A Randomized Trial of Automated Insulin Delivery in Type 2 Diabetes
Bibliographic record
Abstract
BACKGROUND: Automated insulin delivery (AID) systems have been shown to be beneficial for patients with type 1 diabetes, but data are needed from randomized, controlled trials regarding their role in the management of insulin-treated type 2 diabetes. METHODS: In this 13-week, multicenter trial, adults with insulin-treated type 2 diabetes were randomly assigned in a 2:1 ratio to receive AID or to continue their pretrial insulin-delivery method (control group); both groups received continuous glucose monitoring (CGM). The primary outcome was the glycated hemoglobin level at 13 weeks. RESULTS: A total of 319 patients underwent randomization. Glycated hemoglobin levels decreased by 0.9 percentage points (from 8.2±1.4% at baseline to 7.3±0.9% at week 13) in the AID group and by 0.3 percentage points (from 8.1±1.2% to 7.7±1.1%) in the control group (mean adjusted difference, -0.6 percentage points; 95% confidence interval [CI], -0.8 to -0.4; P<0.001). The mean percentage of time that patients were in the target glucose range of 70 to 180 mg per deciliter increased from 48±24% to 64±16% in the AID group and from 51±21% to 52±21% in the control group (mean difference, 14 percentage points; 95% CI, 11 to 17; P<0.001). All other multiplicity-controlled CGM outcomes reflective of hyperglycemia that were measured were significantly better in the AID group than in the control group. The frequency of CGM-measured hypoglycemia was low in both groups. A severe hypoglycemia event occurred in one patient in the AID group. CONCLUSIONS: In this 13-week, randomized, controlled trial involving adults with insulin-treated type 2 diabetes, AID was associated with a greater reduction in glycated hemoglobin levels than CGM alone. (Funded by Tandem Diabetes Care; 2IQP ClinicalTrials.gov number, NCT05785832.).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".