RESUMO
BACKGROUND: The use of machine learning and deep learning techniques in the research on diabetes has garnered attention in recent times. Nonetheless, few studies offer a thorough picture of the knowledge generation landscape in this field. To address this, a bibliometric analysis of scientific articles published from 2000 to 2022 was conducted to discover global research trends and networks and to emphasize the most prominent countries, institutions, journals, articles, and key topics in this domain. METHODS: The Scopus database was used to identify and retrieve high-quality scientific documents. The results were classified into categories of detection (covering diagnosis, screening, identification, segmentation, among others), prediction (prognosis, forecasting, estimation), and management (treatment, control, monitoring, education, telemedicine integration). Biblioshiny and RStudio were used to analyze the data. RESULTS: A total of 1773 articles were collected and analyzed. The number of publications and citations increased substantially since 2012, with a notable increase in the last 3 years. Of the 3 categories considered, detection was the most dominant, followed by prediction and management. Around 53.2% of the total journals started disseminating articles on this subject in 2020. China, India, and the United States were the most productive countries. Although no evidence of outstanding leadership by specific authors was found, the University of California emerged as the most influential institution for the development of scientific production. CONCLUSION: This is an evolving field that has experienced a rapid increase in productivity, especially over the last years with exponential growth. This trend is expected to continue in the coming years.
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Aprendizado Profundo , Diabetes Mellitus , Humanos , Bibliometria , Diabetes Mellitus/diagnóstico , Diabetes Mellitus/terapia , Aprendizado de Máquina , ChinaRESUMO
Introducción: El uso de mHealth puede mejorar la adherencia a el automonitoreo con glucometría capilar (GC) en la transición del ámbito hospitalario al ambulatorio. Objetivo: evaluar la adherencia al automonitoreo con GC de los pacientes con Diabetes Tipo 2 (DM2) vinculados a un programa de educación usuarios de mHealth (ClouDi) comparado con el programa de educación y seguimiento presencial usual. Materiales y métodos: Estudio longitudinal prospectivo. Se analizaron pacientes con DM2 valorados por consulta de educación de diabetes con indicación de tratamiento con insulina al egreso hospitalario. Se analizaron dos grupos: uno con seguimiento presencial y otro vinculado a un programa educativo y uso de ClouDi. Resultados: De los 86 pacientes (44% de sexo femenino, 41 usuarios ClouDi, edad promedio 58.8 ± 11.2 años, con una media de duración de la diabetes de 7.8 ± 7.4 años), 53.6% se encontraban en estrato 2, el 92.9% pertenecían al régimen contributivo, el 42.9% con educación básica primaria y 51.2% empleados. Fue considerada la adherencia a la GC al realizar y registrar 3 o más mediciones por día en los pacientes de ClouDi fue mayor comparado con los pacientes en cuidado usual (64.4% vs 28.2%, p <0.001), independiente de las variables sociodemográficas. Conclusión: El uso de ClouDi se asoció a mayor adherencia a automonitoreo con GC comparado con seguimiento presencial independiente de variables sociodemográficas. El uso de esta tecnología podría ser útil en el seguimiento de pacientes usuarios de insulina al egreso hospitalario
Introduction: The use of mHealth can improve adherence to self-monitoring blood Glucose (SMBG) in the transition from hospital to outpatient setting. Objective: To evaluate adherence to self-monitoring with GC in patients with type 2 diabetes (T2DM) linked to an mHealth user education program (ClouDi) compared with the usual face-to-face education and follow-up program. Materials and Methods: Prospective longitudinal study. Patients with T2D assessed by diabetes education counseling with an indication for insulin treatment at hospital discharge were analyzed. Two groups were analyzed: one with face-to-face follow-up and another linked to an educational program and use of ClouDi. Results: Of the 86 patients (44% female, 41 ClouDi users, mean age 58.8 ± 11.2 years, with a mean duration of diabetes of 7.8 ± 7.4 years), 53.6% were in stratum 2, 92.9% belonged to the contributory system, 42.9% with basic pri-mary education and 51.2% were employed. Compliance with the SMBG was considered if 3 or more measurements per day were taken and recorded, was higher in ClouDi patients com-pared to usual care patients (64.4% vs. 28.2%, p <0.001), independent of sociodemographic variables.Conclusions: The use of ClouDi was associated with greater adherence to SMBG compared to in-person follow-up, independent of sociodemographic variables. The use of this technology may be useful in monitoring insulin-using patients after hospital discharge
Introdução: A utilização do mHealth pode melhorar a adesão à automonitorização com glico-metria capilar (GC) na transição do hospital para o ambulatório. Objetivo: avaliar a adesão ao automonitoramento com GC de pacientes com Diabetes Tipo 2 (DM2) vinculados a um progra-ma de educação de usuários de mHealth (ClouDi) em comparação com o programa habitual de educação e acompanhamento presencial. Materiais e métodos: Estudo prospectivo longitudi-nal. Foram analisados pacientes com DM2 avaliados por consulta de educação em diabetes com indicação de tratamento insulínico na alta hospitalar. Foram analisados dois grupos: um com acompanhamento presencial e outro vinculado a um programa educativo e uso do ClouDi. Re-sultados: Dos 86 doentes (44% do sexo feminino, 41 utilizadores do ClouDi, idade média 58,8 ± 11,2 anos, com duração média da diabetes de 7,8 ± 7,4 anos), 53,6% encontravam-se no estra-to 2, 92,9% pertenciam ao regime contributivo, 42,9% com ensino fundamental básico e 51,2% empregados. A adesão ao GC foi considerada quando realizada e registrada 3 ou mais medidas por dia em pacientes ClouDi foi maior em comparação aos pacientes em cuidados habituais (64,4% vs 28,2%, p <0,001), independente das variáveis sociodemográficas. Conclusão: O uso do ClouDi esteve associado à maior adesão ao automonitoramento com GC em comparação ao acompanhamento presencial independente das variáveis sociodemográficas. O uso dessa tecnologia pode ser útil no monitoramento de pacientes usuários de insulina na alta hospitalar
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Diabetes Mellitus Tipo 2 , Tecnologia , Educação , InsulinaRESUMO
INTRODUCTION: There are data capture devices that attach to the FreeStyle Libre sensor and convert its communication from NFC (Near-field communication) to Bluetooth technology, generating real-time continuous glucose monitoring. The accuracy of hypoglycemia measurements displayed by smartphone apps using this device has not been established. METHODS: Study of diagnostic tests. Numerical accuracy was evaluated, utilizing the absolute difference with respect to capillary glucometry (ISO 15197:2015 standard) and clinical accuracy, using the Clarke and Parkes (Consensus) error grids, for glucose measurements less than 70mg/dL performed with the FreeStyle Libre system and with the digital estimation xDrip+ app, in diabetic patients managed with insulin therapy. RESULTS: Twenty-seven patients were included (TIR 73.4%, TBR70 5.6%), who contributed 83 hypoglycemic events. Numerical accuracy was adequate in similar proportions with the FreeStyle Libre system compared to the xDrip+ app (81.92% vs. 68.67%, p=0.0630). The clinical accuracy evaluation showed that 92.8% of the measurements for xDrip+ and 98.8% for FreeStyle libre met the criteria according to the Parkes (Consensus) grid (p=0.0535); and 79.5% and 91.6% of the measurements met the criteria according to the Clarke grid (p=0.0273), being higher with FreeStyle libre. CONCLUSIONS: The use of the NFC-Bluetooth transmitter (Miao-Miao) associated with the xDrip+ app does not improve numerical or clinical accuracy for detecting hypoglycemic events in diabetic patients managed with insulin therapy, compared to the FreeStyle Libre device.
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Diabetes Mellitus Tipo 1 , Hipoglicemia , Humanos , Insulina , Automonitorização da Glicemia , Glicemia , Diabetes Mellitus Tipo 1/tratamento farmacológico , Hipoglicemia/induzido quimicamente , Hipoglicemiantes/efeitos adversosRESUMO
BACKGROUND: This quality improvement study, entitled Avatar-Based LEarning for Diabetes Optimal Control (ABLEDOC), explored the feasibility of delivering an educational program to people with diabetes in Colombia. The aim was to discover how this approach could be used to improve awareness and understanding of the condition, the effects of treatment, and strategies for effective management of blood-glucose control. METHODS: Individuals with diabetes were recruited by Colombian endocrinologists to a human-centered study to codesign the educational program, using the Double Diamond model. Participants contributed to two phases. The first phase focused on gathering unmet educational needs and choice of curriculum. Three prototypes were developed as a result. During phase 2, a different group of participants engaged with the program for several weeks, before reporting back. RESULTS: Thirty-six participants completed a Web survey during phase 1, and five were also interviewed by telephone. The majority (33 of 36; 91%) were receptive to the prospect of educational interventions and ranked the chosen topic of hypoglycemia highly. In phase 2, the three prototypes were tested by 17 participants, 10 of whom also gave feedback in focus groups. The response was overwhelmingly positive, with 16 of 17 (94%) stating they would use a program like this again. The 3D version was the most highly rated. CONCLUSIONS: Immersive, avatar-based programs, delivered through smartphone, have the potential to deliver educational information that is trusted, engaging, and useful. Future work includes expansion of the curriculum, evaluation with a larger group, and exploration of the prospective role of artificial intelligence in personalizing this form of educational intervention.
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Inteligência Artificial , Diabetes Mellitus , Humanos , Colômbia , Melhoria de Qualidade , Diabetes Mellitus/terapiaRESUMO
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
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: There are several medical devices used in Colombia for diabetes management, most of which have an associated telemedicine platform to access the data. In this work, we present the results of a pilot study evaluating the use of the Tidepool telemedicine platform for providing remote diabetes health services in Colombia across multiple devices. METHOD: Individuals with Type 1 and Type 2 diabetes using multiple diabetes devices were recruited to evaluate the user experience with Tidepool over three months. Two endocrinologists used the Tidepool software to maintain a weekly communication with participants reviewing the devices data remotely. Demographic, clinical, psychological and usability data were collected at several stages of the study. RESULTS: Six participants, from ten at the baseline (five MDI and five CSII), completed this pilot study. Three different diabetes devices were employed by the participants: a glucose meter (Abbot), an intermittently-scanned glucose monitor (Abbot), and an insulin pump (Medtronic). A score of 81.3 in the system usability scale revealed that overall, most participants found the system easy to use, especially the web interface. The system also compared highly favourably against the proprietary platforms. The ability to upload and share data and communicate remotely with the clinicians was raised consistently by participants. Clinicians cited the lockdown imposed by the Covid-19 pandemic as a valuable test for this platform. Inability to upload data from mobile devices was identified as one of the main limitations. CONCLUSION: Tidepool has the potential to be used as a tool to facilitate remote diabetes care in Colombia. Users, both participants and clinicians, agreed to recommend the use of platforms like Tidepool to achieve better disease management and communication with the health care team. Some improvements were identified to enhance the user experience.
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COVID-19 , Diabetes Mellitus Tipo 2 , Telemedicina , Computação em Nuvem , Colômbia , Controle de Doenças Transmissíveis , Diabetes Mellitus Tipo 2/terapia , Humanos , Pandemias , Projetos Piloto , SARS-CoV-2RESUMO
INTRODUCTION: Continuous glucose monitoring (CGM) is a better tool to detect hyper and hypoglycemia than capillary point of care in insulin-treated patients during hospitalization. We evaluated the incidence of hypoglycemia in patients with type 2 diabetes (T2D) treated with basal bolus insulin regimen using CGM and factors associated with hypoglycemia. METHODS: Post hoc analysis of a prospective cohort study. Hypoglycemia was documented in terms of incidence rate and percentage of time <54 mg/dL (3.0 mmol/L) and <70 mg/dL (3.9 mmol/L). Factors evaluated included glycemic variability analyzed during the first 6 days of basal bolus therapy. RESULTS: A total of 34 hospitalized patients with T2D in general ward were included, with admission A1c of 9.26 ± 2.62% (76.8 ± 13 mmol/mol) and mean blood glucose of 254 ± 153 mg/dL. There were two events of hypoglycemia below 54 mg/dL (3.0 mmol/L) and 11 events below 70 mg/dL (3.9 mmol/L) with an incidence of hypoglycemic events of 0.059 and 0.323 per patient, respectively. From second to fifth day of treatment the percentage of time in range (140-180 mg/dL, 7.8-10.0 mmol/L) increased from 72.1% to 89.4%. Factors related to hypoglycemic events <70 mg/dL (3.9 mmol/L) were admission mean glucose (IRR 0.86, 95% CI 0.79, 0.95, P < .01), glycemic variability measured as CV (IRR 3.12, 95% CI 1.33, 7.61, P < .01) and SD, and duration of stay. CONCLUSIONS: Basal bolus insulin regimen is effective and the overall incidence of hypoglycemia detected by CGM is low in hospitalized patients with T2D. Increased glycemic variability as well as the decrease in mean glucose were associated with events <70 mg/dL (3.9 mmol/L).
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Diabetes Mellitus Tipo 2/epidemiologia , Hipoglicemia/epidemiologia , Insulina/administração & dosagem , Idoso , Glicemia/análise , Glicemia/efeitos dos fármacos , Glicemia/metabolismo , Automonitorização da Glicemia , Estudos de Coortes , Colômbia/epidemiologia , Diabetes Mellitus Tipo 2/sangue , Diabetes Mellitus Tipo 2/tratamento farmacológico , Feminino , Hospitalização/estatística & dados numéricos , Humanos , Hipoglicemia/induzido quimicamente , Incidência , Masculino , Pessoa de Meia-Idade , Quartos de Pacientes/estatística & dados numéricos , Fatores de RiscoRESUMO
Background: International consensus on the use of continuous glucose monitoring (CGM) recommends coefficient of variation (CV) as the metric of choice to express glycemic variability (GV) with a cutoff of 36% to define unstable diabetes. Even though, CV is associated with hypoglycemia in type 2 diabetes patients, the evidence on the use of one particular measure of GV in type 1 diabetes (T1DM) patients as a predictor of hypoglycemia is limited. Methods: A cohort of T1DM ambulatory patients was evaluated using CGM. Number and incidence rate of events <54 and <70 mg/dL were calculated. Bivariate and multivariate analysis of different glycemic indexes and clinical variables were performed to identify those associated with hypoglycemia. Receiver operating characteristic (ROC) curve analysis for each of the glycemic indexes was performed to define the best index and its optimal cutoff threshold to discriminate patients with events of hypoglycemia. Results: Seventy-three patients were included. A total of 128 events <54 mg/dL were recorded in 34 patients, and 350 events <70 mg/dL were registered in 51 patients. CV was the only variable significantly associated with hypoglycemia <54 mg/dL in the multivariate analysis (adjusted relative risk [aRR] 1.44, 95% confidence interval [CI]: 1.10-1.88, P = 0.008). CV, HbA1c (glycated hemoglobin), and mean glucose were associated with events <70 mg/dL. ROC curve analysis showed that, among GV metrics, CV had the best performance to discriminate patients with events <54 mg/dL (area under the curve [AUC] 0.87, 95% CI: 0.79-0.95) and events <70 mg/dL (AUC 0.79, 95% CI: 0.68-0.90) with optimal cutoff thresholds values of 34% and 31%, respectively. Among glycemic risk (GR) indexes, low blood glucose index (LBGI) showed the best performance. Conclusions: This analysis shows that CV is the best GV index, and LBGI the best GR index, to identify patients at risk of clinically significant hypoglycemia and hypoglycemia alert events in T1DM patients.
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Automonitorização da Glicemia/estatística & dados numéricos , Glicemia/análise , Diabetes Mellitus Tipo 1/sangue , Indicadores Básicos de Saúde , Hipoglicemia/etiologia , Adulto , Diabetes Mellitus Tipo 1/complicações , Feminino , Hemoglobinas Glicadas/análise , Humanos , Hipoglicemia/diagnóstico , Masculino , Estudos Prospectivos , Curva ROC , Valores de Referência , Medição de Risco/estatística & dados numéricosRESUMO
INTRODUCTION: Recent publications frequently introduce new indexes to measure glycemic variability (GV), quality of glycemic control, or glycemic risk; however, there is a lack of evidence supporting the use of one particular parameter, especially in clinical practice. METHODS: A cohort of type 2 diabetes mellitus (T2DM) patients in ambulatory care were followed using continuous glucose monitoring sensors (CGM). Mean glucose (MG), standard deviation, coefficient of variation (CV), interquartile range, CONGA1, 2, and 4, MAGE, M value, J index, high blood glucose index, and low blood glucose index (LBGI) were estimated. Hypoglycemia incidence (<54 mg/dl) was calculated. Area under the curve (AUC) was determined for different indexes as identifiers of patients with risk of hypoglycemia (IRH). Optimal cutoff thresholds were determined from analysis of the receiver operating characteristic curves. RESULTS: CGM data for 657 days from 140 T2DM patients (4.69 average days per patient) were analyzed. Hypoglycemia was present in 50 patients with 144 hypoglycemic events in total (incidence rate of 0.22 events per patient/day). In the multivariate analysis, both CV (OR 1.20, 95% CI 1.12-1.28, P < .001) and LBGI (OR 4.83, 95% CI 2.41-9.71, P < .001) were shown to have a statistically significant association with hypoglycemia. The highest AUC were for CV (0.84; 95% CI 0.77-0.91) and LBGI (0.95; 95% CI 0.92-0.98). The optimal cutoff threshold for CV as IRH was 34%, and 3.4 for LBGI. CONCLUSION: This analysis shows that CV can be recommended as the preferred parameter of GV to be used in clinical practice for T2DM patients. LBGI is the preferred IRH between glycemic risk indexes.
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Glicemia/análise , Complicações do Diabetes/epidemiologia , Diabetes Mellitus Tipo 2/sangue , Índice Glicêmico , Hipoglicemia/epidemiologia , Idoso , Estudos de Coortes , Feminino , Humanos , Incidência , Masculino , Pessoa de Meia-Idade , Estudos ProspectivosRESUMO
INTRODUCTION: Clinical interventional studies in diabetes mellitus usually exclude patients undergoing peritoneal dialysis (PD). This study evaluates the impact of an educational program and a basal-bolus insulin regimen on the blood glucose level control and risk of hypoglycemia in this population. METHODS: A before-and-after study was conducted in type 1 and type 2 DM patients undergoing PD at the Renal Therapy Services (RTS) clinic network, Bogota, Colombia. An intervention was instituted consisting of a three-month educational program and a basal-bolus detemir (Levemir, NovoNordisk) and aspart (Novorapid, NovoNordisk) insulin regimen. Prior to the intervention and at the end of treatment were conducted measures of HbA1c levels and continuous glucose monitoring (CGM). RESULTS: Forty-seven patients were recruited. Mean HbA1c level decreased from 8.41% ± 0.83 to 7.68% ± 1.32 (mean difference -0.739, 95% CI -0.419, -1.059; P < .0001). Of subjects, 52% achieved HbA1c levels <7.5% at the end of study. Mean blood glucose level reduced from 194.0 ± 42.5 to 172.9 ± 31.8 mg/dl ( P = .0015) measured by CGM. Significant differences were not observed in incidence of overall ( P = .7739), diurnal ( P = .3701), or nocturnal ( P = .5724) hypoglycemia episodes nor in area under the curve (AUC) <54 mg/dl ( P = .9528), but a reduction in AUC >180 ( P < .01) and AUC >250 ( P = .01) was evidenced for total, diurnal, and nocturnal episodes. CONCLUSIONS: An intervention consisting of an educational program and a basal-bolus insulin regimen in type 1 and type 2 diabetes mellitus patients undergoing PD caused a decrease in HbA1c levels, and mean blood glucose levels as measured from CGM with no significant increases in hypoglycemia episodes.