Modelado matemático de ingestas de alimento e infusión de insulina en un paciente con diabetes tipo 1 en lazo cerrado
DOI:
https://doi.org/10.4995/riai.2019.11161Palabras clave:
Diabetes Tipo 1, Modelo Matemático Dinámica Glucosa - Insulina, Regulación de Insulina en Lazo CerradoResumen
La diabetes tipo 1 es una afección en la cual el páncreas pierde su capacidad de producir suficiente insulina, incrementando significativamente la concentración de glucosa en la sangre. En el presente trabajo se presenta el diseño de un modelo matemático de las dinámicas glucosa-insulina de un paciente con diabetes tipo 1, el cual contempla el aporte a la concentración de glucosa en la sangre por parte de la ingesta de carbohidratos, grasas y proteínas. El modelo incluye las dinámicas de absorción de 5 tipos de insulina, diferentes métodos de administración de la misma, y la variación de la sensibilidad a la insulina durante el día. Se integró el modelo a un algoritmo de regulación de insulina en lazo cerrado, con el fin de evaluar el desempeño del modelo y la eficacia de los tratamientos en lazo cerrado, en comparación con las terapias en lazo abierto. Los resultados muestran la respuesta del modelo ante distintas situaciones de un paciente real, y pruebas de funcionamiento del controlador.Descargas
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Ackerman, E., Rosevear, J. W., McGuckin, W. F., 1964. A mathematical model of the glucose-tolerance test. Physics in medicine & Biology 9 (2), 203. https://doi.org/10.1088/0031-9155/9/2/307
American Diabetes Association, 2017. [Online; accessed October 2018]. URL: http://www.diabetes.org/
Apablaza, P., Soto, N., Codner, E., 2017. De la bomba de insulina y el monitoreo continuo de glucosa al páncreas artificial. Revista Médica de Chile,145 (5), 630-640. https://doi.org/10.4067/S0034-98872017000500011
Barrio, R., Andia, V., Vazquez, F., Salgado, Y., Valverde, M., Jansa, M., Flores, M., 2012. Guía de educación terapéutica, al inicio de tratamiento con infusión subcutánea continua de insulina (ISCI). PardeDós. URL: https://diabetesmadrid.org/
Beneyto, A., Bertachi, A., Bondia, J., Vehi, J., 2018. A new blood glucose control scheme for unannounced exercise in type 1 diabetic subjects. IEEE Transactions on Control Systems Technology, 1-8.
Bergenstal, R. M., Garg, S., Weinzimer, S. A., Buckingham, B. A., Bode, B. W., Tamborlane, W. V., Kaufman, F. R., 2016. Safety of a hybrid closed-loop insulin delivery system in patients with type 1 diabetes. Jama 316 (13), 1407- 1408. https://doi.org/10.1001/jama.2016.11708
Berger, M., Rodbard, D., 1989. Computer simulation of plasma insulin and glucose dynamics after subcutaneous insulin injection. Diabetes Care 12 (10), 725-736. https://doi.org/10.2337/diacare.12.10.725
Binder, C., 1969. Absorption of injected insulin: A clinical-pharmacological study. Acta Pharmacologica et Toxicologica 27 (S2), 1-83. https://doi.org/10.1111/j.1600-0773.1969.tb03069.x
Bolie, V. W., 1961. Coefficients of normal blood glucose regulation. Journal of Applied Physiology 16 (5), 783-788. https://doi.org/10.1152/jappl.1961.16.5.783
Breda, E., Cavaghan, M. K., Toffolo, G., Polonsky, K. S., Cobelli, C., 2001. Oral glucose tolerance test minimal model indexes of β-cell function and insulin sensitivity. Diabetes 50 (1), 150-158. https://doi.org/10.2337/diabetes.50.1.150
Breton, M., Farret, A., Bruttomesso, D., Anderson, S., Magni, L., Patek, S., Dalla Man, C., Place, J., Demartini, S., Del Favero, S., 2012. Fully integrated artificial pancreas in type 1 diabetes: modular closed-loop glucose control maintains near normoglycemia. Diabetes 61, 2230-2237. https://doi.org/10.2337/db11-1445
Bruttomesso, D., Farret, A., Costa, S., Marescotti, M. C., Vettore, M., Avogaro, A., Tiengo, A., Dalla Man, C., Place, J., Facchinetti, A., 2009. Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: preliminary studies in Padova and Montpellier. Journal of Diabetes Science and Technology 3, 1014-1021. https://doi.org/10.1177/193229680900300504
Clarke, W. L., Anderson, S., Breton, M., Patek, S., Kashmer, L., Kovatchev, B., 2009. Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience. Journal of Diabetes Science and Technology 3, 1031-1038. https://doi.org/10.1177/193229680900300506
Clemens, A., Chang, P., Myers, R., 1977. The development of biostator, a glucose controlled insulin infusion system (GCIIS). Hormone and metabolic research 7, 23-33.
Cobelli, C., Nucci, G., Del Prato, S., 1999. A physiological simulation model of the glucose-insulin system. Vol. 2.
Colino, E., 2018. Fundación para la Diabetes. [Online; October 2018]. URL: http://www.fundaciondiabetes.org/
Craig, T. P., 2010. Dietary Carnitine Supplementation as a potential modulator of insulin sensitivity. Master's Thesis, University of Stirling. URL: https://dspace.stir.ac.uk/
Dalla Man, C., Breton, M. D., Cobelli, C., 2009. Physical activity into the meal glucose-insulin model of type 1 diabetes: in silico studies 3, 56-67. https://doi.org/10.1177/193229680900300107
Dalla Man, C., Camilleri, M., Cobelli, C., 2006. A system model of oral glucose absorption: validation on gold standard data. IEEE Transactions on Biomedical Engineering 53 (12), 2472-2478. https://doi.org/10.1109/TBME.2006.883792
Dalla Man, C., Micheletto, F., Lv, D., Breton, M., Kovatchev, B., Cobelli, C., 2014. The uva/padova type 1 diabetes simulator: new features. Journal of Diabetes Science and Technology 8 (1), 26-34. https://doi.org/10.1177/1932296813514502
Dalla Man, C., Raimondo, D. M., Rizza, R. A., Cobelli, C., 2007a. GIM, simulation software of meal glucose insulin model. Journal of Diabetes Science and Technology 1, 323-330. https://doi.org/10.1177/193229680700100303
Dalla Man, C., Rizza, R. A., Cobelli, C., 2007b. Meal simulation model of the glucose-insulin system. IEEE Transactions on Biomedical Engineering 54 (10), 1740-1749. https://doi.org/10.1109/TBME.2007.893506
Haidar, A., 2016. The artificial pancreas: How close-loop control is revolutionizing diabetes. IEEE Condtrol Systems 36 (5), 28-47. https://doi.org/10.1109/MCS.2016.2584318
International Diabetes Federation, 2017. IDF diabetes atlas, 8th Edition. URL: http://www.diabetesatlas.org/
IRICOM, 2018. Sociedad Española de Diabetes. [Online; October 2018]. URL: http://www.sediabetes.org/
Kadish, A. H., 1963. Automation control of blood sugar a servomechanism for glucose monitoring and control. ASAIO Journal 9 (1), 363-367.
Manrique, J., Romero, J. D., Sabater, J. M., Vivas, O. A., Vicente, J. M., 2018. Simulador de paciente T1D en tiempo real. Actas de las XXXIX Jornadas de Automática, Badajoz, 64-71. '
Mauseth, R., Hirsch, I. B., Bollyky, J., Kircher, R., Matheson, D., Sanda, S., Greenbaum, C., 2013. Use of a "fuzzy logic" controller in a closed-loop artificial pancreas. Diabetes Technology & Therapeutics 15 (8), 628-633. https://doi.org/10.1089/dia.2013.0036
Murillo, M. D., Fernandez, F., Tuneu, L., 2004. Guía de seguimiento farmacoterapéutico sobre diabetes. Grupo de Investigación en Atención Farmacéutica (GIAF). URL: http://www.ugr.es/
National Center for Biotechnology Information, 2018. Insulin aspart. Pub Chem Compound Database, [Online; October 2018]. URL: https://pubchem.ncbi.nlm.nih.gov/compound/16132418
Nimri, R., Atlas, E., Ajzensztejn, M., Miller, S., Oron, T., Phillip, M., 2012. Feasibility study of automated overnight closed-loop glucose control under md-logic artificial pancreas in patients with type 1 diabetes: the dream project. Diabetes Technology & Therapeutics 14 (8), 728-735. https://doi.org/10.1089/dia.2012.0004
Nucci, G., Cobelli, C., 2000. Models of subcutaneous insulin kinetics. a critical review. Computer Methods and Programs in Biomedicine 62 (3), 249-257. https://doi.org/10.1016/S0169-2607(00)00071-7
OpenAPS Community, 2015. Openaps. OpenAPS.org, [Online; October 2018]. URL: https://openaps.org/
Renard, E., Place, J., Cantwell, M., Chevassus, H., Palerm, C. C., 2010. Closedloop insulin delivery using a subcutaneous glucose sensor and intraperitoneal insulin delivery: feasibility study testing a new model for the artificial pancreas. Diabetes Care 33 (1), 121-127. https://doi.org/10.2337/dc09-1080
Segre, G., Turco, G., Vercellone, G., 1973. Modeling blood glucose and insulin kinetics in normal, diabetic and obese subjects. Diabetes 22 (2), 94-103. https://doi.org/10.2337/diab.22.2.94
Steil, G. M., Palerm, C. C., Kurtz, N., Voskanyan, G., Roy, A., Paz, S., Kandeel, F. R., 2011. The effect of insulin feedback on closed loop glucose control. The Journal of Clinical Endocrinology & Metabolism 96 (5), 1402-1408. https://doi.org/10.1210/jc.2010-2578
Toffolo, G., Bergman, R. N., Finegood, D. T., Bowden, C. R., Cobelli, C., 1980. Quantitative estimation of beta cell sensitivity to glucose in the intact organism: a minimal model of insulin kinetics in the dog. Diabetes 29 (12), 979-990. https://doi.org/10.2337/diab.29.12.979
Trajanoski, Z., Wach, P., Kotanko, P., Ott, A., Skraba, F., 1993. Pharmacokinetic model for the absorption of subcutaneously injected soluble insulin and monomeric insulin-analogues. Biomedizinische Technik Biomedical Engineering 38 (9), 224-231. https://doi.org/10.1515/bmte.1993.38.9.224
Turksoy, K., Cinar, A., 2014. Adaptive control of artificial pancreas systems-a review. Journal of Healthcare Engineering 5 (1), 1-22. https://doi.org/10.1260/2040-2295.5.1.1
Weinzimer, S. A., Sherr, J. L., Cengiz, E., Kim, G., Ruiz, J. L., Carria, L., Voskanyan, G., Roy, A., Tamborlane, W. V., 2012. Effect of pramlintide on prandial glycemic excursions during closed-loop control in adolescents and young adults with type 1 diabetes. Diabetes Care. URL: http://care.diabetesjournals.org https://doi.org/10.2337/dc12-0330
Yoldi, C., Mayo 2018. Las grasas y las proteínas también cuentan. Guía Diabetes tipo 1, [Online; October 2018]. URL: https://www.diabetes-cidi.org/
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