The impact of flash glucose monitoring on glycated hemoglobin in type 2 diabetes managed with basal insulin in Canada: A retrospective real-world chart review study
Bibliographic record
Abstract
Background: The real-world effect of intermittently scanned continuous glucose monitoring on glucose control in type 2 diabetes treated with basal insulin is uncertain. This retrospective real-world study aimed to evaluate change in glycated hemoglobin (HbA1c) amongst adults with type 2 diabetes managed with basal insulin starting flash glucose monitoring. Methods: Medical records were reviewed for adults with type 2 diabetes treated with basal insulin for ⩾1 year and using FreeStyle Libre TM Flash Glucose Monitoring for ⩾3 months. Prior to device use an HbA1c 8.0%–12.0% was recorded and a further HbA1c result was recorded 3–6 months (90–194 days) after starting device use. Results: Medical records ( n = 91) analyzed from six Canadian diabetes centers showed HbA1c significantly decreased by 0.8% ± 1.1 (mean ± SD, [ p < 0.0001]) from mean baseline HbA1c 8.9% ± 0.9 to 8.1% ± 1.0 at 3–6 months after initiating flash glucose monitoring. HbA1c improvement was not independently associated with age, BMI, insulin use duration, or sex. Conclusion: This Canadian real-world retrospective study showed significantly reduced HbA1c following initiation of flash glucose monitoring technology to further support management of type 2 diabetes treated with basal insulin.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".