Accuracy of FreeStyle Libre in Adults with Type 1 Diabetes: The Effect of Sensor Age
Bibliographic record
Abstract
Background: FreeStyle Libre is a factory-calibrated continuous 14-day glucose sensor. Little is known about the accuracy of FreeStyle Libre as a function of sensor age. Methods: We assessed the accuracy of FreeStyle Libre in 14 adults with type 1 diabetes. Each study participant attended our research facility for two or three 24-h visits, during which they wore a FreeStyle Libre aged 0–1 day, 5–7 days, or 13–14 days. Plasma glucose levels were measured every 10–30 min using YSI2300 STAT Plus Analyser. Participants also wore Dexcom G5 ® glucose sensor aged 1–2 days. We assessed sensors' accuracy using mean absolute relative difference (MARD) between FreeStyle Libre, the Dexcom G5 sensor, and plasma glucose. Results: We had 1930 pairs of FreeStyle Libre sensor-plasma glucose measurements, collected from 36 FreeStyle Libre sensors, 18 of which were sensors aged 0–1 day, 9 were sensors aged 5–7 days, and 9 were sensors aged 13–14 days. The mean and median MARD for FreeStyle Libre sensors aged 0–1 days were 14.5% and 11.2%, respectively, and for sensors aged 13–14 days were 14.7% and 11.2%, respectively, but for sensors aged 5–7 days were 7.8% and 6.6%, respectively ( P = 0.03 vs. sensors aged 0–1 days, and P = 0.06 vs. sensors aged 13–14 days). The percentage of points falling in the potentially dangerous zones C, D, or E in Clarke's error grid analysis were 1.9% for FreeStyle Libre sensors aged 0–1 day, 0.2% for sensors aged 5–7 days, and 0.4% for sensors aged 13–14 days. The overall accuracy of FreeStyle Libre and Dexcom G5 sensor was the same (mean MARD 12.8% and 12.5%, respectively; P = 0.57). Conclusions: FreeStyle Libre's accuracy is adequate during its entire lifetime but is least accurate during its first and last days. ClinicalTrials.gov Identifier: NCT02814123
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".