Continuous Glucose Monitoring for In-Flight Measurement of Glucose Levels of Insulin-Treated Pilots
Bibliographic record
Abstract
INTRODUCTION: Due to the risk of hypoglycemia-related incapacitation, diabetic pilots requiring insulin are assessed as unfit according to the International Civil Aviation Organization and most national authorities. Some authorities, such as those from Canada, the United Kingdom, and the United States, permit selected insulin-treated pilots (ITDM-pilots) to fly subject to a protocol requiring pre- and in-flight capillary glucose measurements to show safe levels (>100–<300 mg · dl−1). Critics of such permission question the practicability of these in-flight measurements and whether clinically desired glycemic targets can be achieved while keeping glucose levels in the safe range. Subcutaneous continuous glucose monitoring (CGM) has recently been approved by the FDA as a stand-alone method to provide accurate glucose levels and treatment decision guidance in patients. This commentary considers that use of CGM by ITDM pilots facilitates practicability and recording of in-flight glucose measurements and facilitates achievement of clinically desired glycemic targets without increasing hypoglycemia risks.Strollo F, Simons R, Mambro A, Strollo G, Gentile S. Continuous glucose monitoring for in-flight measurement of glucose levels of insulin-treated pilots. Aerosp Med Hum Perform. 2019; 90(8):735–737.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".