Algorithm for Predicting the Glicemic Profil in Diabetes Under Regular Measurements
DOI:
https://doi.org/10.20535/ibb.2021.5.1.218259Keywords:
diabetes, glycemic regulation, mathematical modeling, identification method, forecasting algorithm, software and algorithmic structure, computer simulation researchAbstract
Background. In recent years, modern technical devices have been created so that to use in the practice of treating diabetes mellitus. These are systems for continuous monitoring of glycemia, which is a significant addition to the widely accepted measurements of glucose levels with a glucometer, various infusion systems, which significantly improve the doctor's decision-making process. However, such technical means are quite expensive and inaccessible to a wide range of users. In addition, their use is associated with both adverse reactions when wearing them and with patient compliance issues. In this case an alternative can be using mathematical modeling tools.
Objective. The aim of the paper is to prove the possibility of using mathematical modeling to predict the glycemic profile as a certain degree of alternative to a sensor for continuous monitoring of blood glucose levels under conditions of limited irregular measurements.
Methods. To solve the problem it is proposed to employ the technology of mathematical modeling. The structure of the model makes it possible to implement the mathematical formalism by analytical formulae.
Results. As a result, the insulin-glucose-tolerance test has been developed that allows quantitatively assessing a patient's personal sensitivity to insulin-bolus therapy. We proposed the mathematical model for solving the problem by analytical formulae. Algorithms for identifying model parameters, an algorithm for calculating the insulin dose that compensates for the carbohydrate component in the intended meal, and an algorithm for predicting the daily glycemic profile have been developed. The software-algorithmic structure for the implementation of the mathematical formalism has been developed.
Conclusions. The conducted simulation study employing the technology of mathematical modeling makes it possible to evaluate the functioning of the developed procedures at the preclinical stage. The simplicity of calculations using analytical formulae can be a prerequisite for the implementation of the algorithm in portable autonomous special-purpose devices or in smartdata under the Android OS, which is a definite contribution to development of digital diabetology.
References
Karpel’ev VA, Filippov YuI, Tarasov YuV, Boyarsky MD, Mayorov AYu, Shestakova MV, Dedov II. Mathematical modeling of the blood glucose regulation system in diabetes mellitus patients. Annals of the Russian academy of medical sciences. 2015;70(5):549-60. DOI: 10.15690/vramn.v70.i5.1441
Cobelli C, Dalla Man C, Sparacino G, Magni L, De Nicolao G, Kovatchev BP. Diabetes: Models, Signals, and Control. IEEE Reviews in Biomedical Engineering. 2009;2:54-96. DOI: 10.1109/RBME.2009.2036073
Kiforenko S. Hierarchical Modeling as the Basis of Technology of Preclinical Testing Blood Glucose Level Control Algorithms. Cybernetics and Computer Engineering. 2017;(1(187):80-95. DOI: 10.15407/kvt187.01.080
Sokol EI, Lapta SS. The mathematical model of the carbohydrate metabolism regulation. Bulletin of the National Technical University "KhPI". A series of "Information and Modeling". 2015;(33):152-7. DOI: 10.20998/2411-0558.2015.33.16
Gomenyuk SM, Emel'yanov AO, Karpenko AP, Chernezov SA. Review of optimal insulin dose forecasting methods and systems for insulin-dependant diabetes patients. Inform Technol. 2010;3;48-57. DOI: 10.7463/0409.0119663
Cappon G, Acciaroli G, Vettoretti M, Facchinetti A, Sparacino G. Wearable Continuous Glucose Monitoring Sensors: A Revolution in Diabetes Treatment. Electronics. 2017;6(3):65. DOI: 10.3390/electronics6030065
Vettoretti M, Facchinetti A. Combining continuous glucose monitoring and insulin pumps to automatically tune the basal insulin infusion in diabetes therapy: a review. BioMedical Engineering OnLine. 2019;18(1):37. DOI: 10.1186/s12938-019-0658-x
Rodbard D. Continuous Glucose Monitoring: A Review of Recent Studies Demonstrating Improved Glycemic Outcomes. Diabetes Technology & Therapeutics. 2017;19(S3):S25-S37. DOI: 10.1089/dia.2017.0035
Heinemann L, DeVries JH. Reimbursement for Continuous Glucose Monitoring. Diabetes Technology & Therapeutics. 2016;18(S2):S248-S252. DOI: 10.1089/dia.2015.0296
Heinemann L, Franc S, Phillip M, Battelino T, Ampudia-Blasco FJ, Bolinder J, et al. Reimbursement for continuous glucose monitoring: A European view. Journal of Diabetes Science and Technology. 2012;6(6):1498-502. DOI: 10.1177/193229681200600631
Bolie VW. Coefficients оf normal blood glucose regulation. Journal of Applied Physiology. 1961;16(5):783-8. DOI: 10.1152/jappl.1961.16.5.783
Palumbo P, Ditlevsen S, Bertuzzi A, De Gaetano A. Mathematical modeling of the glucose-insulin system: A review. Mathematical Biosciences. 2013;244(2):69-81. DOI: 10.1016/j.mbs.2013.05.006
Nefedov VP, Yasaytis AA, Novoseltsev VN. Homeostasis at different levels of the organization of biosystems. Novosibirsk: Nauka; 1991, 232 p.
Gavaghan D, Garny A, Maini PK, Kohl P. Mathematical models in physiology. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2006;364(1842):1099-106. DOI: 10.1098/rsta.2006.1757
Cobelli C, Carson ER, Finkelstein L, Leaning MS. Validation of simple and complex models in physiology and medicine. American Journal of Physiology: Regulatory, Integrative and Comparative Physiology. 1984;246(2):R259-R266. DOI: 10.1152/ajpregu.1984.246.2.R259
Cobelli C, Carson E. Introduction to Modeling in Physiology and Medicine. Elsevier; 2008. DOI: 10.1016/B978-0-12-160240-6.X5001-7
Cobelli C, Federspil G, Pacini G, Salvan A, Scandellari C. An integrated mathematical model of the dynamics of blood glucose and its hormonal control. Mathematical Biosciences.1982;58(1):27-60. DOI: 10.1016/0025-5564(82)90050-5
Lehmann ED, Chatu SS, Hashmy SSH. Retrospective Pilot Feedback Survey of 200 Users of the AIDA Version 4 Educational Diabetes Program. 17–Quantitative Survey Data. Diabetes Technology & Therapeutics. 2006;8(3):419-32. DOI: 10.1089/dia.2006.8.419
Rutscher A, Salzsieder E, Thierbach U, Fischer U, Albrecht G. KADIS – a Computer-Aided Decision Support System for Improving the Management of Type-I Diabetes. Experimental and Clinical Endocrinology & Diabetes. 1990;95(1):137-47. DOI: 10.1055/s-0029-1210946
Dartau LA, Orkina EL, Novoseltsev VN. Carbohydrate metabolism: Minimal models and management. Engineering physio¬logy and modeling of body systems. Novosibirsk: Nauka; 1987. p. 70-5.
Cobelli C, Man CD, Pedersen MG, Bertoldo A, Toffolo G. Advancing Our Understanding of the Glucose System via Modeling: A Perspective. IEEE Transactions on Biomedical Engineering. 2014;61(5):1577-92. DOI: 10.1109/TBME.2014.2310514
Lapta SS, Pospelov LA, Solovieva OI. Computerized early diagnosis of diabetes mellitus by methods of mathematical modeling. Bulletin of the National Technical University "KhPI". Series: New solutions in modern technologies. 2014;(36(1079):55-61.
Kovatchev BP, Breton MD, Dalla Man C, Cobelli C. In silico model and computer simulation environment approximating the human glucose/insulin utilization. Food and Drug Administration Master File MAF1521. 2008.
Kovatchev BP, Breton M, Dalla Man C, Cobelli C. In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes. Journal of Diabetes Science and Technology. 2009;3(1):44-55. DOI: 10.1177/193229680900300106
Man CD, Micheletto F, Lv D, Breton M, Kovatchev B, Cobelli C. The UVA/PADOVA Type 1 Diabetes Simulator: New Features. Journal of Diabetes Science and Technology. 2014;8(1):26-34. DOI: 10.1177/1932296813514502
Kapuro J, Sheable T, McCan T. Method and system for controlling the tuning factor in connection with the replacement of a sensor for a feedback controller with an artificial pancreas [Internet]. 2021 [cited 2020 Dec 7]. Available from: https://findpatent.ru/patent/267/2672121.html
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