l) significantly decreased from 0.82% (0.05-4.79) at run-in to 0.33% (0.00-0.93) at endpoint ( P = .02). This was associated with a significant increase in percentage time in target range (3.9-10.0 mmol/l) from 52.8% (38.3-61.5) to 61.3% (47.5-71.7) ( P = .03). There was also a reduction in number of carbohydrate recommendations. CONCLUSION: A safety system for an insulin dose recommender has been proven to be a viable solution to reduce the number of adverse events associated to glucose control in type 1 diabetes
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
peer-reviewed
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/18038
url http://hdl.handle.net/10256/18038
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1177/1932296819851135
info:eu-repo/semantics/altIdentifier/issn/1932-2968
info:eu-repo/grantAgreement/EC/H2020/689810
dc.rights.none.fl_str_mv Tots els drets reservats
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Tots els drets reservats
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv SAGE Publications
publisher.none.fl_str_mv SAGE Publications
dc.source.none.fl_str_mv © Journal of Diabetes Science and Technology, 2020, vol. 14, núm. 1, p.87-96
Articles publicats (IdIBGi)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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