Efficacy of Artificial Pancreas Use in Patients With Type 2 Diabetes Using Intensive Insulin Therapy: A Randomized Crossover Pilot Trial
Bibliographic record
Abstract
Artificial pancreas (AP) systems have proven efficacy and superiority in glucose control compared with other insulin delivery methods in patients with type 1 diabetes (1,2). Patients with type 2 diabetes (T2D) requiring intensive insulin therapy are difficult to treat and could potentially benefit from AP. Two published reports have addressed AP and T2D in hospitalized patients, with overall results favoring AP (2,3). We aimed to test the applicability of a single-hormone (SH) (insulin only) AP algorithm in patients with T2D who require multiple daily injections (MDI) of insulin. We conducted an open-label, randomized, crossover study to compare glucose control under SH-AP and MDI in adults with T2D (≥55 years old, BMI >25 kg/m2, on ≥3 insulin injections/day). Exclusion criteria were change in hypoglycemic agents within 6 weeks prior to or during the study, creatinine clearance <30 mL/min, macrovascular event within the past 6 months, infections and hospitalization within the past 2 months, severe hypoglycemia in the past 2 weeks, or morning basal insulin. Participants were recruited at diabetes clinics of three Canadian (Quebec) participating centers. Respective ethics committees approved the study with written informed consent. Dexcom G4 Platinum (Dexcom, San Diego, CA) was inserted 24 h before interventions and calibrated 2–3 times/day. In a crossover design, each participant underwent two 24-h intervention visits using SH-AP and MDI in randomized order (separated by at least 3 days). Schedules were identical between these interventions: arrival at the research center at 6:30 p.m. (dinner and insulin bolus prior to that at home), standardized evening snack, next day’s breakfast at 8:00 a.m., lunch at 12:00 p.m., dinner at 5:00 p.m., 15-min walks at 10:00 a.m. and 3:00 p.m., and …
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".