Identification of Dysglycemia With Continuous Glucose Monitoring to Assess Clinical Evolution in Cystic Fibrosis

Plain-language summary

Cystic fibrosis (CF)-related diabetes (CFRD) is the most important emerging complication after pulmonary complications. This specific form of diabetes is associated with an increased morbidity and mortality. CFRD prevalence at the age of 10 is 10% and reaches 40 to 50% in adulthood, while a similar percentage is afflicted with milder dysglycemia also called pre-diabetes abnormalities. In order to identify patients at risk and to implement early therapeutic measures, an annual CFRD screening test is recommended for CF patients after 10 years of age. The standard 2-hour oral glucose tolerance test (OGTT) is the recommended screening test. However, this test is perceived by both patients and CF care teams as unpleasant while adding a significant burden and workload, resulting in screening rates lower than 50% in most centers. An ideal alternative test should be simpler, less invasive, more sensitive than an OGTT to establish risks for lung function and/or nutritional deterioration, and predict future CFRD risk. To date, compared to the OGTT, no alternative screening method has demonstrated its effectiveness. However, continuous glucose monitoring (CGM) is emerging as a possible alternative method. In patients living with CF, CGM is easy to use and can identify early dysglycemia, which in turn, can predict increased risk of accelerated decline of pulmonary function and/or weight, higher risk of pseudomonas colonization, and future risk of CFRD. However, these observations are based on studies of small sample size with very limited prospective data. Furthermore, many of the multiple CGM metrics that have been standardized are based on the risk of complications associated with Type 1 and Type 2 Diabetes. Thus, there is a need for prospective studies to identify the CGM metrics and the cut-off level that is relevant as a predictor of clinical deterioration and/or CFRD risk in CF. The identification of such CF-specific criteria would provide important information to target at-risk patients.

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