Simplified Meal Bolus Strategies with Control-IQ+ Automated Insulin Delivery Are Safe and Effective in Adults with Type 2 Diabetes
Bibliographic record
Abstract
Objective: To characterize simplified meal bolus strategies in adults with insulin-treated type 2 diabetes using automated insulin delivery (AID). Research Design and Methods: In the 2IQP study, a 13-week randomized, controlled trial comparing Control-IQ+ AID to continuation of pre-study insulin regimen with continuous glucose monitoring, 201 participants in the AID arm were classified by meal bolus strategy. Glycemic outcomes were compared to baseline. Results: 68 participants’ meal bolus strategies (33.8%) were classified as Carbohydrate Counting, 79 (39.3%) were classified as Preset Carbohydrate Amounts, 27 (13.4%) were classified as Fixed Insulin Doses, and 27 (13.4%) as Other Methods. All bolus strategies were associated with similar, significant improvements in HbA1c from baseline: −0.9% for Carbohydrate Counting ( P < 0.001), −1.1% for Preset Carbohydrate Amounts ( P < 0.001), −0.8% for Fixed Insulin Doses ( P < 0.001), and −0.9% for Other Methods ( P = 0.003). Hypoglycemia rates were low at baseline and remained low for all bolus strategies. As participants gained experience with the Control-IQ+ AID system, more participants opted to use a simplified bolus strategy in the second half of the study compared with the first half (63% vs. 52%). Conclusion: Simplified bolus strategies worked well for adults with type 2 diabetes using Control-IQ+ in the 2IQP trial. All bolus strategies led to substantial HbA1c improvements, without safety concerns.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".