Reduced Glucose Variability Is Associated With Improved Quality of Glycemic Control in Patients With Type 2 Diabetes: A 12-Month Observational Study
Bibliographic record
Abstract
Background: Current diabetes management relies mainly on hemoglobin A1C measurement to assess quality of treatment and to adjust therapy. We assessed the long-term effectivity of therapeutic adjustments in type 2 diabetes with specific focus on indices of glucose variability and multiple criteria for quality of glycemic control. Methods: Continuous glucose monitoring data collected during an observational study involving 405 outpatients with type 2 diabetes were analyzed at baseline and after 12 months. We evaluated the following criteria for glucose variability and quality of glycemic control: mean amplitude of glycemic excursions (MAGE), SD around the mean sensor glucose, mean of daily differences (MODD), fasting and mean sensor glucose, time outside specified glucose ranges, the Glycemic Risk Assessment Diabetes Equation (GRADE) score, High Blood Glucose Index (HBGI), and Low Blood Glucose Index (LBGI). Patients were classified according to quartiles of MAGE. Results: Indices of glucose variability were reduced by 15 to 23% (P 8.9 mmol/l decreased by 57% and 36% (P 8.9 mmol/l (R 2 = 0.374 and 0.877, P < 0.001 for both). Conclusions: Reduction of elevated glucose variability in type 2 diabetic outpatients is associated with lower risk of hypo- and hyperglycemia, and lower A1C values.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".