A Randomized Trial of a Home System to Reduce Nocturnal Hypoglycemia in Type 1 Diabetes
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Bibliographic record
Abstract
OBJECTIVE: Overnight hypoglycemia occurs frequently in individuals with type 1 diabetes and can result in loss of consciousness, seizure, or even death. We conducted an in-home randomized trial to determine whether nocturnal hypoglycemia could be safely reduced by temporarily suspending pump insulin delivery when hypoglycemia was predicted by an algorithm based on continuous glucose monitoring (CGM) glucose levels. RESEARCH DESIGN AND METHODS: Following an initial run-in phase, a 42-night trial was conducted in 45 individuals aged 15-45 years with type 1 diabetes in which each night was assigned randomly to either having the predictive low-glucose suspend system active (intervention night) or inactive (control night). The primary outcome was the proportion of nights in which ≥1 CGM glucose values ≤60 mg/dL occurred. RESULTS: Overnight hypoglycemia with at least one CGM value ≤60 mg/dL occurred on 196 of 942 (21%) intervention nights versus 322 of 970 (33%) control nights (odds ratio 0.52 [95% CI 0.43-0.64]; P < 0.001). Median hypoglycemia area under the curve was reduced by 81%, and hypoglycemia lasting >2 h was reduced by 74%. Overnight sensor glucose was >180 mg/dL during 57% of control nights and 59% of intervention nights (P = 0.17), while morning blood glucose was >180 mg/dL following 21% and 27% of nights, respectively (P < 0.001), and >250 mg/dL following 6% and 6%, respectively. Morning ketosis was present <1% of the time in each arm. CONCLUSIONS: Use of a nocturnal low-glucose suspend system can substantially reduce overnight hypoglycemia without an increase in morning ketosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.000 |
| 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