Clinical Approach to Flash Glucose Monitoring: An Expert Recommendation

Chico, Ana; Aguilera, Eva; Ampudia‐Blasco, Francisco Javier; Bellido, Virgina; Cardona-Hernández, Roque; Escalada, Javier; Fernández, Diego; Gómez-Peralta, Fernando; Villar, Noemí González Pérez de; Gorgojo, Juan José; Mezquita-Raya, Pedro; Morales, Cristóbal; Velasco, Pedro de Pablos; Palomares, Rafael; Parra, Juan Carlos; Rivero, María Teresa; González-Blanco, Cintia

doi:10.1177/1932296819841911

Cited by 27 publications

(26 citation statements)

References 19 publications

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“…Glycemic control and reduction of hyperglycemia or hypoglycemia events are the main challenges in the clinical experience to achieve decreases of blood glucose variability ( 248 ). Indeed, levels of glucose and its constant fluctuations are good indicators of organ dysfunctions such as those associated with infections ( 249 ).…”

Section: Methods and Inclusion Criteriamentioning

confidence: 99%

Susceptibility for Some Infectious Diseases in Patients With Diabetes: The Key Role of Glycemia

Chávez-Reyes

Escárcega‐González

Chavira-Suárez

et al. 2021

Front. Public Health

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Uncontrolled diabetes results in several metabolic alterations including hyperglycemia. Indeed, several preclinical and clinical studies have suggested that this condition may induce susceptibility and the development of more aggressive infectious diseases, especially those caused by some bacteria (including Chlamydophila pneumoniae, Haemophilus influenzae, and Streptococcus pneumoniae, among others) and viruses [such as coronavirus 2 (CoV2), Influenza A virus, Hepatitis B, etc.]. Although the precise mechanisms that link glycemia to the exacerbated infections remain elusive, hyperglycemia is known to induce a wide array of changes in the immune system activity, including alterations in: (i) the microenvironment of immune cells (e.g., pH, blood viscosity and other biochemical parameters); (ii) the supply of energy to infectious bacteria; (iii) the inflammatory response; and (iv) oxidative stress as a result of bacterial proliferative metabolism. Consistent with this evidence, some bacterial infections are typical (and/or have a worse prognosis) in patients with hypercaloric diets and a stressful lifestyle (conditions that promote hyperglycemic episodes). On this basis, the present review is particularly focused on: (i) the role of diabetes in the development of some bacterial and viral infections by analyzing preclinical and clinical findings; (ii) discussing the possible mechanisms by which hyperglycemia may increase the susceptibility for developing infections; and (iii) further understanding the impact of hyperglycemia on the immune system.

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Section: Methods and Inclusion Criteriamentioning

confidence: 99%

Susceptibility for Some Infectious Diseases in Patients With Diabetes: The Key Role of Glycemia

Chávez-Reyes

Escárcega‐González

Chavira-Suárez

et al. 2021

Front. Public Health

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“…Compared with SMBG, CGM with interstitial glucose measurements at 5 min intervals provides a more comprehensive record during the day and night periods [ 20 , 34 ]. In recent years, Chico et al reported that flash glucose monitoring, a new approach to glucose monitoring, had a long sensor lifetime of 14 days and emerged as a practical solution to the glucose monitoring [ 36 ].…”

Section: Metrics and Measurement Of Gvmentioning

confidence: 99%

“…Long-term GV CV Variation around the mean blood glucose of HbA1c, FPG and PPG between sequential visits [19] SD Magnitude of variability relative to mean blood glucose of HbA1c, FPG and PPG between sequential visits [19] VIM Based on logarithmic curve fitting (the natural logarithm of SD over the natural logarithm of the mean) [22] Short-term GV Within-day or between-day GV CV Variation around the mean blood glucose [18] SD Magnitude of variability relative to mean blood glucose [18] LBGI/HBGI Measure of frequency and magnitude of hypoglycemia or hyperglycemia [31] ADRR Sum of the daily peak risks for hypoglycemia and hyperglycemia [32] Within-day GV MAGE Mean differences from peaks to nadirs [23] MAG Absolute differences between sequential readings divided by the time [8] CONGA Difference between a current blood glucose reading and a reading taken hours earlier [25] TIR Percentage of time spent within the target glucose range of 3.9-10.0 mmol/L during a 24-h period [26,27] Between-day GV MODD Absolute differences between two glucose values measured at the same time with a 24 h interval [28] AGP/IQRs Distribution of glucose data at a given timepoint [29,30] Measuring method of GV SMBG Reflected blood glucose fluctuations on the timescale of hours or days [20] CGM Interstitial glucose measurements at 5 min intervals [20,34] Flash glucose monitoring Measured interstitial glucose and indicated direction and speed of glucose change [36] Within-day GV Similar to long-term GV, SD and CV are also the common metrics of short-term GV. When averaging daily SD or CV, the mean of within-day daily GV can also be estimated over the stated time [18].…”

Section: Various Metrics and Measure Of Gv Description Or Definition mentioning

confidence: 99%

Comprehensive elaboration of glycemic variability in diabetic macrovascular and microvascular complications

Sun

Luo

Zhou

2021

Cardiovasc Diabetol

104

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Diabetes mellitus is the major risk factor for the development of macrovascular and microvascular complications. It is increasingly recognized that glycemic variability (GV), referring to oscillations in blood glucose levels and representing either short-term or long-term GV, is involved in the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for them. In this review, we summarize the metrics and measurement of GV in clinical practice, as well as comprehensively elaborate the role and related mechanisms of GV in diabetic macrovascular and microvascular complications, aiming to provide the mechanism-based therapeutic strategies for clinicians to manage diabetes mellitus.

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“…20 Flash glucose monitoring, a new approach to glucose monitoring, has emerged as a practical solution to the previous challenges of glucose monitoring. 21 In particular, the FreeStyle Libre flash glucose monitor (Abbott Diabetes Care, Witney, UK) enables patients to conveniently access their glucose levels at any time by scanning a sensor for glucose readings. The device does not require calibration, has a long sensor lifetime of 14 days, and is relatively affordable.…”

Section: Introductionmentioning

confidence: 99%

Flash glucose monitoring reduces glycemic variability and hypoglycemia: real-world data from Spain

Gómez-Peralta

Dunn²,

Landuyt

et al. 2020

BMJ Open Diab Res Care

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ObjectiveObservations in real-world settings support and extend findings demonstrated in randomized controlled trials that show flash glucose monitoring improves glycemic control. In this study, Spain-specific relationships between testing frequency and glycemic parameters were investigated under real-world settings.Research design and methodsDeidentified glucose and user scanning data were analyzed and readers were rank ordered into 20 equal sized groups by daily scan frequency. Glucose parameters were calculated for each group: estimated HbA1c, time below range (<70 and ≤54 mg/dL), within range (70–180 mg/dL), and above range (>180 mg/dL). Glycemic variability (GV) metrics were described and data obtained from sensors in Spain and worldwide were compared.ResultsSpanish users (n=22 949) collected 37.1 million glucose scans, 250 million automatically recorded glucose readings, and checked glucose values via a mean of 13 scans/day. Estimated HbA1c, time below 70 mg/dL, at or below 54 mg/dL, above 180 mg/dL, and GV metrics were significantly lower in the highest compared with lowest scan rate group (39.6 to 3.9 scans/day). Time-in-range was higher for the highest versus lowest scan rate group at 15.6 vs 11.5 hours/day, respectively. GV metrics correlated positively with time below 70 mg/dL, at or below 54 mg/dL, above 180 mg/dL, and negatively with time-in-range. The relationship between glucose metrics and scan rate was similar in Spain and worldwide. However, time in hypoglycemia in Spain was higher in the groups with lower scan rates.ConclusionsAs seen in clinical trials, flash glucose monitoring in real-world settings allows frequent glucose checks. High scan rates are associated with the favorable glycemic markers of increased time-in-range and reduced time in hyperglycemia and hypoglycemia, and GV. The same trends, with unique nuances, are observed in both Spanish and global data.

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Clinical Approach to Flash Glucose Monitoring: An Expert Recommendation

Cited by 27 publications

References 19 publications

Susceptibility for Some Infectious Diseases in Patients With Diabetes: The Key Role of Glycemia

Susceptibility for Some Infectious Diseases in Patients With Diabetes: The Key Role of Glycemia

Comprehensive elaboration of glycemic variability in diabetic macrovascular and microvascular complications

Flash glucose monitoring reduces glycemic variability and hypoglycemia: real-world data from Spain

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