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BACKGROUND: Automated insulin delivery (AID) devices have shown to be a promising treatment to improve glycemic control in patients with type 1 diabetes mellitus (T1DM). However, its efficacy in pregnant women with T1DM remains uncertain. METHODS: PubMed, Scopus, Cochrane Central and ClinicalTrials.gov were systematically searched for randomized controlled trials (RCTs) comparing AID to standard care (SC), defined as use of sensor-augmented pump and multiple daily insulin injections. Outcomes included time in range (TIR), nocturnal TIR, time in hypoglycemic and hyperglycemic ranges, among others. Sensitivity and trial sequential analyses (TSA) were performed. PROSPERO ID: CRD42023474398. RESULTS: We included five RCTs with a total of 236 pregnant women, of whom 117 (50.6%) received AID. There was a significant increase in nocturnal TIR (mean difference [MD] 12.69%; 95% CI 8.74-16.64; p < 0.01; I2 = 0%) and a decrease in glucose variability (standard deviation of glucose; MD -2.91; 95% CI -5.13 to -0.69; p = 0.01; I2 = 0%). No significant differences were observed for TIR, HBGI, LGBI, mean glucose and time spent in hyperglycemia and hypoglycemia. Regarding TSA, the statistical significance obtained in nocturnal TIR was conclusive and with minimal risk of a type I error. CONCLUSION: Our findings suggest that AID systems can significantly improve nocturnal glycemic control and potentially reduce glycemic variability in pregnant women with T1DM, with no effect in the risk of hypoglycemia and hyperglycemia compared with current insulin treatments.
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Diabetes Mellitus Tipo 1 , Hipoglicemiantes , Sistemas de Infusão de Insulina , Insulina , Ensaios Clínicos Controlados Aleatórios como Assunto , Adulto , Feminino , Humanos , Gravidez , Glicemia/metabolismo , Glicemia/análise , Glicemia/efeitos dos fármacos , Diabetes Mellitus Tipo 1/tratamento farmacológico , Diabetes Mellitus Tipo 1/sangue , Controle Glicêmico/métodos , Controle Glicêmico/instrumentação , Hipoglicemiantes/administração & dosagem , Insulina/administração & dosagem , Gravidez em Diabéticas/tratamento farmacológico , Gravidez em Diabéticas/sangue , Resultado do TratamentoRESUMO
BACKGROUND: This study investigated the characteristics associated with an increased risk of hypoglycemia, in elderly patients with type 1 diabetes mellitus (T1D) using automated insulin delivery (AID) systems. METHODS: Cross-sectional observational study including patients >60 years, using sensor-augmented insulin pump therapy with predictive low-glucose management (SAPT-PLGM), hybrid closed-loop (HCL), and advanced hybrid closed-loop (AHCL), for more than three months. A geriatric assessment was performed, and body composition was determined to investigate its association with achieving time below range (TBR) <70 mg/dL goals. RESULTS: The study included 59 patients (47.5% of men, mean age of 67.6 years, glycated hemoglobin [HbA1c] of 7.5 ± 0.6%, time in range (TIR) 77.8 ± 9.9%). Time below range <70 and <54 mg/dL were 2.2 ± 2.3% and 0.4 ± 0.81%, respectively. Patients with elevated TBR <70 mg/dL (>1%) had higher HbA1c levels, lower TIR, elevated time above range (TAR), and high glycemic variability. Regarding body composition, greater muscle mass, grip strength, and visceral fat were associated with a lower TBR <70 mg/dL. These factors were independent of the type of technology used, but TIR was higher when using AHCL systems compared with SAPT-PLGM and HCL systems. CONCLUSIONS: In elderly patients treated with AID systems with good functional status, lower lean mass, lower grip strength, and lower visceral fat percentage were associated with TBR greater than 1%, regardless of the device used. A similar finding along was found with CGM indicators such as higher HbA1c levels, lower TIR, higher TAR, and higher CV. Geriatric assessment is crucial for personalizing patient management.
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Objective: The Diabetes Device Confidence Scale (DDCS) is a new scale designed to evaluate school nurse confidence with diabetes devices. We hypothesized that DDCS score would be associated with related constructs of school nurse diabetes knowledge, experience, and training. Research Design and Methods: In a cross-sectional study, we co-administered the DDCS and Diabetes Knowledge Test 2 (DKT2) questionnaires to school nurses in Pennsylvania. We summarized DDCS scores (range 1-5) descriptively. We evaluated the relationship between DKT2 percent score and DDCS mean score with the Spearman correlation coefficient. Simple linear regression examined school nurse characteristics as predictors of DDCS score. Results: A total of 271 completed surveys were received. Mean DDCS score was 3.16±0.94, indicating moderate confidence with devices overall. School nurses frequently reported low confidence in items representing specific skills, including suspending insulin delivery (40%), giving a manual bolus (42%), knowing when to calibrate a continuous glucose monitor (48%), changing an insulin pump site (54%), and setting a temporary basal rate (58%). Mean DKT2 score was 89.5±0.1%, which was weakly but not significantly correlated with DDCS score (r=0.12, p=0.06). Formal device training (p<0.001), assisting ≥5 students with diabetes devices in the past 5 years (p<0.01), and a student caseload between 1000-1500 students (p<0.001) were associated with higher mean DDCS score. Conclusions: DDCS score is related to prior training and experience, providing evidence for the scale's convergent validity. The DDCS may be a useful tool for assessing school nurse readiness to use devices and identify areas to enhance knowledge and practical skills.
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Diabetes Mellitus , Humanos , Estudos Transversais , Diabetes Mellitus/terapia , Insulina , Inquéritos e Questionários , EstudantesRESUMO
BACKGROUND: There is evidence in the literature that the use of sensor-augmented insulin pumps in patients with high-complexity diabetes improves metabolic control. However, there is no long-term information on clinical outcomes such as hospitalization or admission to the emergency room. This study describes outcomes for metabolic control, incidence of hospitalizations, and emergency room visits in a specific population using this technology. OBJECTIVE: We aimed to assess long-term glycemic and clinical outcomes after the use of continuous subcutaneous insulin infusion and continuous glucose monitoring in people with diabetes. METHODS: A retrospective cohort study was carried out in patients with diabetes previously treated with an intensive insulin regimen at a specialized diabetes treatment center who required a sensor-augmented insulin pump due to nonoptimal glycemic control. Glycated hemoglobin, severe hypoglycemic episodes, nonsevere hypoglycemic episodes, perception of hypoglycemia, and the incidence of emergency room visits and hospitalizations before and after treatment were evaluated. RESULTS: Between January 2013 and August 2020, 74 patients with a median age of 36 (IQR 27-46) years were included in the study with a median 4 (IQR 2-7) years of follow-up. We found a statistically significant reduction in glycated hemoglobin (8.35% vs 7%; P<.001), nonsevere hypoglycemic episodes (71/74, 96% vs 62/74, 84%; P=.01), emergency room visits (42/73, 58% vs 4/62, 6%; P<.001), and hospitalizations (36/72, 50% vs 10/72, 14%; P<.001) after use of continuous subcutaneous insulin infusion. CONCLUSIONS: The use of a sensor-augmented insulin pump associated with a strict follow-up program for patients with high-complexity diabetes led to a significant and sustained reduction in glycated hemoglobin and hypoglycemic episodes, as well as in the rate of emergency room visits and hospitalizations. These results encourage the adoption of this technology in patients who do not achieve metabolic control with optimal management of diabetes.
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BACKGROUND AND AIMS: Evidence supports the efficacy and safety of the Hybrid Close loop (HCL) system in patients with type 1 diabetes (T1D). However, limited data are available on the long-term outcomes of patients on HCL with telemedicine follow-up. METHODS: A prospective observational cohort study including T1D patients, who were upgrading to HCL system. Virtual training and follow-up were done through telemedicine. CGM data were analyzed to compare the baseline time in range (TIR), time below range (TBR), glycemic variability and auto mode (AM), with measurements performed at 3, 6 and 12 months. RESULTS: 134 patients were included with baseline A1c 7.6% ± 1.1. 40.5% had a severe hypoglycemia event in the last year. Baseline TIR, measured two weeks after starting AM was 78.6 ± 9.94%. No changes were evident at three (Mean difference - 0.15;CI-2.47,2.17;p = 0.96), six (MD-1.09;CI-3.42,1.24;p = 0.12) and 12 months (MD-1.30;CI-3.64,1.04;p = 0.08). No significant changes were found in TBR or glycemic variability throughout the follow-up. Use of AM was 85.6 ± 17.5% and percentage of use of sensor was 88.75 ± 9.5% at 12 months. No severe hypoglycemic (SH) events were reported. CONCLUSIONS: HCL systems allow to improve TIR, TBR and glycemic variability safely, early and sustained up to 1 year of follow-up in patients with T1D and high risk of hypoglycemia followed through telemedicine.
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Diabetes Mellitus Tipo 1 , Hipoglicemia , Telemedicina , Humanos , Diabetes Mellitus Tipo 1/etiologia , Insulina/uso terapêutico , Glicemia , Estudos Prospectivos , Sistemas de Infusão de Insulina/efeitos adversos , Hipoglicemiantes/uso terapêutico , Hipoglicemia/etiologia , Hipoglicemia/induzido quimicamente , Automonitorização da GlicemiaRESUMO
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
BACKGROUND AND AIMS: In Colombia, the government established mandatory isolation after the first case of COVID-19 was reported. As a diabetes care center specialized in technology, we developed a virtual training program for patients with type 1 diabetes (T1D) who were upgrading to hybrid closed loop (HCL) system. The aim of this study is to describe the efficacy and safety outcomes of the virtual training program. METHOD: ology: A prospective observational cohort study was performed, including patients with diagnosis of T1D previously treated with multiple doses of insulin (MDI) or sensor augmented pump therapy (SAP) who were updating to HCL system, from March to July 2020. Virtual training and follow-up were done through the Zoom video conferencing application and Medtronic Carelink System version 3.1 software. CGM data were analyzed to compare the time in range (TIR), time below range (TBR) and glycemic variability, during the first two weeks corresponding to manual mode with the final two weeks of follow-up in automatic mode. RESULTS: 91 patients were included. Mean TIR achieved with manual mode was 77.3 ± 11.3, increasing to 81.6% ± 7.6 (p < 0.001) after two weeks of auto mode use. A significant reduction in TBR <70 mg/dL (2,7% ± 2,28 vs 1,83% ± 1,67, p < 0,001) and in glycemic variability (% coefficient of variation 32.4 vs 29.7, p < 0.001) was evident, independently of baseline therapy. CONCLUSION: HCL systems allows T1D patients to improve TIR, TBR and glycemic variability independently of previous treatment. Virtual training can be used during situations that limit the access of patients to follow-up centers.
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COVID-19/epidemiologia , Diabetes Mellitus Tipo 1/epidemiologia , Diabetes Mellitus Tipo 1/terapia , Sistemas de Infusão de Insulina , Educação de Pacientes como Assunto/métodos , Telemedicina/métodos , Adolescente , Adulto , Idoso , Automonitorização da Glicemia/métodos , COVID-19/prevenção & controle , Estudos de Coortes , Colômbia/epidemiologia , Feminino , Seguimentos , Humanos , Hipoglicemiantes/administração & dosagem , Masculino , Pessoa de Meia-Idade , Estudos Prospectivos , Adulto JovemRESUMO
Insulin pump technologies are commonly used by youth with type 1 diabetes (T1D) for intensive insulin therapy, the gold standard for T1D care. Insulin pump technologies are advancing rapidly, with new insulin pumps becoming available every year offering improvements in glycemic control. School nurses must understand the basics of insulin pump therapy and distinguish between advanced pump technologies to best support their students with T1D. This is the second article in a three-part series on the use of technology in managing diabetes in youth. The first article described continuous glucose monitoring (CGM) devices and provided tips for the school nurses in incorporating CGM into the student's individualized healthcare plan. The purpose of this article is to summarize insulin pump technologies, from conventional insulin pump therapy to advanced automated insulin delivery systems and to describe keys to success with insulin pump technologies. Part 3 will focus on special considerations and problem solving related to technology use in the school setting.
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Diabetes Mellitus Tipo 1 , Enfermeiras e Enfermeiros , Serviços de Enfermagem Escolar , Adolescente , Glicemia , Automonitorização da Glicemia , Diabetes Mellitus Tipo 1/tratamento farmacológico , Humanos , Hipoglicemiantes , Insulina , Instituições Acadêmicas , TecnologiaRESUMO
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.