Effects of Sensor-Augmented Pump Therapy on Glycemic Variability in Well-Controlled Type 1 Diabetes in the STAR 3 Study
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Bibliographic record
Abstract
BACKGROUND: Compared with multiple daily injections (MDI), sensor-augmented pump (SAP) insulin therapy may reduce glycemic variability and oxidative stress in type 1 diabetes in a glycosylated hemoglobin (A1C)-independent manner. SUBJECTS AND METHODS: The STAR 3 study compared SAP with MDI therapy for 1 year. Week-long continuous glucose monitoring studies were conducted at baseline and 1 year for assessment of glycemic variability in both groups. Soluble CD40 ligand (CD40L), a biomarker of inflammation and thrombocyte function, was measured at baseline and 1 year. Subjects were classified according to treatment group and 1-year A1C levels (<6.5%, 6.5-6.9%, 7-7.9%, ≥8%). Glycemic parameters were compared between SAP and MDI subjects in each A1C cohort. RESULTS: At 1 year, sensor glucose values at A1C levels ≥6.5% were similar in the SAP and MDI groups. However, sensor glucose SD and coefficient of variation (CV) values were lower at A1C levels <8% among SAP than among MDI subjects; the overall between-group difference was significant for both SD (P<0.01) and CV (P=0.01). The overall mean amplitude of glycemic excursion was similar in MDI and SAP groups (P=0.23). CD40L levels fell over the course of the study in both groups, but the between-group difference was not significant (P=0.18). CD40L concentrations were unrelated to A1C, change in A1C from baseline, or glycemic variability. CONCLUSIONS: At comparable A1C levels of <8%, SAP reduced glycemic variability as measured by SD and CV compared with MDI. SAP may provide beneficial reductions in the number and severity of glycemic excursions.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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