NIR-Based Electronic Platform for Glucose Monitoring for the Prevention and Control of Diabetes Mellitus.

The glucose level in the blood is measured through invasive methods, causing discomfort in the patient, loss of sensitivity in the area where the sample is obtained, and healing problems. This article deals with the design, implementation, and evaluation of a device with an ESP-WROOM-32D microcontroller with the application of near-infrared photospectroscopy technology that uses a diode array that transmits between 830 nm and 940 nm to measure glucose levels in the blood. In addition, the system provides a webpage for the monitoring and control of diabetes mellitus for each patient; the webpage is hosted on a local Linux server with a MySQL database. The tests are conducted on 120 people with an age range of 35 to 85 years; each person undergoes two sample collections with the traditional method and two with the non-invasive method. The developed device complies with the ranges established by the American Diabetes Association: presenting a measurement error margin of close to 3% in relation to traditional blood glucose measurement devices. The purpose of the study is to design and evaluate a device that uses non-invasive technology to measure blood glucose levels. This involves constructing a non-invasive glucometer prototype that is then evaluated in a group of participants with diabetes.

A concept for human use of real-time and remote monitoring of diabetic subjects using intermittent scanned continuous glucose measurement.

BACKGROUND: Flash glucose monitoring systems like the FreeStyle Libre (FSL) sensor have gained popularity for monitoring glucose levels in people with diabetes mellitus. This sensor can be paired with an off-label converted real-time continuous glucose monitor (c-rtCGM) plus an ad hoc computer/smartphone interface for remote real-time monitoring of diabetic subjects, allowing for trend analysis and alarm generation. OBJECTIVES: This work evaluates the accuracy and agreement between the FSL sensor and the developed c-rtCGM system. As real-time monitoring is the main feature, the system's connectivity was assessed at 5-min intervals during the trials. METHODS: One week of glucose data were collected from 16 type 1 diabetic rats using the FSL sensor and the c-rtCGM. Baseline blood samples were taken the first day before inducing type 1 diabetes with streptozotocin. Once confirmed diabetic rats, FSL and c-rtCGM, were implanted, and to improve data matching between the two monitoring devices, the c-rtCGM was calibrated to the FSL glucometer readings. A factorial design 2 × 3^3 and a second-order regression was used to find the base values of the linear model transformation of the raw data obtained from the sensor. Accuracy, agreement, and connectivity were assessed by median absolute relative difference (Median ARD), range averaging times, Parkes consensus error grid analysis (EGA), and Bland-Altman analysis with a non-parametric approach. RESULTS: Compared to the FSL sensor, the c-rtCGM had an overall Median ARD of 6.58%, with 93.06% of results in zone A when calibration was not carried out. When calibration frequency changed from every 50 h to 1 h, the overall Median ARD improved from 6.68% to 2.41%, respectively. The connectivity evaluation showed that 95% of data was successfully received every 5 min by the computer interface. CONCLUSIONS AND CLINICAL IMPORTANCE: The results demonstrate the feasibility and reliability of real-time and remote subjects with diabetes monitoring using the developed c-rtCGM system. Performing calibrations relative to the FSL readings increases the accuracy of the data displayed at the interface.

Continuous interstitial glucose monitoring for term newborns: analysis of the first day of life.

OBJECTIVE: Glycaemia in newborns changes significantly after birth; however, little is known about these changes. The objective was to describe continuous interstitial glucose values in term newborns who were exclusively breast fed on the first day of life. DESIGN: We studied 159 newborns with appropriate weights for gestational age, who were exclusively breast fed on the first day of life, using a continuous glucose monitoring device that calculates interstitial glucose every 5 min. The device was removed after 24 hours, and the results were analysed using the R program, which provides the minimum, maximum, median and a standard curve with centiles. RESULTS: At the second hour of life, the moment in which the sensor started to identify the newborn's glycaemia, interstitial glucose levels were 2.59-4.43 mmol/L (46.7-79.9 mg/dL). The median interstitial glucose level of the newborns during the first day of life was 3.33±0.48 mmol/L (60±8.6 mg/dL). Interstitial glucose levels dropped until the sixth hour of life, reaching 2.19-3.95 mmol/L (39.5-71.1 mg/dL), and then increased again. The maximum values were found at the 20th and 21st hours of life, which were 2.81-4.64 mmol/L (50.6-83.6 mg/dL). CONCLUSION: The interstitial glucose during the first 24 hours of life declined until the sixth hour of life, then increased around the 20th hour and remained stable until the end of the first day of life.

Association Between Diabetes Technology Use and Glycemic Outcomes in Adults With Type 1 Diabetes Over a Decade.

OBJECTIVE: To evaluate change in mean clinic HbA1c from 2014 to 2021 with diabetes technology use in adults with type 1 diabetes. RESEARCH DESIGN AND METHODS: In this single-center study, we analyzed diabetes technology use and mean clinic HbA1c among unique adults (age ≥18 years) with type 1 diabetes (last visit of the year per patient) between 1 January 2014 and 31 December 2021 from the electronic medical record. Diabetes technology use was defined as the use of continuous glucose monitors (CGMs) without an automated insulin delivery (AID) system or an AID system. Diabetes technology use and HbA1c over time were analyzed using mixed models adjusted for age, sex, and visit year. RESULTS: A total of 15,903 clinic visits over 8 years (mean 1,988 patients per year, 4,174 unique patients, 52.7% female, 80.0% Non-Hispanic White) showed significant increases in CGM and AID use (P < 0.001 for both), resulting in an increase of diabetes technology use from 26.9% in 2014 to 82.7% in 2021. These increases were associated with a lower mean clinic HbA1c (7.7-7.5%, P < 0.001) and a higher percentage of adults achieving an HbA1c <7.0% (32.3-41.7%, P < 0.001) from 2014 to 2021. The HbA1c difference between technology users and nonusers increased over time from 0.36% (95% CI 0.26-0.47%, P < 0.001) in 2014 to 0.93% (95% CI 0.80-1.06%, P < 0.001) in 2021. CONCLUSIONS: Adopting diabetes technology in adults with type 1 diabetes decreased HbA1c and increased the number of people achieving an HbA1c <7.0%, supporting the current international recommendation to offer AID systems to most individuals with type 1 diabetes.

Flash glucose monitoring system in patients with type 1 diabetes in healthcare center in Brazil: real world data from a short-term prospective study.

Objective: To evaluate the alternate use of flash glucose monitoring (FGM) with self-monitoring blood glucose (SMBG), in patients with type 1 diabetes (T1D). Materials and methods: Two weeks of open FGM (P2), both preceded (P1) and followed by 2 weeks (P3) of SMBG with a blinded FGM system. Mean absolute relative difference (MARD) was calculated by (|FGMi - SMBGi|) / SMBGi, where it was a paired data sample. Results: In total, 34 patients were evaluated. Time in range (TIR) did not change between P1 and P2. In 12 patients (35.3%), TIR increased from 40% at P1 to 52% at P2 (p = 0.002) and in 22 (64.7%), TIR decreased or did not change. FGM use resulted in decreased % time spent in hypoglycemia (<70 mg/dL) (6.5% vs. 5.0%; p = 0.005), increased % time spent in hyperglycemia (>180 mg/dL) (44.5% to 51%; p = 0.046) with no significant change in % TIR. The proportion of patients who reached sensor-estimated glycated hemoglobin (eA1c) < 7% decreased from 23.5% at P1 to 12.9% at P2, p = 0.028. For the whole sample, the MARD between the two methods was 15.5% (95% CI 14.5-16.6%). For normal glucose range, hyperglycemic levels and hypoglycemic levels MARD were 16.0% (95% CI 15.0-17.0%), 13.3% (95% CI 11.5-15.2%) and 23.4% [95% CI 20.5-26.3%)], respectively. Conclusion: FGM after usual SMBG decreased the % time spent in hypoglycemia concomitant with an undesired increase in % time spent in hyperglycemia. Lower accuracy of FGM regarding hypoglycemia levels could result in overcorrection of hypoglycemia.

Observaciones en el mundo real sobre la efectividad del sistema flash de monitorización de glucosa en la práctica clínica en Chile / Real-world observations of the effectiveness of the flash glucose monitoring in clinical practice in Chile

OBJETIVO: Evaluar el tiempo en rango de glucosa y su asociación con otras medidas del control glicémico establecidas por el consenso internacional del tiempo en rango en usuarios de vida real del sistema flash de monitorización de glucosa FreeStyle LibreTM en Chile. MÉTODOS: Se analizaron los datos provenientes de la base de datos Freestyle Libre™ entre diciembre de 2014 y enero de 2022. Las lecturas se dividieron en 10 grupos (deciles) del mismo tamaño (cada decil contenía aproximadamente 498 usuarios) en función del tiempo en rango. Para cada decil se calculó la media de determinaciones diarias, el promedio de glucosa, la HbA1c, la desviación estándar de glucosa, el coeficiente de variación de la glucosa, el tiempo en rango, el tiempo de glucosa (porcentaje) por encima de 250 mg/dL (TA250), el tiempo de glucosa (porcentaje) por encima de 180 mg/dL (TA180), el tiempo por debajo (porcentaje) de 70 mg/dL (TB70) y el tiempo por debajo (porcentaje) de 54 mg/dL (TB54). RESULTADOS: Desde diciembre de 2014 hasta enero de 2022 hubo 4984 lectores. El grupo con el mayor tiempo en rango mostró significativamente una menor glucosa promedio que el grupo con el tiempo en rango más bajo (decil 1: media 248,3 mg/dL, decil 10: media 113,2 mg/L, diferencia ­135,1 mg/dL, p<0.05). Asimismo, el mayor tiempo en rango se asoció con una menor desviación estándar (decil 1: media 93,7mg/dL, decil 10: media 26,7mg/L, diferencia: -67,0 mg/ dL, p<0,05), menor coeficiente de variación (decil 1: media 37,8%, decil 10: media 23,3%, diferencia: -14,5%, p<0,05), menor TA250 (decil 1: media 46,5%, decil 10: media 0,2%, diferencia: -46,3%, p<0.05), menor TA180 (decil 1: media 73,9%, decil 10: media 3,8%, diferencia: -70,1%, p<0.05), menor TB70 (decil 5: mediana 6,13%, decil 10: mediana 1,70%, diferencia: -4,43%, p<0.05) y menor TB54 (decil 5: mediana 1,79%, decil 10: mediana 0,12%, diferencia: -1,67%, p<0.05). El mayor tiempo en rango se asoció también significativamente con más determinaciones diarias (decil 1: media 11,4, decil 10: media 16,6, diferencia: 5,2, p<0,05). La frecuencia media de las determinaciones entre todos los lectores fue de 14,7 determinaciones diarias. CONCLUSIONES: En los pacientes con diabetes en Chile, el empleo del sistema flash de monitorización demuestra la asociación entre el mayor tiempo en rango, la reducción de la variabilidad de la glucosa y un menor riesgo de hiperglucemias e hipoglicemias y también con un mayor compromiso.

OBJECTIVE: To evaluate glucose time in range and its association with other metrics of glucose control established by the International Consensus on TIR amongst real-life patients using the Flash Glucose Monitoring system FreeStyle LibreTM in Chile. METHODS: Data from the Freestyle Libre™ database between December 2014 and January 2022 were analyzed. Readers were divided into 10 groups (deciles) of the same size (each decile had approximately 498 users) according to time in range. For each decile of time in range, the mean of daily scans, average glucose, estimated HbA1c, glucose standard deviation, glucose coefficient of variation, time in range, glucose time (percentage) above 250 mg/dL (TA250), and glucose time (percentage) above 180 mg/dL (TA180), and the median of glucose time (percentage) below 70 mg/dL (TB70) and glucose time (percentage) below 54 mg/dL (TB54), were calculated. RESULTS: From December 2014 to January 2022, there were 4984 readers. The group with the highest TIR showed significantly lower average glucose than the group with the lowest TIR (decile 1: mean 248.3 mg/dL, decile 10: mean 113.2 mg/L, difference: ­135.1 mg/dL, p<0.05). In addition, more time in range was associated with a lower glucose standard deviation (decile 1: mean 93.7 mg/dL, decile 10: mean 26.7 mg/L, difference: -67.0 mg/dL, p<0.05), lower glucose coefficient of variation (decile 1: mean 37.8%, decile 10: mean 23.3%, difference: -14.5%, p<0.05), lower TA250 (decile 1: mean 46.5%, decile 10: mean 0.2%, difference: -46.3%, p<0.05),lower TA180 (decile 1: mean 73.9%, decile 10: mean 3.8%, difference: -70.1%, p<0.05), lower TB70 (decile 5: median 6.13%, decile 10: median 1.70%, difference: -4.43%, p<0.05) and lower TB54 (decile 5: median 1.79%, decile 10: median 0.12%, difference: -1.67%, p<0.05). Greater TIR was also associated with significantly more daily scans (decile 1: mean 11.4, decile 10: mean 16.6, difference: 5.2, p<0.05). Mean scan frequency amongst all readers was 14.7 daily scans. CONCLUSIONS: In patients with diabetes from Chile, the use of the flash glucose monitoring system demonstrates the association between greater TIR, reduced glucose variability, and reduced risk of hyperglycemia and hypoglycemia, and also its association with greater engagement.

Monitoreo continuo de glucosa en tiempo real en personas con Diabetes Mellitus tipo 1 / Continuous real-time glucose monitoring people with type 1 Diabetes Mellitu

INTRODUCCIÓN: Este documento técnico se realiza a solicitud de la Dirección de Prevención y Control de Enfermedades No Transmisibles, Raras y Huérfanas del Ministerio de Salud; la cual motivó la realización de la pregunta PICO por parte de médicos y especialistas de la siguiente manera, P: personas con diabetes tipo 1; I: dispositivos de monitoreo continuo de glucosa en tiempo real; C: automonitoreo de glucosa; O: cambio en niveles de hemoglobina glicosilada, tiempo en el rango, hiperglicemia, hipoglicemia, otros eventos adversos y calidad de vida. a. Cuadro clínico: La Diabetes Mellitus tipo 1 (DM1) es una enfermedad crónica que produce incremento de los niveles de glicemia debido a una deficiencia de insulina como consecuencia de la pérdida de células ß en el páncreas. En Perú, la incidencia estandarizada por edad es de 0.5 x 100 mil personas de 0-19 años. Las personas con DM1 tienen mayor riesgo de enfermedades cardiovasculares y complicaciones microvasculares como neuropatía, nefropatía y retinopatía. El monitoreo de glucosa (mediante automonitoreo con glucómetro o dispositivos de monitoreo continuo) constituye una parte integral del manejo de la enfermedad. b. Tecnología sanitária: Un dispositivo de MCG en tiempo real consiste en un sensor colocado debajo de la piel que mide la concentración de glucosa en el líquido intersticial a intervalos de 1 a 5 minutos, y un transmisor que transmite de manera continua los datos del sensor al receptor con la finalidad de mejorar el control glicémico. OBJETIVO: Describir la evidencia científica sobre la eficacia y seguridad del uso de dispositivos de monitoreo continuo de glucosa en tiempo real en personas con Diabetes Mellitus tipo 1. METODOLOGÍA: Se realizó una búsqueda sistemática en Medline (Ovid), The Cochrane Library y LILACS utilizando la estrategia de búsqueda descrita en el Anexo 01. Ésta se complementó con la búsqueda de evidencia en páginas institucionales de agencias gubernamentales y buscadores genéricos. Se priorizó la identificación y selección de ensayos clínicos aleatorizados controlados (ECA), revisiones sistemáticas (RS) de ECA, guías de práctica clínica (GPC), evaluaciones de tecnología sanitaria (ETS) y evaluaciones económicas (EE) de América Latina. La calidad de la evidencia se valoró usando: AMSTAR 2 para revisiones sistemáticas, la herramienta de la colaboración Cochrane para ensayos clínicos y AGREE II para valorar el rigor metodológico de las GPC. RESULTADOS: Hemoglobina glicosilada: (HbA1c) Un meta-análisis de 21 ensayos clínicos reportó menor nivel de HbA1c en participantes que usaron MCG, comparado con quienes emplearon automonitoreo de glucosa (diferencia de medias [DM]: -2.46 mmol/mol [−0.23%]: IC 95%: -3.83 a -1.08; p=0.0005; I 2= 72%). En diferentes análisis de subgrupos, las diferencias a favor del MCG solo se observaron en participantes con promedio de HbA1c >8% en la línea de base, con administración de insulina mediante múltiples inyecciones diarias y duración de la enfermedad menor a 10 años, así como en estudios con duración mayor a 24 semanas, y que usaron dispositivos de MCG adyuvantes (que requieren confirmación con glucosa capilar). Tiempo en el rango: Se reportó un incremento significativo del porcentaje de tiempo en el rango (glicemia: 70­180 mg/dl o 3.9­10 mmol/L) en los grupos tratados con MCG comparado con el automonitoreo de glucosa (DM: 5.37%; IC 95%: 3.54 a 7.20; I 2= 71.29%; 22 estudios). Hiperglicemia: Se reportó una disminución significativa del porcentaje de tiempo en el rango de hiperglicemia (glicemia >180 mg/dl o >10 mmol/L) en los grupos tratados con MCG comparado con el automonitoreo de glucosa (DM: -3.62%; IC 95%: -5.94 a -1.29; I 2= 74.82%). Hipoglicemia: Se reportó una disminución significativa del porcentaje de tiempo en el rango de hipoglicemia (glicemia < 70 mg/dl o < .9 mmol/L) en los grupos tratados con MCG comparado con automonitoreo de glucosa (DM: -1.77%; IC 95%: -2.70 a -0.83; I 2= 84.08%; 14 estudios). No observó diferencias en el riesgo de hipoglicemia severa (riesgo relativo [RR]: 0.60; IC 95%: 0.30 a 1.20; p=0.15; I2=57%; 11 estudios). Otros eventos adversos: No se observó diferencias entre el uso de MCG y automonitoreo de glucosa sobre el riesgo de sufrir eventos de cetoacidosis (RR: 1.06; IC 95%: 0.49 a 2.32; p=0.88; I2=0%; 14 estudios). Calidad de vida: No se observaron diferencias entre los participantes tratados con MCG o automonitoreo de glucosa respecto al miedo a la hipoglicemia, ni a la satisfacción del tratamiento. Recomendaciones en GPC: Las GPC de la American Diabetes Association, del National Institute for Health and Care Excellence del Reino Unido y de la de la Endocrine Society Clinical recomiendan ofrecer dispositivos de MCG en tiempo real a todos los jóvenes y adultos con DM1 considerando sus preferencias y que sean capaces de usar apropiadamente el dispositivo. En sentido contrario, las GPC de Colombia, México y Chile solo recomiendan estos dispositivos en personas que no han logrado una adecuado control glicémico. Evaluaciones de tecnología sanitária: La ETS del Ministerio de Sanidad de España establece una recomendación condicional a favor de la inclusión de sistemas de MCG para adultos con DM1 con mal control glucémico (HbA1c >7.5%) y/o riesgo de hipoglucemias graves. En niños, no recomienda su cobertura hasta que haya más estudios de calidad disponibles. La ETS de CADTH señala que existe importante incertidumbre sobre el beneficio clínico de usar dispositivos de MCG, debido al alto riesgo de sesgo, heterogeneidad e imprecisión entre los estudios incluidos en su revisión. Evaluación de la calidad metodológica: La certeza de evidencia fue considerada baja para todos los desenlaces críticos en población general con DM1. La calidad metodológica de las GPC varió entre 67.1% y 81.6%. CONCLUSIONES: Se identificó cuatro revisiones sistemáticas, dos evaluaciones de tecnología sanitaria y siete guías de práctica clínica. El uso de MCG redujo en alrededor de 0.23% los niveles de HbA1c, respecto al automonitoreo de glucosa. Las diferencias a favor del MCG se observaron principalmente en participantes con HbA1c >8% en la línea de base, con administración de insulina mediante múltiples inyecciones diarias y duración de la enfermedad menor a 10 años, así como en estudios con duración mayor a 24 semanas, y que usaron dispositivos de MCG adyuvantes (que requieren confirmación con glucosa capilar). El uso de MCG incrementó en un 5.37% el tiempo en el rango (≈1.3 horas), redujo el tiempo en hiperglicemia alrededor de un 3.62% (≈0.87 horas) y el tiempo en hipoglicemia en alrededor de 1.77% (≈0.43 horas). No se observó diferencias en el riesgo de hipoglicemia severa, cetoacidosis diabética y calidad de vida (miedo a la hipoglicemia o satisfacción con el tratamiento). La certeza de la evidencia fue considerada baja o muy baja debido al alto riesgo de sesgo, heterogeneidad e imprecisión entre los estudios incluidos en las cuatro revisiones sistemáticas consideradas para la presente ETS. Las GPC de Colombia, México y Chile recomiendan usar MCG en personas con inadecuado control glicémico, mientras que las GPC del NICE, ADA y ESC recomiendan ofrecerlos a todos los jóvenes y adultos con DM1 considerando preferencias personales y uso adecuado del dispositivo. La ETS del Ministerio de Sanidad de España recomienda dar cobertura a dispositivos de MCG en adultos con mal control glucémico y/o riesgo de hipoglucemias graves, y no recomienda dar cobertura en población pediátrica. La ETS de CADTH no establece una recomendación, aunque destaca que existe incertidumbre sobre el beneficio clínico de usar dispositivos de MCG.

[Sensor-Augmented Pump Therapy: description of pediatric patients with Type 1 Diabetes Mellitus (T1D) and initial metabolic outcomes]. / Uso de microinfusor de insulina con sistema integrado en pacientes pediátricos con diabetes tipo 1: resultados metabólicos iniciales.

The insulin microinfuser with integrated system (SAPT) for patients with type 1 Diabetes Mellitus (T1D) is included in the national financial protection system for high-cost treatments. OBJECTIVE: To describe the initial and first-year metabolic outcomes and epidemiological and nutritional characteristics of T1D pediatric patients treated with SAPT. PATIENTS AND METHOD: Retrospective, descriptive and analytical study of clinical records from 2017 to 2019, of 12 patients with T1D users of SAPT, attended in a referral hospital. VARIABLES: age at program entry, time of evolution of the disease, type of insulin treatment and type of glucose monitoring (capillary: sample or Continuous Glucose Monitoring [CGM]) at program entry, cause of application to the program, nutritional status, rural or urban origin, educational level of the main guardian, HbA1c at application and in the last month of each quarter after SAPT installation, over a 12-month period. HbA1c analysis was venous sample by High-Performance Liquid Chromatography and follow-up was capillary sample by Latex Particle Agglutination Inhibition. RESULTS: The median variables at 12 months of treatment were Total Daily Dose (TDD) 0.74, %Basal (%B) 49%, Time In Range (TIR) 39%, Time Below Range (TBR) 1%, and HbA1c 7.7%. The sensor usage time was met in all cases and only half of them achieved a correct execution of hyperglycemia and hypoglycemia treatment. Inadvertent severe hypoglycemia was the main cause of application to the program. CONCLUSION: TDD and %B increased, approaching physiological requirement, although without statistical significance, which could be attributed to the administra tion of adequate insulin with lower risk of hypoglycemia due to predictive suspension and CGM. TIR presented a favorable increase, although not significant, nor reaching the target range, attributable to the short observation time, difficulties in understanding and execution of our patients, and the learning process of the treating clinical team. SAPT was effective in hypoglycemia management and effective in improving HbA1c.

The Bihormonal Bionic Pancreas Improves Glycemic Control in Individuals With Hyperinsulinism and Postpancreatectomy Diabetes: A Pilot Study.

OBJECTIVE: To determine whether the bihormonal bionic pancreas (BHBP) improves glycemic control and reduces hypoglycemia in individuals with congenital hyperinsulinism (HI) and postpancreatectomy diabetes (PPD) compared with usual care (UC). RESEARCH DESIGN AND METHODS: Ten subjects with HI and PPD completed this open-label, crossover pilot study. Coprimary outcomes were mean glucose concentration and time with continuous glucose monitoring (CGM) glucose concentration <3.3 mmol/L. RESULTS: Mean (SD) CGM glucose concentration was 8.3 (0.7) mmol/L in the BHBP period versus 9 (1.8) mmol/L in the UC period (P = 0.13). Mean (SD) time with CGM glucose concentration <3.3 mmol/L was 0% (0.002) in the BHBP period vs. 1.3% (0.018) in the UC period (P = 0.11). CONCLUSIONS: Relative to UC, the BHBP resulted in comparable glycemic control in our population.

Daily glucose variation influenced by the use of corticosteroids in COVID-19 patients treated in Lima-Peru.

AIM: The pandemic has generated the need for COVID-19 patients to be treated as best as possible; however, the effect of these treatments on glycemic control has not yet been taken into account. This article aims to determine whether the daily variation of glucose is influenced by the use of corticosteroids in COVID-19 patients treated in Lima-Peru. METHODOLOGY: A prospective cohort study was undertook, in which glucose was measured four times a day in 53 patients hospitalized due to COVID-19. These values were associated with the use of corticosteroids and adjusted for other socio-educational variables, all by means of PA-GEE models. RESULTS: Nested multivariate analysis of daily glucose variation found that those using corticosteroids increased the daily average glucose as well as the first and last glucose measurements, this is, at 6am and 10pm, respectively (all p-values <0.026). An increase in glucose levels was also observed in those with diabetes (all p-values <0.001). In contrast, we found that there was a decrease in the last glucose measurement of the day in obese patients (p-value = 0.044). CONCLUSIONS: The patients who used corticosteroids for the treatment of COVID-19 increased the average glucose per day, especially in the first and last measurement.

Continuous glucose monitoring in obese pregnant women with no hyperglycemia on glucose tolerance test.

OBJECTIVE: The objective of the present study was to compare 24-hour glycemic levels between obese pregnant women with normal glucose tolerance and non-obese pregnant women. METHODS: In the present observational, longitudinal study, continuous glucose monitoring was performed in obese pregnant women with normal oral glucose tolerance test with 75 g of glucose between the 24th and the 28th gestational weeks. The control group (CG) consisted of pregnant women with normal weight who were selected by matching the maternal age and parity with the same characteristics of the obese group (OG). Glucose measurements were obtained during 72 hours. RESULTS: Both the groups were balanced in terms of baseline characteristics (age: 33.5 [28.7-36.0] vs. 32.0 [26.0-34.5] years, p = 0.5 and length of pregnancy: 25.0 [24.0-25.0] vs. 25.5 [24.0-28.0] weeks, p = 0.6 in the CG and in the OG, respectively). Pre-breakfast glycemic levels were 77.77 ± 10.55 mg/dL in the CG and 82.02 ± 11.06 mg/dL in the OG (p<0.01). Glycemic levels at 2 hours after breakfast were 87.31 ± 13.10 mg/dL in the CG and 93.48 ± 18.74 mg/dL in the OG (p<0.001). Daytime blood glucose levels were 87.6 ± 15.4 vs. 93.1 ± 18.3 mg/dL (p<0.001) and nighttime blood glucose levels were 79.3 ± 15.8 vs. 84.7 ± 16.3 mg/dL (p<0.001) in the CG and in the OG, respectively. The 24-hour, daytime, and nighttime values of the area under the curve were higher in the OG when compared with the CG (85.1 ± 0.16 vs. 87.9 ± 0.12, 65.6 ± 0.14 vs. 67.5 ± 0.10, 19.5 ± 0.07 vs. 20.4 ± 0.05, respectively; p<0.001). CONCLUSION: The results of the present study showed that obesity in pregnancy was associated with higher glycemic levels even in the presence of normal findings on glucose tolerance test.

The effects of professional continuous glucose monitoring as an adjuvant educational tool for improving glycemic control in patients with type 2 diabetes.

BACKGROUND: The study objective was to evaluate the effects of professional continuous glucose monitoring (CGM) as an adjuvant educational tool for improving glycemic control in patients with type 2 diabetes (T2D). METHODS: We conducted a three-month quasi-experimental study with an intervention (IGr) and control group (CGr) and ex-ante and ex-post evaluations in one family medicine clinic in Mexico City. Participants were T2D patients with HbA1c > 8% attending a comprehensive diabetes care program. In addition to the program, the IGr wore a professional CGM sensor (iPro™2) during the first 7 days of the study. Following this period, IGr participants had a medical consultation for the CGM results and treatment adjustments. Additionally, they received an educational session and personalized diet plan from a dietitian. After 3 months, the IGr again wore the CGM sensor for 1 week. The primary outcome variable was HbA1c level measured at baseline and 3 months after the CGM intervention. We analyzed the effect of the intervention on HbA1c levels by estimating the differences-in-differences treatment effect (Diff-in-Diff). Additionally, baseline and three-month CGM and dietary information were recorded for the IGr and analyzed using the Student's paired t-test and mixed-effects generalized linear models to control for patients' baseline characteristics. RESULTS: Overall, 302 T2D patients participated in the study (IGr, n = 150; control, n = 152). At the end of the three-month follow-up, we observed 0.439 mean HbA1C difference between groups (p = 0.004), with an additional decrease in HbA1c levels in the IGr compared with the CGr (Diff-in-Diff HbA1c mean of - 0.481% points, p = 0.023). Moreover, compared with the baseline, the three-month CGM patterns showed a significant increase in the percentage of time in glucose range (+ 7.25; p = 0.011); a reduction in the percentage of time above 180 mg/dl (- 6.01; p = 0.045), a decrease in glycemic variability (- 3.94, p = 0.034); and improvements in dietary patterns, shown by a reduction in total caloric intake (- 197.66 Kcal/day; p = 0.0001). CONCLUSION: Professional CGM contributes to reducing HbA1c levels and is an adjuvant educational tool that can improve glycemic control in patients with T2D. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04667728 . Registered 16/12/2020.

Virtual training on the hybrid close loop system in people with type 1 diabetes (T1D) during the COVID-19 pandemic.

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.

Comparison of 2 portable human glucometers for the measurement of blood glucose concentration in White New Zealand rabbits.

We compared measurements of blood glucose concentrations in 30 healthy adult White New Zealand rabbits using 2 commercial portable glucometers (PGM1 and PGM2) and a laboratory chemical analyzer. Results were analyzed with Pearson correlation, Passing-Bablok regression analysis, Bland-Altman analysis, and a modified error grid. Measurements with PGM1 were significantly correlated (r = 0.37) with those obtained from the laboratory reference method (RM); Bland-Altman and Passing-Bablok analyses indicated no significant systematic or proportional differences (mean difference of -0.26, 95% CI of mean difference of -0.54 to 0.01, and LOA of -1.70 to 1.17); and error grid resulted in 100% of measurements in zone A. No significant correlation (r = -0.05) was detected between PGM2 and RM; Bland-Altman and Passing-Bablok analyses results indicated a mean difference of 2.14, 95% CI of mean difference of 1.67-2.60, and limit of agreement of -0.32 to 4.59, which overestimated blood glucose concentration, with 53% of glucose measurements in error grid zone A and 47% in zone B. PGM1 was considered accurate in normoglycemic rabbits, whereas the use of PGM2 could result in overestimations of glycemia.

Youth Involvement in the Decision to Start CGM Predicts Subsequent CGM Use.

OBJECTIVE: The ability of continuous glucose monitoring (CGM) to improve diabetes outcomes depends upon consistent use. To identify factors that facilitate long-term use of CGM, this study tested the hypothesis that youth involvement in the decision to initiate this therapy would influence subsequent CGM use and that CGM self-efficacy and satisfaction mediate this relationship. RESEARCH DESIGN AND METHODS: Before initiating CGM, parent-youth dyads (i.e., pairs) from an academic endocrinology clinic completed assessments, including a measure of the child's involvement in the decision to start CGM. Two months into CGM use, youth completed measures of CGM self-efficacy and satisfaction. Fidelity of CGM use between weeks 5 and 12 was accessed via a cloud-based data repository. Hypotheses were tested with linear mixed-effects models, accounting for patients clustered within provider and repeated measures within patients. RESULTS: CGM use in 108 dyads (youth mean age 13.4 ± 2.7 years; 73% White) was positively predicted by baseline parent report of youth involvement in the CGM decision (P < 0.0001), and this relationship was mediated by youth's perceptions of CGM self-efficacy (P < 0.0001) and hassle (P = 0.014). So, when the youth shared their opinions about CGM with parents and participated in the decision to start, they perceived higher self-efficacy and lower hassle at 2-month follow-up, which predicted more days of use. This pattern held in models adjusting for youth race and sex and family income. CONCLUSIONS: To achieve maximum clinical benefit from CGM use, providers should facilitate youth involvement in the decision to initiate the device.

Use of Technology in Managing Diabetes in Youth, Part 1: Continuous Glucose Monitoring: Information and Tips for the School Nurse.

Glucose monitoring is an essential component of type 1 diabetes (T1D) treatment. Continuous glucose monitoring (CGM) systems measure glucose levels every few minutes and provide valuable trend information about the direction and speed glucose levels are changing. Use of CGM is increasing rapidly in youth with T1D and consistent use of CGM is associated with improved glycemic control. School nurses are a vital part of the care team for a student with T1D, and therefore, must be comfortable using CGM to support their students at school. This is the first article in a three-part series on the use of technology in managing diabetes in youth. The purpose of this article is to describe CGM devices, including calibration requirements and interpretation of trend arrows and provide tips for school nurses in incorporating CGM into the student's individualized healthcare plan. Part 2 in this series will focus on insulin pumps and Part 3 will focus on special considerations and problem solving when using diabetes technology in the school setting.

Use of flash glucose-sensing technology in patients with type 2 diabetes treated with liraglutide combined with CSII: a pilot study

Glycemic variability (GV) may be linked to the development of diabetic complications by inducing inflammation, oxidative stress, and endothelial dysfunction. Flash glucose monitoring (FGM) provides a novel method of continuously monitoring interstitial glucose levels for up to 14 days. This study randomly assigned poorly controlled type 2 diabetes mellitus patients treated with metformin and multiple daily injections of insulin (n=60) to either continuous subcutaneous insulin infusion (CSII) treatment or CSII in combination with liraglutide (CSII+Lira) treatment for 14 days during hospitalization. GV was assessed using a FGM system; weight and cardiometabolic biomarkers were also evaluated. The coefficient of variation was significantly reduced in the CSII+Lira group (P<0.001), while no significant change was observed in the CSII group. The changes differed significantly between the two groups in mean amplitude of glycemic excursions (P=0.004), standard deviation (P=0.006), and the percentage of time in the target range (4-10 mmol/L, P=0.005 and >10 mmol/L, P=0.028). The changes in mean of daily differences, interquartile range, and percentage of time in hypoglycemia (<3.3 mmol/L) and hyperglycemia (>13.9 mmol/L) identified by FGM showed no difference. Treatment with liraglutide increased serum adiponectin [33.5 (3.5, 47.7) pg/mL, P=0.003] and heme oxygenase-1 levels [0.4 (-0.0, 1.8) ng/mL, P=0.001] and reduced serum leptin levels [-2.8 (3.9) pg/mL, P<0.001]. Adding the glucagon-like peptide-1 analog liraglutide improved GV, weight, and some cardiometabolic risk markers. The FGM system is, therefore, shown to be a novel and useful method for glucose monitoring.

Use of flash glucose-sensing technology in patients with type 2 diabetes treated with liraglutide combined with CSII: a pilot study.

Glycemic variability (GV) may be linked to the development of diabetic complications by inducing inflammation, oxidative stress, and endothelial dysfunction. Flash glucose monitoring (FGM) provides a novel method of continuously monitoring interstitial glucose levels for up to 14 days. This study randomly assigned poorly controlled type 2 diabetes mellitus patients treated with metformin and multiple daily injections of insulin (n=60) to either continuous subcutaneous insulin infusion (CSII) treatment or CSII in combination with liraglutide (CSII+Lira) treatment for 14 days during hospitalization. GV was assessed using a FGM system; weight and cardiometabolic biomarkers were also evaluated. The coefficient of variation was significantly reduced in the CSII+Lira group (P<0.001), while no significant change was observed in the CSII group. The changes differed significantly between the two groups in mean amplitude of glycemic excursions (P=0.004), standard deviation (P=0.006), and the percentage of time in the target range (4-10 mmol/L, P=0.005 and >10 mmol/L, P=0.028). The changes in mean of daily differences, interquartile range, and percentage of time in hypoglycemia (<3.3 mmol/L) and hyperglycemia (>13.9 mmol/L) identified by FGM showed no difference. Treatment with liraglutide increased serum adiponectin [33.5 (3.5, 47.7) pg/mL, P=0.003] and heme oxygenase-1 levels [0.4 (-0.0, 1.8) ng/mL, P=0.001] and reduced serum leptin levels [-2.8 (3.9) pg/mL, P<0.001]. Adding the glucagon-like peptide-1 analog liraglutide improved GV, weight, and some cardiometabolic risk markers. The FGM system is, therefore, shown to be a novel and useful method for glucose monitoring.