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Comparison of Insulin Dose Adjustments Made by Artificial Intelligence-Based Decision Support Systems and by Physicians in People with Type 1 Diabetes Using Multiple Daily Injections Therapy
R. Nimri, A. Tirosh, I. Muller, Y. Shtrit, I. Kraljevic, MM. Alonso, T. Milicic, B. Saboo, A. Deeb, A. Christoforidis, M. den Brinker, L. Bozzetto, AM. Bolla, M. Krcma, RA. Rabini, S. Tabba, A. Gerasimidi-Vazeou, G. Maltoni, E. Giani, I. Dotan,...
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
35325567
DOI
10.1089/dia.2021.0566
Knihovny.cz E-zdroje
- MeSH
- diabetes mellitus 1. typu * farmakoterapie MeSH
- hypoglykemika terapeutické užití MeSH
- inzulin lidský terapeutické užití MeSH
- inzulin terapeutické užití MeSH
- krevní glukóza MeSH
- lékaři * MeSH
- lidé MeSH
- umělá inteligence MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Objective: Artificial intelligence-based decision support systems (DSS) need to provide decisions that are not inferior to those given by experts in the field. Recommended insulin dose adjustments on the same individual data set were compared among multinational physicians, and with recommendations made by automated Endo.Digital DSS (ED-DSS). Research Design and Methods: This was a noninterventional study surveying 20 physicians from multinational academic centers. The survey included 17 data cases of individuals with type 1 diabetes who are treated with multiple daily insulin injections. Participating physicians were asked to recommend insulin dose adjustments based on glucose and insulin data. Insulin dose adjustments recommendations were compared among physicians and with the automated ED-DSS. The primary endpoints were the percentage of comparison points for which there was agreement on the trend of insulin dose adjustments. Results: The proportion of agreement and disagreement in the direction of insulin dose adjustment among physicians was statistically noninferior to the proportion of agreement and disagreement observed between ED-DSS and physicians for basal rate, carbohydrate-to insulin ratio, and correction factor (P < 0.001 and P ≤ 0.004 for all three parameters for agreement and disagreement, respectively). The ED-DSS magnitude of insulin dose change was consistently lower than that proposed by the physicians. Conclusions: Recommendations for insulin dose adjustments made by automatization did not differ significantly from recommendations given by expert physicians regarding the direction of change. These results highlight the potential utilization of ED-DSS as a useful clinical tool to manage insulin titration and dose adjustments.
Department of Biomedical Sciences Humanitas University Milan Italy
Department of Clinical Medicine and Surgery University of Naples Federico 2 Naples Italy
Department of Diabetology Hospital Mazzoni Ascoli Piceno Italy
Department of Pediatric Endocrinology Arnold Palmer Hospital for Children Orlando Florida USA
Department of Pediatrics Children's Endocrinology Unit University Hospital of Salamanca Spain
Dia Care Diabetes Care and Hormone Clinic Ahmedabad Gujarat India
Diabetes Center A' Department of Pediatrics P and A Kyriakou Athens Greece
Diabetes Center for Children and Adolescents Children's Hospital AUF DER BULT Hannover Germany
Division of Endocrinology ASST Fatebenefratelli Sacco Milan Italy
DreaMed Diabetes Ltd Petah Tikva Israel
Rabin Medical Center Institute of Endocrinology Beilinson Hospital Petach Tikva Israel
Sackler Faculty of Medicine Tel Aviv University Tel Hashomer Israel
Unit of Pediatrics IRCCS Azienda Ospedaliero Universitaria di Bologna Bologna Italy
Citace poskytuje Crossref.org
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