Browsing by Author "Fushimi, Emilia"
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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."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 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 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."