Glycaemic measures for 8914 adult FreeStyle Libre users during routine care, segmented by age group and observed changes during the COVID-19 pandemic.

AIM: To evaluate the impact of the stay-at-home policy on different glucose metrics for time in range (%TIR 3.9-10 mmol/L), time below range (%TBR < 3.9 mmol/L) and time above range (%TAR > 10 mmol/L) for UK adult FreeStyle Libre (FSL) users within four defined age groups and on observed changes during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: Data were extracted from 8914 LibreView de-identified user accounts for adult users aged 18 years or older with 5 or more days of sensor readings in each month from January to June 2020. Age-group categories were based on self-reported age on LibreView accounts (18-25, 26-49, 50-64 and ≥65 years). RESULTS: In January, prior to the COVID-19 pandemic, the 65 years or older age group had the highest %TIR (57.9%), while the 18-25 years age group had the lowest (51.2%) (P < .001). Within each age group, TIR increased during the analysed months, by 1.7% (26-49 years) to 3.1% (≥65 years) (P < .001 in all cases). %TBR was significantly reduced only in the 26-49 years age group, whereas %TAR was reduced by 1.5% (26-49 years) to 3.0% (≥65 years) (P < .001 in both cases). The proportion of adults achieving both of the more than 70% TIR and less than 4% TBR targets increased from 11.7% to 15.9% for those aged 65 years or older (P < .001) and from 6.0% to 9.1% for those aged 18-25 years (P < .05). Mean daily glucose-sensor scan rates were at least 12 per day and remained stable across the analysis period. CONCLUSIONS: Our data show the baseline glucose metrics for FSL users in the UK across different age groups under usual care. During lockdown in the UK, the proportion of adults achieving TIR consensus targets increased among FSL users.

Real world hypoglycaemia related to glucose variability and Flash glucose scan frequency assessed from global FreeStyle Libre data.

AIM: Flash glucose monitoring provides a range of glucose metrics. In the current study, we aim to identify those that indicate that glycaemic targets can be consistently met and contrast the total (t-CV) and within-day coefficient of variation (wd-CV) to guide the assessment of glucose variability and hypoglycaemia exposure. METHODS: De-identified data from Flash readers were collected. The readers were sorted into 10 equally sized groups of scan frequency followed by quartiles of estimated A1c (eA1c). A similar grouping was performed for the total coefficient of variation (t-CV) and within-day coefficient of variation (wd-CV). In addition, analysis of the association of time below 54 mg/dl and glucose variability measured by t-CV and wd-CV was performed. RESULTS: The dataset included 1 002 946 readers. Readers sorted by 10 equal groups of scan rate and quartiles by eA1c, t-CV and wd-CV represented 25 074 readers per group. The association of lower eA1c with higher time in range and reduced time above range was clear. The correlation of eA1c quartiles and time below range was not consistent. An association between glucose variability and hypoglycaemia was found. Both wd-CV and t-CV were associated with time below range. For achieving the consensus target of <1% time below 54 mg/dl, the associated wd-CV and t-CV values were 33.5% and 39.5%, respectively. CONCLUSIONS: The type of CV reported by the different continuous glucose monitoring systems should be acknowledged. CV <36% might not be adequate to ensure low hypoglycaemia exposure. To our knowledge, the majority of continuous glucose monitoring reports the t-CV. Appropriate thresholds should be used to identify patients that would probably meet time below range targets (t-CV <40% or wd-CV <34%).

Low Initial Adherence with Flash Glucose Monitoring is Not a Predictor of Long-Term Glycemic Outcomes: Longitudinal Analysis of the Association Between Experience, Adherence, and Glucose Control for FreeStyle Libre Users.

INTRODUCTION: Frequent scanning of FreeStyle Libre (FSL) flash glucose monitoring sensors is known to be important whilst wearing an active sensor, but adherence to sensor reapplication is also critical to effective glucose monitoring. We report novel measures of adherence for users of the FSL system and their association with improvements in metrics of glucose control. METHODS: Anonymous data were extracted for 1600 FSL users in the Czech Republic with ≥ 36 completed sensors from October 22, 2018 to December 31, 2021. "Experience" was defined by the number of sensors used (1-36 sensors). "Adherence" was defined by time between the end of one sensor and the start of the next (gap time). User adherence was analyzed for four experience levels after initiating FLASH; Start (sensors 1-3); Early (sensors 4-6); Middle (sensors 19-21); End (sensors 34-36). Users were split into two adherence levels based on mean gap time during Start period, "low" (> 24 h, n = 723) and "high" (≤ 8 h, n = 877). RESULTS: Low-adherence users reduced their sensor gap times significantly: 38.5% applied a new sensor within 24 h during sensors 4-6, rising to 65.0% by sensors 34-36 (p < 0.001). Improved adherence was associated with increased %TIR (time in range; mean + 2.4%; p < 0.001), reduced %TAR (time above range; mean - 3.1%; p < 0.001), and reduced glucose coefficient of variation (CV; mean - 1.7%; p < 0.001). CONCLUSIONS: With experience, FSL users became more adherent in sensor reapplication, with associated increases in %TIR, and reductions in %TAR and glucose variability.

Real-life 24-week changes in glycemic parameters among European users of flash glucose monitoring with type 1 and 2 diabetes and different levels of glycemic control.

AIM: To evaluate real-life changes of glycemic parameters among flash glucose monitoring (FLASH) users who do not meet glycemic targets. METHODS: De-identified data were obtained between 2014 and 2021 from patients using FLASH uninterrupted for a 24-week period. Glycemic parameters during first and last sensor use were examined in four identifiable groups: type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM) on basal-bolus insulin, T2DM on basal insulin, and T2DM without insulin treatment. Within each group, subgroup analyses were performed in persons with initial suboptimal glycemic regulation (time in range (TIR; 3.9-10 mmol/L) < 70%, time above range (TAR; >10 mmol/L) > 25%, or time below range (TBR; <3.9 mmol/L) > 4%). RESULTS: Data were obtained from 1,909 persons with T1DM and 1,813 persons with T2DM (1,499 basal-bolus insulin, 189 basal insulin, and 125 non-insulin users). In most of the performed analyses, both overall and in the various subgroups, significant improvements were observed in virtually all predefined primary (TIR) and secondary endpoints (eHbA1c, TAR, TBR and glucose variability). CONCLUSIONS: 24-weeks FLASH use in real life by persons with T1DM and T2DM with suboptimal glycemic regulation is associated with improvement of glycemic parameters, irrespective of pre-use regulation or treatment modality.

Frequency of flash glucose monitoring and glucose metrics: real-world observational data from Saudi Arabia.

BACKGROUND: This real-world data study analyzed glucose metrics from FreeStyle Libre® flash glucose monitoring in relation to scanning frequency, time in range (TIR) and estimated A1c (eA1c) in Saudi Arabia. METHODS: Anonymized reader data were analyzed according to scanning frequency quartiles, eA1c categories (<7%,≥7%‒≤9% or>9%) and TIR categories (<50%,≥50%‒≤70% or>70%). Sensors, grouped by reader, were required to have≥120 h of operation. Differences in scanning frequency, eA1c, TIR, time in hypoglycemia and hyperglycemia, and glucose variability (standard deviation [SD] and coefficient of variation [CV]) were analyzed between groups. RESULTS: 6097 readers, 35,747 sensors, and 40 million automatic glucose measurements were analyzed. Patients in the highest scanning frequency quartile (Q4, mean 32.0 scans/day) had lower eA1c (8.47%), greater TIR (46.4%) and lower glucose variation (SD 75.0 mg/dL, CV 38.2%) compared to the lowest quartile (Q1, mean 5.2 scans/day; eA1c 9.77%, TIR 32.8%, SD 94.9 mg/dL, CV 41.3%). Lower eA1c and higher TIR were associated with greater scanning frequency, lower glucose variability and less time in hyperglycemia. CONCLUSIONS: Higher scanning frequency in flash glucose users from Saudi Arabia is associated with lower eA1c, higher TIR, lower glucose variability and less time in hypoglycemia or hyperglycemia.

Flash Glucose Monitoring in the Netherlands: Increased monitoring frequency is associated with improvement of glycemic parameters.

AIMS: To evaluate the association between Flash Glucose Monitoring (FLASH) frequency and glycemic parameters during real-life circumstances in the Netherlands. METHODS: Obtained glucose readings were de-identified and uploaded to a dedicated database when FLASH reading devices were connected to internet. Data between September 2014 and March 2020, comprising 16,331 analyzable readers (163,762 sensors) were analyzed. Scan rate per reader was determined and each reader was sorted into 20 equally sized rank ordered groups (n = 817 each). RESULTS: Users performed a median of 11.5 [IQR 7.7-16.7] scans per day. Those in the lowest and highest ventiles scanned on average 3.7 and 40.0 times per day and had an eHbA1c of 8.6% (71 mmol/mol) and 6.9% (52 mmol/mol), respectively. Increasing scan rates were associated with more time in target range (3.9-10 mmol/L), less time in hyperglycemia (>10 mmol/L), and a lower standard deviation of glucose. An eHbA1c of 7.0% (53 mmol/mol) translated in approximately 65% time in target range, 30% time in hyperglycemia and 5% time in hypoglycemia (<3.9 mmol/L). CONCLUSIONS: These outcomes among Dutch FLASH users suggest that with higher scan rate glycemic control improves.

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.