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Objectives: To describe the trends and characteristics of the worldwide scientific production on the use of artificial pancreas (AP) in the management of diabetes mellitus (DM). Materials and Methods: Scientific papers published between 2017 and 2022 were retrieved from the Scopus database using relevant keywords. Only original articles, reviews, and short surveys were included. The metadata were exported to the SciVal software for retrieving quantitative data and the main characteristics such as journals, authors, institutions, journal metrics by quartiles, subcategories, and collaborative networks were extracted. Results: A total of 642 articles were included after applying the inclusion/exclusion criteria: original articles, 489; reviews, 151; and short surveys, 2. The most common type of collaboration was at the national level (38.3%; citations per publication: 22.3; field-weighted citation index [FWCI]: 2.2) followed by international collaboration (29.4%; citations per publication: 19.6; FWCI: 1.94). More than 70% of articles in each year were published in journals listed in Q1. Two journals, Diabetes Technology and Therapeutics and Journal of Diabetes Science and Technology, accounted for about 22% of all publications. Six of the top 10 universities were from the United States, with The University of Virginia having the most publications (n = 54; 59 authors; citations per publication: 38.4; FWCI: 3.73). Conclusions: The findings of this study highlight that most research on this topic is published in high-quality journals and has a good citation impact. Notably, most research has been conducted in developed countries, thereby indicating the need for research efforts in this field from developing countries.
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BACKGROUND: 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. METHOD: Phase 3 involved the evaluation of the ARG algorithm in five adult participants (n = 5) during 72 hours of closed-loop (CL) and 72 hours of open-loop (OL) control in an outpatient setting. This trial was performed with an own AP and remote monitoring platform developed from open-source resources, called InsuMate. The meals tested ranged its CHO content from 38 to 120 g and included challenging meals like pasta. Also, the participants performed mild exercise (3-5 km walks) daily. The clinical trial is registered in ClinicalTrials.gov with identifier: NCT04793165. RESULTS: The ARG algorithm showed an improvement in the time in hyperglycemia (52.2% [16.3%] OL vs 48.0% [15.4%] CL), time in range (46.9% [15.6%] OL vs 50.9% [14.4%] CL), and mean glucose (188.9 [25.5] mg/dl OL vs 186.2 [24.7] mg/dl CL) compared with the OL therapy. No severe hyperglycemia or hypoglycemia episodes occurred during the trial. The InsuMate platform achieved an average of more than 95% of the time in CL. CONCLUSION: The results obtained demonstrated the feasibility of outpatient full CL regulation of glucose levels involving the ARG algorithm and the InsuMate platform.
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Diabetes Mellitus Tipo 1 , Hiperglicemia , Pâncreas Artificial , Adulto , Humanos , Algoritmos , Glicemia , Automonitorização da Glicemia , Diabetes Mellitus Tipo 1/tratamento farmacológico , Glucose , Hiperglicemia/tratamento farmacológico , Hipoglicemiantes , Insulina , Sistemas de Infusão de Insulina , Pacientes Ambulatoriais , América do SulRESUMO
Type 1 diabetes mellitus is a disease that affects millions of people around the world. Recent progress in embedded devices has allowed the development of artificial pancreas that can pump insulin subcutaneously to automatically regulate blood glucose levels in diabetic patients. In this work, a Lyapunov-based intelligent controller using artificial neural networks is proposed for application in automated insulin delivery systems. The adoption of an adaptive radial basis function network within the control scheme allows regulation of blood glucose levels without the need for a dynamic model of the system. The proposed model-free approach does not require the patient to inform when they are going to have a meal and is able to deal with inter- and intrapatient variability. To ensure safe operating conditions, the stability of the control law is rigorously addressed through a Lyapunov-like analysis. In silico analysis using virtual patients are provided to demonstrate the effectiveness of the proposed control scheme, showing its ability to maintain normoglycemia in patients with type 1 diabetes mellitus. Three different scenarios were considered: one long- and two short-term simulation studies. In the short-term analyses, 20 virtual patients were simulated for a period of 7 days, with and without prior basal therapy, while in the long-term simulation, 1 virtual patient was assessed over 63 days. The results show that the proposed approach was able to guarantee a time in the range above 95% for the target glycemia in all scenarios studied, which is in fact well above the desirable 70%. Even in the long-term analysis, the intelligent control scheme was able to keep blood glucose metrics within clinical care standards: mean blood glucose of 119.59 mg/dL with standard deviation of 32.02 mg/dL and coefficient of variation of 26.78%, all below the respective reference values.
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INTRODUCTION: Automated insulin delivery (AID) systems, known as artificial pancreas or closed-loop glucose control systems, have been developed to improve the glycemic outcomes of people with type 1 diabetes. These systems use a control algorithm that automatically modifies the amount of insulin infused into a patient based on real-time blood glucose measurements. This study presents a summary of key clinical and technical issues related to the development of the first commercial AID systems and their evolution into commercial biomedical devices. AREAS COVERED: Highlights of each AID system are summarized through timelines, ranging from the definition of the core strategy of the control algorithm to the practical application and subsequent commercial approval. Tabulated information regarding the conducted main clinical studies is also presented. EXPERT OPINION: Insulin therapy has evolved up to the current commercial AID systems available, which have provided patients access to a safer and more effective therapy owing to automatic adjustments to insulin. However, this technology is relatively new and can be significantly improved. Limitations include the resistance of healthcare providers, high costs, and the availability of this treatment. The future of this technology is directed toward obtaining fully automatic control systems.
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Diabetes Mellitus Tipo 1 , Pâncreas Artificial , Humanos , Sistemas de Infusão de Insulina , Diabetes Mellitus Tipo 1/tratamento farmacológico , Insulina/uso terapêutico , Glicemia , Automonitorização da GlicemiaRESUMO
INTRODUCTION: Artificial pancreas systems usually define an insulin-on-board constraint (IOB¯) for safety schemes to limit the insulin infusion and avoid hypoglycemia during the closed-loop performance. Several methods have been proposed with impractical considerations requiring information from the prandial events or complex procedures for ambulatory use. METHODS: This paper presents a simple method that consists of two novel rules that allow finding an IOB¯ based only on common clinical parameters that do not require patient intervention. The method robustness was evaluated using a control system coupled to a safety layer under demanding scenarios implemented on the FDA-approved simulator for preclinical studies. RESULTS: The method maintains a safe performance, even in the face of interpatient variability, hybrid and fully automatic implementations of an artificial pancreas system, and uncertain settings. Both proposed rules work as effectively or even better and without the patient intervention than other methods that have already been clinically validated. CONCLUSION: This method can be used to define a constant IOB¯ that ensures performance and safety of the control system, even under scenarios with incorrect clinical data. Unlike other methods, this method only requires reliable information that is easily obtained from the patient, such as their total daily dose of insulin or body mass.
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Diabetes Mellitus Tipo 1 , Pâncreas Artificial , Algoritmos , Glicemia , Humanos , Hipoglicemiantes/efeitos adversos , Insulina , Sistemas de Infusão de InsulinaRESUMO
The aim of control strategies for artificial pancreas systems is to calculate the insulin doses required by a subject with type 1 diabetes to regulate blood glucose levels by reducing hyperglycemia and avoiding the induction of hypoglycemia. Several control formulations developed for this end involve a safety constraint given by the insulin on board (IOB) estimation. This constraint has the purpose of reducing hypoglycemic episodes caused by insulin stacking. However, intrapatient variability constantly changes the patient's response to insulin, and thus, an adaptive method is required to restrict the control action according to the current situation of the subject. In this work, the control action computed by an impulsive model predictive controller is modulated with a safety layer to satisfy an adaptive IOB constraint. This constraint is established with two main steps. First, upper and lower IOB bounds are generated with an interval model that accounts for parameter uncertainty, and thus, define the possible system responses. Second, the constraint is selected according to the current value of glycemia, an estimation of the plant-model mismatch, and their corresponding first and second time derivatives to anticipate the changes of both glucose levels and physiological variations. With this strategy satisfactory results were obtained in an adult cohort where random circadian variability and sensor noise were considered. A 92% time in normoglycemia was obtained, representing an increase of time in range compared to previous MPC strategies, and a reduction of time in hypoglycemia to 0% was achieved without dangerously increasing the time in hyperglycemia.
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Hiperglicemia , Hipoglicemia , Pâncreas Artificial , Adulto , Algoritmos , Humanos , Hipoglicemia/prevenção & controle , Hipoglicemiantes/uso terapêutico , Insulina/uso terapêutico , Sistemas de Infusão de InsulinaRESUMO
BACKGROUND: Artificial pancreas is a well-known research topic devoted to achieving better glycemic outcomes that has been attracting increasing attention over the years. However, there is a lack of systematic, chronological, and synthesizing studies that show the background of the knowledge generation in this field. This study implements a bibliometric analysis to recognize the main documents, type of publications, research categories, countries, keywords, organizations, and authors related to this topic. METHODS: Web of Science core collection database was accessed from 2000 to 2020 in order to select high-quality scientific documents based on a specific search query. Bibexcel, MS Excel, Power BI, R-Studio, VOSviewer, and CorText software were used for a descriptive and network analysis based on the local database obtained. Bibliometric parameters as the h-index, frequencies, co-authorship and co-ocurrences were computed. RESULTS: A total of 756 documents were included that show a growing scientific production on this topic with an increasing contribution from engineering. Outstanding authors, organizations, and countries were identified. An analysis of trends in research was conducted according to the scientific categories of the Web of Science database to identify the main research interests of the last 2 decades and the emerging areas with greater prominence in the coming years. A keyword network analysis allowed to identify the main stages in the development of the AP research over time. CONCLUSIONS: Results reveal a comprehensive background of the knowledge generation for the AP topic during the last 2 decades, which has been strengthened with international collaborations and a remarkable interdisciplinarity between endocrinology and engineering, giving rise to a growing number of research areas over time, where computer science and medical informatics stand out as the main emerging research areas.
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Pâncreas Artificial , Bibliometria , Bases de Dados Factuais , Humanos , SoftwareRESUMO
BACKGROUND: Artificial pancreas design using subcutaneous insulin infusion without pre-meal feed-forward boluses often induces an over-response leading to hypoglycemia due to the increase of blood insulin concentration sustained in time. The objective of this work was to create an algorithm for controlling the function of insulin pumps in closed-loop systems to improve blood glucose management in type 1 diabetic patients by mimicking the pulsatile behaviour of the pancreas. METHODS: A controller tuned in a pulsatile way promotes damped oscillations of blood insulin concentration injected through an insulin pump. We tested it in a simulated environment, using nine 'in silica' subjects. The control algorithm is founded on feedback linearization where through a change of variables, the nonlinear system turns into an equivalent linear system, suitable for implementing through a PID controller. We compared the results obtained 'in silica' with the volume injected by an insulin pump controlled by this algorithm. RESULTS: The use of this algorithm resulted in a pulsatile control of postprandial blood glucose concentration, avoiding hypoglycaemic episodes. The results obtained 'in silica' were replicated in a real pump 'in vitro'. CONCLUSIONS: With this proposed linear system, an appropriate control input can be designed. The controller works with a damped pulsatile pattern making the insulin infusion from the pump and blood insulin concentration pulsatile. This operational would improve the performance of an artificial pancreas.
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Diabetes Mellitus Tipo 1 , Pâncreas Artificial , Algoritmos , Glicemia , Automonitorização da Glicemia , Diabetes Mellitus Tipo 1/tratamento farmacológico , Humanos , Hipoglicemiantes , Insulina , PâncreasRESUMO
Advanced diabetes technologies have produced increasingly favorable outcomes compared to older treatments. Disparities in practice resources have led to a treatment disparity by clinical setting, where endocrinologists typically prescribe far more such technologies than primary care providers (PCPs). Fully automated artificial pancreas systems (APS), which combine technologies to deliver and adjust insulin dosing continuously in response to automatic and continuous glucose monitoring, may be more straightforward for PCPs to prescribe and manage, therefore extending their benefit to more patients. We aimed to assess willingness of PCPs to prescribe advanced diabetes technologies through a cross-sectional survey of PCPs from 4 geographically diverse centers. While respondents were uncomfortable initiating (63 of 72, 88%) or adjusting (64 of 72, 89%) traditional insulin pumps, their views on APS were quite different: 71 of 76 (93%) saw advantages to prescribing APS by PCPs rather than only endocrinologists. Most would consider prescribing APS for type 1 diabetes (58 of 76, 76%) and type 2 diabetes (52 of 76, 68%). No differences were seen among attendings, residents, or nurse practitioners. APS were much more acceptable than traditional insulin pumps among this primary care sample. If successful, primary care management of closed-loop APS would greatly increase access to such therapies and reduce disparities among those patients who face more difficulty accessing subspecialty care than they do primary care.
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Current technological advances have brought closer to reality the project of a safe, portable, and efficient artificial pancreas for people with type 1 diabetes (T1D). Among the developed control strategies for T1D, model predictive control (MPC) has been emphasized in literature as a promising control for glucose regulation. However, these control strategies are commonly designed in a computer environment, regardless of the limitations of a portable device. In this paper, the performances of six embedded platforms and three open-source optimization solver algorithms are assessed for T1D treatment. Their advantages and limitations are clarified using four MPC formulations of increasing complexity and a hardware-in-the-loop methodology to evaluate glucose control in virtual adult subjects. The performance comparison includes the execution time, the difference concerning the evolution obtained in MATLAB, the processor temperature, energy consumption, time percentage in normoglycemia, and the number of hypo- and hyperglycemic events. Results show that Quadprog is the package that faithfully follows the results obtained with control strategies designed and tuned on a computer with the MATLAB software. In addition, the Raspberry Pi 3 and the Tinker Board S embedded systems present the appropriate characteristics to be implemented as portable devices in the artificial pancreas application according to the criteria set out in this work.
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Diabetes Mellitus Tipo 1/terapia , Pâncreas Artificial , Adulto , Algoritmos , Glicemia , Humanos , Hiperglicemia , Hipoglicemia , Insulina , Software , TemperaturaRESUMO
Resumen El presente trabajo describe el desarrollo y simulación de un algoritmo para el control automático de la infusión de insulina en el manejo glucémico de pacientes con cetoacidosis diabética (CAD) y estado hiperosmolar hiperglucémico (EHH). Se programó un algoritmo que calcula la insulina necesaria para lograr un descenso glucémico de 50 mg/dL/h hasta llegar a glucemias de 250 mg/dL, para posteriormente mantenerlas en 220 mg/dL hasta la remisión de la patología. La simulación del software se realizó haciendo uso de registros glucémicos de 10 pacientes con CAD manejados en el Hospital Juárez de México. Los resultados de la simulación mostraron una incidencia 6 veces menor de hipoglucemias, así como un 33.7% menos de insulina necesaria dentro del tratamiento, sin diferencias entre los descensos medios de glucosa por hora de las mediciones reales y simuladas. Este software propone un uso innovador de los llamados páncreas artificiales al aplicarlos en urgencias hiperglucémicas, implementando además el uso de la sensibilidad a la insulina como variable para el funcionamiento de los mismos. Los resultados demuestran que el algoritmo podría ser capaz de lograr un manejo glucémico apegado a las guías de tratamiento, generando un menor gasto de insulina y evitando hipoglucemias durante la terapéutica, con una posible aplicación en dispositivos biomédicos autónomos.
Abstract This paper describes the development and simulation of an algorithm for the automatic control of insulin infusion, in the glycemic management of patients with diabetic ketoacidosis (CAD) and hyperglycemic hyperosmolar state (EHH). An algorithm was programmed to calculate the requirement insulin for a glycemic decrease of 50 mg/dL/h until reach 250 mg/dL in blood glucose levels, and thus maintaining it at 220 mg/dL until the pathology remission. The software simulation was performed using glycemic records of 10 patients with CAD managed in the Hospital Juárez de México. The results of the simulation showed a lower incidence of hypoglycemia, as well as a lower insulin requirement within the treatment, without differences in the average glucose decreases per hour between real and simulated measurements. This software proposes an innovative use of the artificial pancreas in hyperglycemic emergencies, and also implementing the use of insulin sensitivity as a variable for their function. The results show that the algorithm could be able to achieve glycemic management attached to the treatment guidelines, generating lower insulin expenditure and avoiding hypoglycemia during therapy, with a possible application in autonomous biomedical devices.
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Artificial pancreas (AP) systems have shown to improve glucose regulation in type 1 diabetes (T1D) patients. However, full closed-loop performance remains a challenge particularly in children and adolescents, since these age groups often present the worst glycemic control. In this work, an algorithm based on switched control and time-varying IOB constraints is presented. The proposed control strategy is evaluated in silico using the FDA-approved UVA/ Padova simulator and its performance contrasted with the previously introduced Automatic Regulation of Glucose (ARG) algorithm in the pediatric population. The effect of unannounced meals is also explored. Results indicate that the proposed strategy achieves lower hypo- and hyperglycemia than the ARG for both announced and unannounced meals. Graphical Abstract Block diagram and illustrative example of insulin and glucose evolution over time for the proposed algorithm (ARGAE).
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Algoritmos , Insulina , Pâncreas Artificial , Adolescente , Glicemia , Automonitorização da Glicemia , Criança , Simulação por Computador , Diabetes Mellitus Tipo 1/terapia , Humanos , Hiperglicemia , Hipoglicemia , Insulina/administração & dosagem , Insulina/sangue , Fatores de TempoRESUMO
BACKGROUND: Either under standard basal-bolus treatment or hybrid closed-loop control, subjects with type 1 diabetes are required to count carbohydrates (CHOs). However, CHO counting is not only burdensome but also prone to errors. Recently, an artificial pancreas algorithm that does not require premeal insulin boluses-the so-called automatic regulation of glucose (ARG)-was introduced. In its first pilot clinical study, although the exact CHO counting was not required, subjects still needed to announce the meal time and classify the meal size. METHOD: An automatic switching signal generator (SSG) is proposed in this work to remove the manual mealtime announcement from the control strategy. The SSG is based on a Kalman filter and works with continuous glucose monitoring readings only. RESULTS: The ARG algorithm with unannounced meals (ARGum) was tested in silico under the effect of different types of mixed meals and intrapatient variability, and contrasted with the ARG algorithm with announced meals (ARGam). Simulations reveal that, for slow-absorbing meals, the time in the euglycemic range, [70-180] mg/dL, increases using the unannounced strategy (ARGam: 78.1 [68.6-80.2]% (median [IQR]) and ARGum: 87.8 [84.5-90.6]%), while similar results were found with fast-absorbing meals (ARGam: 87.4 [86.0-88.9]% and ARGum: 87.6 [86.1-88.8]%). On the other hand, when intrapatient variability is considered, time in euglycemia is also comparable (ARGam: 81.4 [75.4-83.5]% and ARGum: 80.9 [77.0-85.1]%). CONCLUSION: In silico results indicate that it is feasible to perform an in vivo evaluation of the ARG algorithm with unannounced meals.
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Glicemia/análise , Diabetes Mellitus Tipo 1/tratamento farmacológico , Hipoglicemiantes/uso terapêutico , Insulina/uso terapêutico , Refeições , Pâncreas Artificial , Algoritmos , Automonitorização da Glicemia , Simulação por Computador , Diabetes Mellitus Tipo 1/sangue , Humanos , Hipoglicemiantes/administração & dosagem , Insulina/administração & dosagem , Período Pós-PrandialRESUMO
OBJECTIVE: We produced, through a systematic review of quantitative and qualitative evidence, a synthesis of the issues of importance (values and preferences) to adult patients with type 1 diabetes regarding treatment with automated insulin delivery systems. METHODS: We searched MEDLINE, CINAHL, EMBASE, and PsycINFO from the inception of each database through September 2018. We included studies examining patient values and preferences for outcomes related to continuous subcutaneous insulin infusion or artificial pancreas treatment. We compiled structured summaries of the results and assessed the relative importance of each outcome. GRADE (Grading of Recommendations, Assessment Development, and Evaluation) and CERQual (Confidence in Evidence from Reviews of Qualitative research) approaches provided the structure for the evaluation of the quality of evidence and confidence in the findings. A mixed-methods result-based convergent design provided the structure for integration and presentation of results. RESULTS: We reviewed 1665 unique citations; 19 studies (8 quantitative and 11 qualitative) proved eligible. Glycemic control is the key attribute that drives patients' preference. Reduction of glycemic variability and decreased incidence of hypoglycemia and chronic complications proved of intermediate importance and were ranked similarly to components of treatment burden, including the size and appearance of devices, cost, ease of use, and the embarrassment of public use. CONCLUSIONS: Clinician guidance may play a crucial role in determining patient values and preferences (for instance, patients' priority in glucose control rather than avoiding diabetic complications). Our results provide guidance for clinicians in discussing preferred insulin delivery systems with patients with type 1 diabetes.
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Diabetes Mellitus Tipo 1/tratamento farmacológico , Sistemas de Infusão de Insulina , Insulina/administração & dosagem , Pâncreas Artificial , Preferência do Paciente , Glicemia/análise , Diabetes Mellitus Tipo 1/sangue , Humanos , Insulina/uso terapêuticoRESUMO
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.
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Algoritmos , Diabetes Mellitus Tipo 1/tratamento farmacológico , Hipoglicemiantes/administração & dosagem , Insulina/administração & dosagem , Pâncreas Artificial , Adulto , Automonitorização da Glicemia , Feminino , Humanos , Sistemas de Infusão de Insulina , América Latina , Masculino , Pessoa de Meia-Idade , Projetos Piloto , Período Pós-PrandialRESUMO
Since the 2000s, research teams worldwide have been working to develop closed-loop (CL) systems able to automatically control blood glucose (BG) levels in patients with type 1 diabetes. This emerging technology is known as artificial pancreas (AP), and its first commercial version just arrived in the market. The main objective of this paper is to present an extensive review of the clinical trials conducted since 2011, which tested various implementations of the AP for different durations under varying conditions. A comprehensive table that contains key information from the selected publications is provided, and the main challenges in AP development and the mitigation strategies used are discussed. The development timelines for different AP systems are also included, highlighting the main evolutions over the clinical trials for each system.
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Automonitorização da Glicemia/estatística & dados numéricos , Glicemia/análise , Diabetes Mellitus Tipo 1/sangue , Pâncreas Artificial , Automação , Automonitorização da Glicemia/instrumentação , Automonitorização da Glicemia/métodos , Ensaios Clínicos como Assunto , Diabetes Mellitus Tipo 1/tratamento farmacológico , Desenho de Equipamento , Exercício Físico , Previsões , Humanos , Hiperglicemia/sangue , Hiperglicemia/tratamento farmacológico , Hipoglicemia/sangue , Hipoglicemia/induzido quimicamente , Hipoglicemia/prevenção & controle , Hipoglicemiantes/administração & dosagem , Hipoglicemiantes/uso terapêutico , Bombas de Infusão Implantáveis , Insulina/administração & dosagem , Insulina/uso terapêutico , Sistemas de Infusão de InsulinaRESUMO
Resumen Las bombas de insulina han sido usadas por más de 35 años, principalmente en pacientes con diabetes tipo 1 y en menor medida en diabetes tipo 2. En esta última población hay una liberación más funcional de insulina, se puede prevenir el fenómeno de alba y mantener por más tiempo los niveles adecuados de glucemia. Las indicaciones de bomba en diabetes tipo 2 son poco claras, pero los que tal vez más se benefician son aquellos con historia de mal control metabólico, hipoglucemias severas o asintomáticas. El uso de esta tecnología durante la hospitalización ha sido difícil, principalmente por el desconocimiento del personal de salud en su uso; no obstante, se ha demostrado que es factible mantener a los pacientes en esta terapia mientras están hospitalizados, siempre y cuando se tenga un adecuado protocolo, disposición del personal y educación del paciente. El costo ha sido una de las cuestiones más controversiales con el uso de estos sistemas. Los análisis de costo-efectividad han encontrado una disminución del número de hipoglucemiantes orales, las visitas a urgencias y las dosis de insulina, llegando algunos a aseverar que en tres años podrían compensarse los costos.
Abstract Insulin pumps have been used for over 35 years, mostly in patients with type 1 diabetes and to a lesser extent in type 2 diabetes. The use of pumps in this population is supported by a more physiological release of insulin, prevention of the dawn phenomenon and enabling patients to achieve better glucose targets. Pump indications in type 2 diabetes are less clear than in patients with type 1, but perhaps those who benefit most, are patients with a history of significant glycemic excursions, severe or asymptomatic hypoglycemia. Pump management as inpatient has been limited by lack of personal knowledge, however it has been reported that it is feasible to keep patients who are using this technology to continue it while they are in the hospital provided that a suitable protocol has been standardized and the patient has enough knowledge. Costs have been one of the most controversial issues with the use of these technology, cost-effectiveness analysis have found that there is a decrease in the number of oral agents, emergency room visits and insulin doses, reaching some studies to conclude that three years could offset the pump cost.
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Technology for diabetes care has undergone major development during recent decades. These technological advances include continuous subcutaneous insulin infusion (CSII), also known as insulin pumps, and real-time continuous glucose monitoring system (RT-CGMS). The integration of CSII and RT-CGMS into a single device has led to sensor-augmented pump therapy and more recently, a technology that has automated delivery of basal insulin therapy, known as hybrid system. These new technologies have led to benefits in attaining better metabolic control and decreasing the incidence of severe hypoglycemia, especially in patients with type 1 diabetes. This review describes the types of technologies currently available or under investigation for these purposes, their benefits and disadvantages, recommendations and the appropriate patient selection for their use. The clinical use of the hybrid system and artificial pancreas seem to be possible in the near future.
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Humanos , Sistemas de Infusão de Insulina , Pâncreas Artificial , Diabetes Mellitus Tipo 1/tratamento farmacológico , Diabetes Mellitus Tipo 2/tratamento farmacológico , Hipoglicemiantes/administração & dosagem , Insulina/administração & dosagem , Automonitorização da GlicemiaRESUMO
En la década pasada, el conocimiento sobre la historia natural y fisiopatogenia de la diabetes tipo 1 tuvo un importante crecimiento, particularmente en relación con predicción, heterogeneidad, patología pancreática y su epidemiología. Las mejoras tecnológicas específicamente en el desarrollo de bombas de insulina y sensores continuos de glucosa ayudan a los pacientes con diabetes tipo 1 en el desafío de la administración de insulina a largo plazo. A pesar de grandes inversiones sobre distintos aspectos de la enfermedad (financiación de proyectos, organizativos, educacionales, etc.) no existe hasta el momento la prevención ni la cura para la diabetes tipo 1, y sumado a esto la calidad sobre el manejo de la enfermedad es muy heterogéneo. Como el control glucémico mejora con un tratamiento intensificado (múltiples inyecciones de insulina), el número y frecuencia de eventos hipoglucémicos tienden a incrementarse. La hipoglucemia es generadora de cuadros de estrés, ansiedad y deterioro de la calidad de vida en los pacientes con diabetes. Una de las razones por las cuales existe gran dificultad de alcanzar los objetivos glucémicos en pacientes con diabetes tipo 1 es la variabilidad en la absorción de la insulina inyectada en forma subcutánea, la que conlleva mayor e impredecible variabilidad en la concentración glucémica y todo esto en general se relaciona con valores elevados de hemoglobina glicosilada e hipoglucemia. La terapia con bomba de insulina se inició hace más de 30 años con el objetivo de mejorar el control en pacientes con diabetes tipo 1. El objetivo de esta revisión es actualizar las herramientas tecnológicas en el tratamiento de la diabetes. (AU)
Over the past decade, knowledge of the pathogenesis and natural history of type 1 diabetes has grown substantially, particularly with regard to disease prediction and heterogeneity, pancreatic pathology, and epidemiology. Technological improvements in insulin pumps and continuous glucose monitors help patients with type 1 diabetes manage the challenge of lifelong insulin administration. Agents that show promise for averting debilitating disease-associated complications have also been identified. However, despite broad organisational, intellectual, and fiscal investments, no means for preventing or curing type 1 diabetes exists, and , globally, the quality of diabetes management remains uneven. As glycemic control improves with intensified insulin regimens, the frequency of hypoglycemia tends to increase. Hypoglycemia is the cause of considerable stress and anxiety, impaired well-being, and poor quality of life in patients with type diabetes. One reason for continued poor glycemic control in patients with type 1 diabetes is the erratic absorption and action of subcutaneously injected insulin, which lead to unpredictable swings in blood glucose concentrations, and those swings, in themselves, are associated with elevated glycated hemoglobin levels and hypoglycemia. Insulinpump therapy, or continuous subcutaneous insulin infusion, was introduced more than 30 years ago as a procedure for improving glycemic control in patients with type 1 diabetes. The primary goal is to perform an up date about the new technological tools in diabetes treatment. (AU)
Assuntos
Humanos , Masculino , Feminino , Sistemas de Infusão de Insulina/tendências , Diabetes Mellitus Tipo 1/tratamento farmacológico , Insulina/uso terapêutico , Glicemia/análise , Automonitorização da Glicemia , Bombas de Infusão Implantáveis , Diabetes Mellitus Tipo 1/sangue , Controle Glicêmico/métodos , Insulina/administração & dosagemRESUMO
AIM: To report the first clinical experience with a prototype of implanted artificial beta-cell. METHODS: The Long-Term Sensor System® project assessed the feasibility of glucose control by the combined implantation of a pump for peritoneal insulin delivery and a central intravenous glucose sensor, connected physically by a subcutaneous lead and functionally by PID algorithms. It was performed in 10 type 1 diabetic patients from 2000 to 2007. RESULTS: No harmful complication related to implants occurred. Insulin delivery was affected by iterative but reversible pump slowdowns due to insulin precipitation. Glucose measurement by the intravenous sensors correlated well with meter values (r = 0.83-0.93, with a mean absolute deviation of 16.5 percent) for an average duration of 9 months. Uploading of pump electronics by PID algorithms designed for closed-loop insulin delivery allowed in-patient 48 hourtrials. CONCLUSION: Although the concept of a fully implantable artificial beta-cell has been shown as feasible, improvements in the sensor structure to increase its longevity and decrease sensor delay that affected closed-loop control at meal-times are expected.
OBJETIVO: Relatar a primeira experiência clínica com um protótipo de célulabeta artificial implantável. MÉTODOS: O Projeto de Um Sistema Sensor de Longo Prazo avaliou a possibilidade do controle glicêmico através do implante combinado de uma bomba de infusão de insulina peritoneal e um gluco - sensor endovenoso central - conectados fisicamente por um dispositivo subcutâneo e funcionalmente por algoritmos PID (integral and derivative). Este projeto envolveu 10 pacientes com diabetes melito tipo 1 de 2000 a 2007. RESULTADOS: Complicações significativas relacionadas aos implantes não ocorreram. A liberação de insulina pela bomba sofreu o efeito de períodos de lentificação interativo, mas reversível, devido a precipitação do peptídeo. As medidas da glicose pelo sensor endovenoso mostraram boa correlação com os valores do glicosímetro (r = 0,83-0,93, com desvio médio absoluto de 16,5 por cento) durante período médio de 9 meses. Os dados para construção dos algoritmos PID do sistema de alça fechada de liberação de insulina foram obtidos a partir de 12 pacientes que permaneceram internados com esse sistema durante 48 horas com refeições que continham 40 a 70 g de carboidratos. CONCLUSÃO : Embora o conceito de uma célula-beta artificial totalmente implantável tenha demonstrado ser possível, aperfeiçoamentos são necessários na estrutura do sensor para aumentar a sua longevidade e no sistema de alça fechada de liberação de insulina para diminuir as lentificações que comprometem o controle glicêmico nos períodos relacionados às refeições.