Evaluation of a novel continuous glucose monitoring-based method for mealtime insulin dosing - the iBolus - in subjects with type 1 diabetes using continuous subcutaneous insulin infusion therapy: a randomized controlled trial

This is a copy of an article published in the Diabetes Technology and Therapeutics © 2012 [copyright Mary Ann Liebert, Inc.]; Diabetes Technology and Therapeutics is available online at: http://online.liebertpub.com.[EN] Objective: Prandial insulin dosing is an empirical practice associated frequently with poor reproducibility in postprandial glucose response. Based on continuous glucose monitoring (CGM), a method for prandial insulin administration (iBolus) is presented and evaluated for people with type 1 diabetes using CSII therapy. Subjects and Methods: An individual patient¿s model for a 5-h postprandial period was obtained from 6-day ambulatory CGM and used for iBolus calculation in 12 patients with type 1 diabetes. In a double-blind, crossover study each patient underwent four meal tests with 40 g or 100 g of carbohydrates (CHOs), both on two occasions. For each meal, the iBolus or the traditional bolus (tBolus) was given before mealtime (t 0) in a randomized order. We measured the postprandial glycemic response as the area under the curve of plasma glucose (AUC-PG0¿5h) and variability as the individual coef¿cient of variation (CV) of AUC-PG0¿5h. The contribution of the insulin-to-CHO ratio, CHO, plasma glucose at t 0 (PGt0), and insulin dose to AUC-PG0¿5h and its CV was also investigated. Results: AUC-PG0¿5h was similar with either bolus for 40-g (iBolus vs. tBolus, 585.5¿127.5 vs. 689.2¿180.7 mg/dL$h) or 100-g (752.1¿237.7 vs. 760.0¿263.2 mg/dL$h) CHO meals. A multiple regression analysis revealed a signi¿cant model only for the tBolus, with PGt0 being the best predictor of AUC-PG0¿5h explaining approximately 50% of the glycemic response. Observed variability was greater with the iBolus (CV, 16.7¿15.3% vs. 10.1¿12.5%) but independent of the factors studied. Conclusions: A CGM-based algorithm for calculation of prandial insulin is feasible, although it does not reduce unpredictability of individual glycemic responses. Causes of variability need to be identi¿ed and analyzed for further optimization of postprandial glycemic control.We are grateful to Mrs. Sara Correa, Fundacion INCLIVA-Hospital Clinico Universitario de Valencia, and Mrs. Geles Viguer, Hospital Clinico Universitario de Valencia, for their invaluable help in conducting the study. We also thanks Dr. Carmine Fanelli, University of Perugia, Dr. Howard Zisser, Sansum Diabetes Research Institute, and Prof. Alberto Ferrer, Universitat Politecnica de Valencia, for their suggestions on study design and data analysis. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007/2013) under grant agreement 252085 and from the Spanish Ministry of Science under grants DPI2010-20764-C02-01 and DPI2011-28112-C04-01.Rossetti, P.; Ampudia Blasco, FJ.; Laguna Sanz, AJ.; Revert Tomás, A.; Vehí Casellas, J.; Ascaso, JF.; Bondía Company, J. (2012). Evaluation of a novel continuous glucose monitoring-based method for mealtime insulin dosing - the iBolus - in subjects with type 1 diabetes using continuous subcutaneous insulin infusion therapy: a randomized controlled trial. Diabetes Technology & Therapeutics. 14(11):1043-1052. https://doi.org/10.1089/dia.2012.0145S10431052141

Robust strategies for glucose control in type 1 diabetes

[EN] Type 1 diabetes mellitus is a chronic and incurable disease that affects millions of people all around the world. Its main characteristic is the destruction (totally or partially) of the beta cells of the pancreas. These cells are in charge of producing insulin, main hormone implied in the control of blood glucose. Keeping high levels of blood glucose for a long time has negative health effects, causing different kinds of complications. For that reason patients with type 1 diabetes mellitus need to receive insulin in an exogenous way. Since 1921 when insulin was first isolated to be used in humans and first glucose monitoring techniques were developed, many advances have been done in clinical treatment with insulin. Currently 2 main research lines focused on improving the quality of life of diabetic patients are opened. The first one is concentrated on the research of stem cells to replace damaged beta cells and the second one has a more technological orientation. This second line focuses on the development of new insulin analogs to allow emulating with higher fidelity the endogenous pancreas secretion, the development of new noninvasive continuous glucose monitoring systems and insulin pumps capable of administering different insulin profiles and the use of decision-support tools and telemedicine. The most important challenge the scientific community has to overcome is the development of an artificial pancreas, that is, to develop algorithms that allow an automatic control of blood glucose. The main difficulty avoiding a tight glucose control is the high variability found in glucose metabolism. This fact is especially important during meal compensation. This variability, together with the delay in subcutaneous insulin absorption and action causes controller overcorrection that leads to late hypoglycemia (the most important acute complication of insulin treatment). The proposals of this work pay special attention to overcome these difficulties. In that way interval models are used to represent the patient physiology and to be able to take into account parametric uncertainty. This type of strategy has been used in both the open loop proposal for insulin dosage and the closed loop algorithm. Moreover the idea behind the design of this last proposal is to avoid controller overcorrection to minimize hypoglycemia while adding robustness against glucose sensor failures and over/under- estimation of meal carbohydrates. The algorithms proposed have been validated both in simulation and in clinical trials.[ES] La diabetes mellitus tipo 1 es una enfermedad crónica e incurable que afecta a millones de personas en todo el mundo. Se caracteriza por una destrucción total o parcial de las células beta del páncreas. Estas células son las encargadas de producir la insulina, hormona principal en el control de glucosa en sangre. Valores altos de glucosa en la sangre mantenidos en el tiempo afectan negativamente a la salud, provocando complicaciones de diversa índole. Es por eso que los pacientes con diabetes mellitus tipo 1 necesitan recibir insulina de forma exógena. Desde que se consiguiera en 1921 aislar la insulina para poder utilizarla en clínica humana, y se empezaran a desarrollar las primeras técnicas de monitorización de glucemia, se han producido grandes avances en el tratamiento con insulina. Actualmente, las líneas de investigación que se están siguiendo en relación a la mejora de la calidad de vida de los pacientes diabéticos, tienen fundamentalmente 2 vertientes: una primera que se centra en la investigación en células madre para la reposición de las células beta y una segunda vertiente de carácter más tecnológico. Dentro de esta segunda vertiente, están abiertas varias líneas de investigación, entre las que se encuentran el desarrollo de nuevos análogos de insulina que permitan emular más fielmente la secreción endógena del páncreas, el desarrollo de monitores continuos de glucosa no invasivos, bombas de insulina capaces de administrar distintos perfiles de insulina y la inclusión de sistemas de ayuda a la decisión y telemedicina. El mayor reto al que se enfrentan los investigadores es el de conseguir desarrollar un páncreas artificial, es decir, desarrollar algoritmos que permitan disponer de un control automático de la glucosa. La principal barrera que se encuentra para conseguir un control riguroso de la glucosa es la alta variabilidad que presenta su metabolismo. Esto es especialmente significativo durante la compensación de las comidas. Esta variabilidad junto con el retraso en la absorción y actuación de la insulina administrada de forma subcutánea favorece la aparición de hipoglucemias tardías (complicación aguda más importante del tratamiento con insulina) a consecuencia de la sobreactuación del controlador. Las propuestas presentadas en este trabajo hacen especial hincapié en sobrellevar estas dificultades. Así, se utilizan modelos intervalares para representar la fisiología del paciente, y poder tener en cuenta la incertidumbre en sus parámetros. Este tipo de estrategia se ha utilizado tanto en la propuesta de dosificación automática en lazo abierto como en el algoritmo en lazo cerrado. Además la principal idea de diseño de esta última propuesta es evitar la sobreactuación del controlador evitando hipoglucemias y añadiendo robustez ante fallos en el sensor de glucosa y en la estimación de las comidas. Los algoritmos propuestos han sido validados en simulación y en clínica.[CA] La diabetis mellitus tipus 1 és una malaltia crònica i incurable que afecta milions de persones en tot el món. Es caracteritza per una destrucció total o parcial de les cèl.lules beta del pàncrees. Aquestes cèl.lules són les encarregades de produir la insulina, hormona principal en el control de glucosa en sang. Valors alts de glucosa en la sang mantinguts en el temps afecten negativament la salut, provocant complicacions de diversa índole. És per això que els pacients amb diabetis mellitus tipus 1 necessiten rebre insulina de forma exògena. Des que s'aconseguís en 1921 aïllar la insulina per a poder utilitzar-la en clínica humana, i es començaren a desenrotllar les primeres tècniques de monitorització de glucèmia, s'han produït grans avanços en el tractament amb insulina. Actualment, les línies d'investigació que s'estan seguint en relació a la millora de la qualitat de vida dels pacients diabètics, tenen fonamentalment 2 vessants: un primer que es centra en la investigació de cèl.lules mare per a la reposició de les cèl.lules beta i un segon vessant de caràcter més tecnològic. Dins d' aquest segon vessant, estan obertes diverses línies d'investigació, entre les que es troben el desenrotllament de nous anàlegs d'insulina que permeten emular més fidelment la secreció del pàncrees, el desenrotllament de monitors continus de glucosa no invasius, bombes d'insulina capaces d'administrar distints perfils d'insulina i la inclusió de sistemes d'ajuda a la decisió i telemedicina. El major repte al què s'enfronten els investigadors és el d'aconseguir desenrotllar un pàncrees artificial, és a dir, desenrotllar algoritmes que permeten disposar d'un control automàtic de la glucosa. La principal barrera que es troba per a aconseguir un control rigorós de la glucosa és l'alta variabilitat que presenta el seu metabolisme. Açò és especialment significatiu durant la compensació dels menjars. Aquesta variabilitat junt amb el retard en l'absorció i actuació de la insulina administrada de forma subcutània afavorix l'aparició d'hipoglucèmies tardanes (complicació aguda més important del tractament amb insulina) a conseqüència de la sobreactuació del controlador. Les propostes presentades en aquest treball fan especial insistència en suportar aquestes dificultats. Així, s'utilitzen models intervalares per a representar la fisiologia del pacient, i poder tindre en compte la incertesa en els seus paràmetres. Aquest tipus d'estratègia s'ha utilitzat tant en la proposta de dosificació automàtica en llaç obert com en l' algoritme en llaç tancat. A més, la principal idea de disseny d'aquesta última proposta és evitar la sobreactuació del controlador evitant hipoglucèmies i afegint robustesa.Revert Tomás, A. (2015). Robust strategies for glucose control in type 1 diabetes [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/56001TESI

Methods for the treatment of uncertainty in dynamical systems: Application to diabetes

[EN] Patients suffering from Type 1 Diabetes are not able to secrete insulin, thus, they have to get it administered externally. Current research is focused on developing an artificial pancreas, a control system that automatically administers insulin according to patient's needs. The work presented here aims to improve the efficiency and safety of control algorithms for artificial pancreas. Glucose-insulin models try to mimic the administration of external insulin, the absorption of carbohydrates, and the influence of both of them in blood glucose concentration. However, these processes are infinitely complex and they are characterized by their high variability. The mathematical models used are often a simplified version which does not include all the process variability and, therefore, they do not always match reality. This deficiency on the models can be addressed by considering uncertainty on their parameters and initial conditions. In this way, the exact values are unknown but they can be bounded by intervals that comprehend all the variability of the considered process. When the value of the parameters and initial conditions is known, there is usually just one possible behaviour. However, if they are bounded by intervals, a set of possible solutions exists. In this case, it is interesting to compute a solution envelope that guarantees the inclusion of all the possible behaviours. A common technique to compute this envelope is the monotonicity analysis of the system. Nevertheless, some overestimation is produced if the system is not fully monotone. In this thesis, several methods and approaches have been developed to reduce, or even eliminate, the overestimation in the computation of solution envelopes, while satisfying the inclusion guarantee. Another problem found during the use of an artificial pancreas is that only the subcutaneous glucose concentration can be measured in real time, with some noise in the measurements. The rest of the system states are unknown, but they could be estimated from this set of noisy measurements by state observers, like Kalman filters. A detailed example is shown at the end of this thesis, where an Extended Kalman Filter is used to estimate in real time insulin concentration based on the food ingested and in periodical measurements of subcutaneous glucose.[ES] Los pacientes que sufren de diabetes tipo 1 no son capaces de secretar insulina, por lo que tienen que administrársela externamente. La investigación actual se centra en el desarrollo de un páncreas artificial, un sistema de control que administre automáticamente la insulina en función de las necesidades del paciente. El trabajo que aquí se presenta tiene como objetivo mejorar la eficiencia y la seguridad de los algoritmos de control para el páncreas artificial. Los modelos de glucosa-insulina tratan de emular la administración externa de la insulina, la absorción de carbohidratos y la influencia de ambos en la concentración de glucosa en sangre. El problema es que estos procesos son infinitamente complejos y se caracterizan por su alta variabilidad. Los modelos matemáticos utilizados suelen ser una versión simplificada que no incluye toda la variabilidad del proceso y, por lo tanto, no coinciden con la realidad. Esta deficiencia de los modelos puede subsanarse considerando inciertos sus parámetros y las condiciones iniciales, de manera que se desconoce su valor exacto pero sí podemos englobarlos en ciertos intervalos que comprendan toda la variabilidad del proceso considerado. Cuando los valores de los parámetros y de las condiciones iniciales son conocidos, existe, por lo general, un único comportamiento posible. Sin embargo, si están delimitados por intervalos se obtiene un conjunto de posibles soluciones. En este caso, interesa obtener una envoltura de las soluciones que garantice la inclusión de todos los comportamientos posibles. Una técnica habitual que facilita el cómputo de esta envoltura es el análisis de la monotonicidad del sistema. Sin embargo, si el sistema no es totalmente monótono la envoltura obtenida estará sobrestimada. En esta tesis se han desarrollado varios métodos para reducir, o incluso eliminar, la sobrestimación en el cálculo de envolturas, al tiempo que se satisface la garantía de inclusión. Otro inconveniente con el que nos encontramos durante el uso de un páncreas artificial es que solo es posible medir en tiempo real, con cierto ruido en la medida, la glucosa subcutánea. El resto de los estados del sistema son desconocidos, pero podrían ser estimados a partir de este conjunto limitado de mediciones con ruido utilizando observadores de estado, como el Filtro de Kalman. Un ejemplo detallado se muestra al final de la tesis, donde se estima en tiempo real la concentración de insulina en plasma en función de la comida ingerida y de mediciones periódicas de la glucosa subcutánea con ayuda de un Filtro de Kalman Extendido.[CA] Els pacients que pateixen de diabetis tipus 1 no són capaços de secretar insulina, motiu pel qual han d'administrar-se-la externament. La investigació actual es centra en el desenvolupament d'un pàncrees artificial, un sistema de control que administre automàticament la insulina en funció de les necessitats del pacient. El treball que ací es presenta té com a objectiu millorar l'eficiència i la seguretat dels algorismes de control per al pàncrees artificial. Els models de glucosa-insulina tracten d'emular l'administració externa de la insulina, l'absorció de carbohidrats i la influència d'ambdós factors en la concentració de glucosa en sang. El problema és que estos processos són infinitament complexos i es caracteritzen per la seua alta variabilitat. Els models matemàtics emprats solen ser una versió simplificada que no inclou tota la variabilitat del procés i, per tant, no coincideixen amb la realitat. Esta deficiència dels models pot esmenar-se considerant incerts els seus paràmetres i les condicions inicials, de manera que es desconeix el seu valor exacte però sí podem englobar-los en certs intervals que comprenguen tota la variabilitat del procés considerat. Quan els valors dels paràmetres i de les condicions inicials són coneguts, existeix, en general, un únic comportament possible. No obstant, si estan delimitats per intervals s'obté un conjunt de possibles solucions. En este cas, interessa obtindre un embolcall de les solucions que assegure la inclusió de tots els comportaments possibles. Una tècnica habitual que facilita el còmput d'este embolcall és l'anàlisi de la monotonicitat del sistema. No obstant, si el sistema no és totalment monòton l'embolcall obtingut estarà sobreestimat. En esta tesi s'han desenvolupat diversos mètodes per a reduir, o fins i tot eliminar, la sobreestimació en el càlcul dels embolcalls, al temps que se satisfà la garantia d'inclusió. Altre inconvenient amb què ens trobem durant l'ús d'un pàncrees artificial és que només és possible mesurar en temps real, amb cert soroll en la mesura, la glucosa subcutània. La resta dels estats del sistema són desconeguts, però podrien ser estimats a partir d'este conjunt limitat de mesures amb soroll utilitzant observadors d'estat, com el Filtre de Kalman. Un exemple detallat es mostra al final de la tesi, on s'estima en temps real la concentració d'insulina en plasma en funció del menjar ingerit i de les mesures periòdiques de la glucosa subcutània amb ajuda d'un Filtre de Kalman Estés.Pereda Sebastián, DD. (2015). Methods for the treatment of uncertainty in dynamical systems: Application to diabetes [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/54121TESI

A decision support system for insulin-dose adjustment in insulin-treated subjects with type 2 diabetes mellitus

The Diabetes Control and Complications Trial (DCCT) and the United Kingdom Prospective Diabetes Study provide motivation for the intensive insulin therapy (IIT) in type 1 and also type 2 diabetes mellitus. Decision support systems (DSS) for the adjustment of insulin dosage in insulin-treated subjects with type 2 diabetes have the potential to attain significant importance in clinical practice by offering the means to improve glycaemic control. The aims of the research were to extend the existing Diabetes Insulin Advisory System (DIAS) model of carbohydrate metabolism with a component representing the insulin secretion present in subjects with type 2 diabetes and to develop a decision support system, DIAS-NIDDM, to assist in clinical practice with the adjustment of insulin dosage in insulin-treated subjects with type 2 diabetes. In relation to assessing the long-term complications of diabetes, the aim was to incorporate a model that predicts steady state HbA)c concentrations in response to changes in diet and insulin therapy. Furthermore, the research evaluated DIAS-NIDDM with regard to performance, clinical utility, and safety of its advice on retrospective data to justify prospective clinical testing of DIAS-NIDDM. The new model, implemented using causal probabilistic networks (CPN), represents the insulin secretion present in subjects with type 2 diabetes and assumes a linear relationship between plasma glucose concentration and endogenous insulin secretion. DIAS-NIDDM was used to predict patient-specific plasma glucose profiles and advise on insulin doses during a pilot study in eight subjects with type 2 diabetes, with five subjects treated by insulin. Case studies showed that the advice is plausible and safe. However, a systematic error has been identified when the system predicted BG values in the hyperglycaemic BG range. Another evaluation step was performed as a pilot peer assessment of the insulin dose advice generated by DIAS-NIDDM. The peer blind assessment provided valuable information about the competence of DIAS-NIDDM compared to diabetes specialists, confirming the clinical utility and the safety of the advice. However, in the peer review study, DIAS-NIDDM recommendations performed less well than advice from a clinical diabetologist, as the system does not use the subject demoghraphic data to assess the feasibility of the recommended therapy in aged and insulin resistant subjects. A new model using stochastic differential equations has been built to describe the relationship between DIAS-NIDDM predicted plasma glucose levels and glycated haemoglobin (HbAic) at steady state conditions. The model uses two physiological compartments to represent the glycated and unglycated haemoglobin where the glycation process is controlled by the plasma glucose concentration. The HbAic assay has been modelled, in a novel approach, as a separate process in order to deal with the glycation-induced heterogeneity and the mix of cell life spans in the sample. A retrospective pilot study has been performed in order to carry out a preliminary validation of the glycation model. The accuracy of the model was excellent when predicting thirty-two HbA)C retrospective measurements. In conclusion, the results confirm that DIAS-NIDDM can generate advice that is similar in performance to the advice recommended by diabetes specialists and that the advice is safe, plausible, and of clinical utility. The system can predict steady state HbAic in response to changes in diet and insulin therapy. Despite possible further optimisations of the system, prospective clinical testing of DIAS-NIDDM is justified. The thesis, nevertheless, identifies DIAS-NIDDM as a decision support system with valuable potential

Regional Intestinal Drug Absorption

The gastrointestinal tract (GIT) can be broadly divided into several regions: the stomach, the small intestine (which is subdivided to duodenum, jejunum, and ileum), and the colon. The conditions and environment in each of these segments, and even within the segment, are dependent on many factors, e.g., the surrounding pH, fluid composition, transporters expression, metabolic enzymes activity, tight junction resistance, different morphology along the GIT, variable intestinal mucosal cell differentiation, changes in drug concentration (in cases of carrier-mediated transport), thickness and types of mucus, and resident microflora. Each of these variables, alone or in combination with others, can fundamentally alter the solubility/dissolution, the intestinal permeability, and the overall absorption of various drugs. This is the underlying mechanistic basis of regional-dependent intestinal drug absorption, which has led to many attempts to deliver drugs to specific regions throughout the GIT, aiming to optimize drug absorption, bioavailability, pharmacokinetics, and/or pharmacodynamics. In the book "Regional Intestinal Drug Absorption: Biopharmaceutics and Drug Formulation" we aim to highlight the current progress and to provide an overview of the latest developments in the field of regional-dependent intestinal drug absorption and delivery, as well as pointing out the unmet needs of the field

REGULATION OF BLOOD GLUCOSE IN TYPE I DIABETIC PATIENTS

Ph.DDOCTOR OF PHILOSOPH

Modeling the effect of physical activity on postprandial glucose turnover

In healthy subjects, glucose regulation relies on a complex control system that keeps blood glucose level within a narrow range around its basal value. A common element that offers a net benefit for most individuals with and without diabetes is regular physical activity, which is known to enhance insulin sensitivity, improve glycemic control and reduce the risk of cardiovascular mortality. Nowadays numerous studies have demonstrated increased rate of glucose uptake (Rd) and rate of endogenous glucose production (EGP) during physical activity in individuals with and without diabetes in the postabsorptive state, while very few have examined the effects of exercise in the postprandial state although many people, with and without diabetes, exercise a few hours after a meal. A method for the quantification of the effect and effect size of exercise on insulin sensitivity and a physiological model quantitatively describing the effect of exercise on glucose turnover in the postprandial state have never been developed. This represents a significant knowledge gap, especially in type 1 diabetes, because this information could be incorporated into currently available artificial pancreas control algorithms, thus extending their applicability to treat people with type 1 diabetes. However, such tools will need to be developed and tested in healthy subjects before validating in those with diabetes. In this work data of 12 healthy individuals who underwent a triple-tracer mixed-meal and a moderate-intensity exercise session 2 hours after meal ingestion for 75 minutes have been used. The tracer-to-tracee clamp method was used to accurately estimate postprandial glucose turnover continuously after the meal, during and after exercise by clamping tracer-to-tracee ratios in order to minimize non-steady-state errors. Since it is almost impossible to realize a "perfect" clamp of the plasma tracer-to-tracee ratio, the use of models, to compensate the non-steady-state errors, is needed. Use of models requires the estimation of derivatives both for tracer-to-tracee ratio and glucose signals and, due to ill-conditioning, this issue is generally solved via regularized deconvolution. However, an implicit assumption of standard regularized deconvolution is that, in a Bayesian embedding, expectations on smoothness of the unknown input can be formalized by describing it a priori as the multiple integration of a stationary white noise process but, because of physical activity, signals represented marked nonstationarity. We solved the problem by resorting to an improved stochastic deconvolution method, in order to account for nonstationarity introduced by exercise. Fluxes analysis showed that during exercise session EGP rose, which can be explained by both falling insulin and rising glucagon concentrations, while glucose concentrations fell and Rd plateaued, which can be explained by increasing muscle uptake by both insulin-independent and -dependent mechanisms. In order to quantify the effect and effect size of exercise on net insulin sensitivity (SI), i.e. the ability of insulin to stimulate glucose disposal and suppress endogenous glucose production, we developed a method able to calculate net insulin sensitivity and evaluate the relative contribution of liver and disposal insulin sensitivity based on glucose fluxes data. SI was estimated first using data of first 2 hours after the meal, i.e. in absence of physical activity, and then using the data of the whole experiment, i.e. in presence of physical activity. We found that net SI increases by almost 75% during moderate-intensity exercise and that this increase is associated to insulin-dependent glucose disposal. Furthermore, we validated these results by calculating an index of net insulin sensitivity, both in absence and presence of physical activity, based on an integral formula using glucose and insulin concentration data. We found a strong correlation between net SI indices calculated with the two methods. The results on effect size of physical activity on SI have been incorporated into the UVA/Padova T1DM simulator in order to suggest the best strategy that could be adopted during artificial pancreas clinical trials that involves a session of moderate physical activity. We showed that, in order to prevent hypoglycemia during and after exercise, any control algorithm would benefit by knowing in advance of upcoming physical activity and, if patient-specific basal insulin reduction pattern is not available, an optimal basal reduction strategy has been proposed. However, the method for the quantification of the effect size of exercise on insulin sensitivity was not able to tease out the insulin-independent effect of exercise on glucose uptake. Therefore, to discriminate the effect of exercise on insulin-dependent and -independent glucose turnover, the development of a mathematical model to assess the effect of physical activity on glucose kinetics has been approached. A set of models of increasing complexity have been developed and selection was tackled using standard criteria (e.g. ability to describe the data, precision of parameter estimates, model parsimony, residual independence). The models proposed well fitted the data and allowed the estimation of physiologically interpretable parameters quantifying the effect of physical activity on glucose turnover

Multimodel Approaches for Plasma Glucose Estimation in Continuous Glucose Monitoring. Development of New Calibration Algorithms

ABSTRACT Diabetes Mellitus (DM) embraces a group of metabolic diseases which main characteristic is the presence of high glucose levels in blood. It is one of the diseases with major social and health impact, both for its prevalence and also the consequences of the chronic complications that it implies. One of the research lines to improve the quality of life of people with diabetes is of technical focus. It involves several lines of research, including the development and improvement of devices to estimate "online" plasma glucose: continuous glucose monitoring systems (CGMS), both invasive and non-invasive. These devices estimate plasma glucose from sensor measurements from compartments alternative to blood. Current commercially available CGMS are minimally invasive and offer an estimation of plasma glucose from measurements in the interstitial fluid CGMS is a key component of the technical approach to build the artificial pancreas, aiming at closing the loop in combination with an insulin pump. Yet, the accuracy of current CGMS is still poor and it may partly depend on low performance of the implemented Calibration Algorithm (CA). In addition, the sensor-to-patient sensitivity is different between patients and also for the same patient in time. It is clear, then, that the development of new efficient calibration algorithms for CGMS is an interesting and challenging problem. The indirect measurement of plasma glucose through interstitial glucose is a main confounder of CGMS accuracy. Many components take part in the glucose transport dynamics. Indeed, physiology might suggest the existence of different local behaviors in the glucose transport process. For this reason, local modeling techniques may be the best option for the structure of the desired CA. Thus, similar input samples are represented by the same local model. The integration of all of them considering the input regions where they are valid is the final model of the whole data set. Clustering is tBarceló Rico, F. (2012). Multimodel Approaches for Plasma Glucose Estimation in Continuous Glucose Monitoring. Development of New Calibration Algorithms [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17173Palanci