Outpatient 60‐hour day‐and‐night glucose control with dual‐hormone artificial pancreas, single‐hormone artificial pancreas, or sensor‐augmented pump therapy in adults with type 1 diabetes: <scp>A</scp> n open‐label, randomised, crossover, controlled trial
Bibliographic record
Abstract
AIMS: To assess whether the dual-hormone (insulin and glucagon) artificial pancreas reduces hypoglycaemia compared to the single-hormone (insulin alone) artificial pancreas in outpatient settings during the day and night. MATERIAL AND METHODS: In a randomized, three-way, crossover trial we compared the dual-hormone artificial pancreas, the single-hormone artificial pancreas and sensor-augmented pump therapy (control) in 23 adults with type 1 diabetes. Each intervention was applied from 8 AM Day 1 to 8 PM Day 3 (60 hours) in outpatient free-living conditions. The primary outcome was time spent with sensor glucose levels below 4.0 mmol/L. A P value of less than .017 was regarded as significant. RESULTS: The median difference between the dual-hormone system and the single-hormone system was -2.3% (P = .072) for time spent below 4.0 mmol/L, -1.3% (P = .017) for time below 3.5 mmol/L, and -0.7% (P = .031) for time below 3.3 mmol/L. Both systems reduced (P < .017) hypoglycaemia below 4.0, 3.5 and 3.3 mmol/L compared to control therapy, but reductions were larger with the dual-hormone system than with the single-hormone system (medians -4.0% vs -3.4% for 4.0 mmol/L; -2.7% vs -2.2% for 3.5 mmol/L; and -2.2% vs -1.2% for 3.3 mmol/L). There were 34 hypoglycaemic events (<3.0 mmol/L for 20 minutes) with control therapy, 14 with the single-hormone system and 6 with the dual-hormone system. These differences in hypoglycaemia were observed while mean glucose level was low and comparable in all interventions (P = NS). CONCLUSIONS: The dual-hormone artificial pancreas had the lowest risk of hypoglycaemia, but the differences were not statistically significant. Larger studies are needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".