Blood glucose monitoring by insulin‐treated pilots of commercial and private aircraft: An analysis of out‐of‐range values

Abstract

Aim To examine blood glucose measurements recorded as part of the diabetes protocol operated by the UK, Ireland and Austria, which allows commercial airline pilots with insulin‐treated diabetes to fly. Methods An observational study was conducted in pilots with insulin‐treated diabetes, granted medical certification to fly commercial or noncommercial aircraft, who recorded pre‐flight and hourly in‐flight blood glucose measurements. These values were correlated to a traffic light system (green 5.0 to 15.0 mmol/L; amber 4.0 to 4.9 mmol/L and 15.1 to 20.0 mmol/L; and red <4.0 mmol/L or >20.0 mmol/L) and studied for trends in glucose concentrations, time course within flight and any consequences. Pilot demographics were also analysed. Results Forty‐four pilots (90%) recorded one or more blood glucose value outside the green range during the 7 years of the study. Pilot age, diabetes type and duration, and follow‐up period were comparable among subgroups, and mean glycated haemoglobin did not differ before and after certification in a way which would indicate poorer glycaemic control in any subgroup. A total of 892 blood glucose values (2.31%) were outside the green range, with half reported in‐flight at various time intervals. There were 48 (0.12%) low red range values recorded, 14 (0.04%) of which occurred in‐flight; all but four were restored to within the green range by the time of the next measurement. Appropriate corrective action was taken for all out‐of‐range values, with no reports of pilot incapacitation from any cause. Conclusions The traffic light system appears effective in identifying and reducing the frequency and severity of out‐of‐range values.

Individualized Prediction of Blood Glucose Outcomes Using Compositional Data Analysis

“…DSSs have proven to be useful tools for patients and physicians [2,46,47]. Although glucose profiles have been treated as CoDa vectors in previous studies [15][16][17], there is no application in this branch of mathematics that is focused on predicting the mean and the CV as an information system or DSS tool for patients with T1D at specific hours of the day oriented to wide PH (2 h and 4 h).…”

“…"Traffic light" systems for clinical information and clinical support are well known [46,47]. Using the multiple linear regression model's predictions for mean and coefficient of variation, in addition to the estimates for minimum and maximum glucose levels over the next 2 and 4 h, a methodology was implemented to categorize each hour of the day into 3 and 5 categories, as illustrated in Figure 3.…”