Browsing by Author "Garelli, Fabricio"
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capítulo de libro.listelement.badge The ARG algorithm: clinical trials in Argentina(2019) Colmegna, Patricio; Garelli, Fabricio; De Battista, Hernán; Bianchi, Fernando D.; Sánchez-Peña, Ricardo"The objective of this work is to present a brief review of the control design problem for glucose regulation in T1DM. In particular, control-oriented models, and robust and time-varying controllers will be mentioned. Characteristics of diabetes in general and T1DM in particular in the context of Latin America will be described. Finally, the Automatic Regulation of Glucose (ARG) algorithm will be presented, including in silico and clinical results."artículo de publicación periódica.listelement.badge Artificial pancreas: clinical study in Latin America without premeal insulin boluses(2018-09) Sánchez-Peña, Ricardo; Colmegna, Patricio; Garelli, Fabricio; De Battista, Hernán; García Violini, Demián; Moscoso-Vásquez, Marcela; Rosales, Nicolás; Fushimi, Emilia; Campos-Náñez, Enrique; Breton, Marc; Beruto, Valeria; Scibona, Paula; Rodriguez, Cintia; Giunta, Javier; Simonovich, Ventura; Belloso, Waldo H.; Cherñavvsky, Daniel; Grosembacher, Luis"Background: Emerging therapies such as closed-loop (CL) glucose control, also known as artificial pancreas (AP) systems, have shown significant improvement in type 1 diabetes mellitus (T1DM) management. However, demanding patient intervention is still required, particularly at meal times. To reduce treatment burden, the automatic regulation of glucose (ARG) algorithm mitigates postprandial glucose excursions without feedforward insulin boluses. This work assesses feasibility of this new strategy in a clinical trial. Methods: A 36-hour pilot study was performed on five T1DM subjects to validate the ARG algorithm. Subjects wore a subcutaneous continuous glucose monitor (CGM) and an insulin pump. Insulin delivery was solely commanded by the ARG algorithm, without premeal insulin boluses. This was the first clinical trial in Latin America to validate an AP controller. Results: For the total 36-hour period, results were as follows: average time of CGM readings in range 70-250 mg/dl: 88.6%, in range 70-180 mg/dl: 74.7%, <70 mg/dl: 5.8%, and <50 mg/dl: 0.8%. Results improved analyzing the final 15-hour period of this trial. In that case, the time spent in range was 70-250 mg/dl: 94.7%, in range 70-180 mg/dl: 82.6%, <70 mg/dl: 4.1%, and <50 mg/dl: 0.2%. During the last night the time spent in range was 70-250 mg/dl: 95%, in range 70-180 mg/dl: 87.7%, <70 mg/dl: 5.0%, and <50 mg/dl: 0.0%. No severe hypoglycemia occurred. No serious adverse events were reported. Conclusions: The ARG algorithm was successfully validated in a pilot clinical trial, encouraging further tests with a larger number of patients and in outpatient settings."ponencia en congreso.listelement.badge Artificial Pancreas: first clinical trials in Argentina(2017-07) Sánchez-Peña, Ricardo; Colmegna, Patricio; Grosembacher, Luis; Breton, Marc; De Battista, Hernán; Garelli, Fabricio; Belloso, Waldo H.; Campos-Náñez, Enrique; Simonovich, Ventura; Beruto, Valeria; Scibona, Paula; Cherñavvsky, Daniel"The first clinical trials using an Artificial Pancreas (AP) in Latin America have been defined in 2 stages. The first stage was carried out in November 2016 with the UVA controller (developed by the Center for Diabetes Technology and already clinically tested), and the second will be performed during the first semester of 2017 with the ARG (Automatic Regulation of Glucose) algorithm (developed by ITBA, UNQ, and UNLP in Argentina). Both tests are based on the DiAs (Diabetes Assistant) from the UVA, and are performed in the HIBA on 5 patients with Type 1 Diabetes Mellitus (T1DM), for 36 hours. For the first stage, Open-Loop (OL) insulin boluses were applied before meals and patient's physical activity was included. On the other hand, for the second stage, patients will not be involved in physical activity, but no OL insulin boluses will be injected before meals. In this work, experimental results from the first stage with the UVA controller, and preliminary results with the ARG control algorithm tested on the UVA/Padova simulator are presented. Due to the final paper deadline, the experimental results from the second stage are not included here, but will be presented at the IFAC World Congress."artículo de publicación periódica.listelement.badge Automatic regulatory control in type 1 diabetes without carbohydrate counting(2018-05) Colmegna, Patricio; Garelli, Fabricio; De Battista, Hernán; Sánchez-Peña, Ricardo"A new approach to automatically regulate the glucose level in type 1 diabetes is presented in this work. This is the so-called Automatic Regulation of Glucose (ARG) algorithm, which is based on a switched Linear Quadratic Gaussian (LQG) inner controller, combined with an outer sliding mode safety loop with Insulin on Board (IOB) constraints. In silico and in vivo results without feedforward insulin boluses delivered at meal times indicate that safe blood glucose control can be achieved by the proposed controller. This controller is simple to migrate to well-known hardware platforms, and intuitive to tune using a priori clinical information."artículo de publicación periódica.listelement.badge Control no-híbrido de glucemia ensayado en pacientes ambulatorios con Diabetes Tipo 1(2022-07) Garelli, Fabricio; Fushimi, Emilia; Rosales, Nicolás; Arambarri, Delfina; Serafini, María Cecilia; De Battista, Hernán; Grosembacher, Luis; Sánchez-Peña, Ricardo"En este trabajo se presenta la experiencia argentina en el problema de regulación de los niveles de glucosa en sangre para pacientes con Diabetes Mellitus Tipo 1 (insulino-dependientes), denominado Páncreas Artificial. El grupo de trabajo ha realizado 3 pruebas clínicas, las primeras en Latinoamérica. Las dos primeras fueron concretadas en 2016 y 2017, ambas en el Hospital Italiano de Buenos Aires (HIBA) con 5 pacientes adultos durante 36 hs. En la segunda de ellas se utilizó un nuevo algoritmo de control de lazo cerrado puro (sin bolo prandial), llamado ARG (Automatic Regulation of Glucose) y basado en un control LQG conmutado en combinación con una capa de seguridad llamada SAFE (Safety Auxiliary Feedback Element). Más recientemente y en plena pandemia de COVID-19 se llevó a cabo la primera prueba ambulatoria, realizada en 2021 en un hotel con 5 pacientes durante 6 días. En esta tercera prueba además, se utilizó una plataforma desarrollada por la Universidad Nacional de La Plata (UNLP), denominada InsuMate. Ésta conecta el celular con la bomba de insulina y el monitor de glucosa, aloja el algoritmo de control y permite el monitoreo remoto de múltiples pacientes. Los resultados obtenidos sugieren que el uso del algoritmo ARG en forma ambulatoria es factible, seguro y eficaz en comparación con la terapia usual. Asimismo, la plataforma InsuMate resultó ser intuitiva y sencilla para los usuarios, tanto médicos como pacientes participantes del ensayo, logrando un tiempo de funcionamiento del lazo cerrado superior al 95 %."artículo de publicación periódica.listelement.badge Control-oriented model with intra-patient variations for an artificial pancreas(2020) Moscoso-Vásquez, Marcela; Colmegna, Patricio; Rosales, Nicolás; Garelli, Fabricio; Sánchez-Peña, Ricardo"In this work, a low-order model designed for glucose regulation in Type 1 Diabetes Mellitus (T1DM) is obtained from the UVA/Padova metabolic simulator. It captures not only the nonlinear behavior of the glucose-insulin system, but also intrapatient variations related to daily insulin sensitivity (SI) changes. To overcome the large inter-subject variability, the model can also be personalized based on a priori patient information. The structure is amenable for linear parameter varying (LPV) controller design, and represents the dynamics from the subcutaneous insulin input to the subcutaneous glucose output. The eficacy of this model is evaluated in comparison with a previous control-oriented model which in turn is an improvement of previous models. Both models are compared in terms of their open- and closed-loop differences with respect to the UVA/Padova model. The proposed model outperforms previous T1DM control oriented models, which could potentially lead to more robust and reliable controllers for glycemia regulation."artículo de publicación periódica.listelement.badge First outpatient clinical trial of a full closed-loop artificial pancreas system in South America(2022-05) Garelli, Fabricio; Fushimi, Emilia; Rosales, Nicolás; Arambarri, Delfina; Mendoza, Leandro; Serafini, María Cecilia; Moscoso-Vásquez, Marcela; Stasi, Marianela; Duette, Patricia; García Arabehety, Julia; Giunta, Javier; De Battista, Hernán; Sánchez-Peña, Ricardo; Grosembacher, Luis"The first two studies of an artificial pancreas (AP) system carried out in Latin America took place in 2016 (phase 1) and 2017 (phase 2). They evaluated a hybrid algorithm from the University of Virginia (UVA) and the automatic regulation of glucose (ARG) algorithm in an inpatient setting using an AP platform developed by the UVA. The ARG algorithm does not require carbohydrate (CHO) counting and does not deliver meal priming insulin boluses. Here, the first outpatient trial of the ARG algorithm using an own AP platform and doubling the duration of previous phases is presented."artículo de publicación periódica.listelement.badge Non-pharmaceutical intervention to reduce COVID-19 impact in Argentina(2021-06-21) García Violini, Demián; Sánchez-Peña, Ricardo; Moscoso-Vásquez, Marcela; Garelli, Fabricio"This work is focused on the multilevel control of the population confinement in the city of Buenos Aires and its surroundings due to the pandemic generated by the COVID-19 outbreak. The model used here is known as SEIRD and two objectives are sought: a time-varying identification of the infection rate and the inclusion of a controller. A control differential equation has been added to regulate the transitions between confinement and normal life, according to five different levels. The plasma treatment from recovered patients has also been considered in the control algorithm. Using the proposed strategy the ICU occupancy is reduced, and as a consequence, the number of deaths is also decreased."artículo de publicación periódica.listelement.badge Non-pharmaceutical intervention to reduce COVID-19 impact in Argentina(2022-05) García Violini, Demián; Sánchez-Peña, Ricardo; Moscoso-Vásquez, Marcela; Garelli, Fabricio"This work is focused on the multilevel control of the population confinement in the city of Buenos Aires and its surroundings due to the pandemic generated by the COVID-19 outbreak. The model used here is known as SEIRD and two objectives are sought: a time-varying identification of the infection rate and the inclusion of a controller. A control differential equation has been added to regulate the transitions between confinement and normal life, according to five different levels. The plasma treatment from recovered patients has also been considered in the control algorithm. Using the proposed strategy the ICU occupancy is reduced, and as a consequence, the number of deaths is also decreased."artículo de publicación periódica.listelement.badge Online adjustable linear parameter-varying controller for artificial pancreas systems(Elsevier, 2023-06) Bianchi, Fernando D.; Sánchez-Peña, Ricardo; Garelli, FabricioThe purpose of this article is to present a non-hybrid fully closed-loop controller for the Artificial Pancreas (AP) problem focused on long-term clinical trials and home-use applications. It includes physical activity (PA) and unannounced meals. The controller is based on a robust gain-scheduled algorithm with a Linear Parameter-Varying (LPV) structure. It takes into account the time-varying dynamics of the problem by adapting itself in real-time according to measured glucose levels, and allows online fine-tuning during tests and periodic evaluations without the need of a controller redesign. The proposed fully parameterized LPV control adds several features to our previous results, accounts for the main perturbations of the AP problem and simplifies its implementation. To help in the parameter fine-tuning, a methodology based on clinical information is proposed. In-silico tests show that the achieved performance is similar or better than our previous Automatic Regulation of Glucose (ARG) algorithm, tested in two clinical trials, with the addition of the features mentioned before.artículo de publicación periódica.listelement.badge Remote glucose monitoring platform for multiple simultaneous patients at coronavirus disease 2019 intensive care units: case report including adults and children(2021) Garelli, Fabricio; Rosales, Nicolás; Fushimi, Emilia; Arambarri, Delfina; Mendoza, Leandro; De Battista, Hernán; Sánchez-Peña, Ricardo; García Arabehety, Julia; Distefano, Sabrina; Barcala, Consuelo; Giunta, Javier; Las Heras, Marcos; Martínez Mateu, Carolina; Prieto, Mariana; San Román, Eduardo; Krochik, Gabriela; Grosembacher, Luisponencia en congreso.listelement.badge Unannounced meal analysis of the ARG algorithm(2019-07) Fushimi, Emilia; Colmegna, Patricio; De Battista, Hernán; Garelli, Fabricio; Sánchez-Peña, Ricardo"One of the main challenges in automatic glycemic regulation in patients with type 1 diabetes (T1D) is to dispense with carbohydrate counting. In this context, we propose to equip a previously introduced switched Linear Quadratic Gaus-sian (LQG) controller—the so-called Automatic Regulation of Glucose (ARG) algorithm—with an automatic switching signal generator (SSG). The ARG algorithm not only regulates the basal insulin infusion rate but also generates feedback insulin spikes at meal times, i.e., no open-loop insulin boluses are needed to mitigate postprandial glucose excursions. However, in its former version, it was required to announce the meal time. In this work, the performance of the ARG algorithm combined with the proposed SSG is assessed in silico with unannounced meals. In addition, the response of the SSG is estimated using clinical data obtained with the ARG algorithm in the first-ever artificial pancreas (AP) trials carried out in Latin America."