Accuracy of FreeStyle Libre in Adults with Type 1 Diabetes: The Effect of Sensor Age
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it