Hybrid Closed Loop in Adults With Type 1 Diabetes and Severely Impaired Hypoglycemia Awareness
Bibliographic record
Abstract
Background: Benefits of hybrid closed-loop (HCL) systems in a high-risk group with type 1 diabetes and impaired awareness of hypoglycemia (IAH) have not been well-explored. Methods: Adults with Edmonton HYPO scores ≥1047 were randomized to 26-weeks HCL (MiniMed™ 670G) vs standard therapy (multiple daily injections or insulin pump) without continuous glucose monitoring (CGM) (control). Primary outcome was percentage CGM time-in-range (TIR; 70-180 mg/dL) at 23 to 26 weeks post-randomization. Major secondary endpoints included magnitude of change in counter-regulatory hormones and autonomic symptom responses to hypoglycemia at 26-weeks post-randomization. A post hoc analysis evaluated glycemia risk index (GRI) comparing HCL with control groups at 26 weeks post-randomization. Results: Nine participants (median [interquartile range (IQR)] age 51 [41, 59] years; 44% male; enrolment HYPO score 1183 [1058, 1308]; Clarke score 6 [6, 6]; n = 5 [HCL]; n = 4 [control]) completed the study. Time-in-range was higher using HCL vs control (70% [68, 74%] vs 48% [44, 50%], P = .014). Time <70 mg/dL did not differ (HCL 3.8% [2.7, 3.9] vs control 6.5% [4.3, 8.6], P = .14) although hypoglycemia episode duration was shorter (30 vs 50 minutes, P < .001) with HCL. Glycemia risk index was lower with HCL vs control (38.1 [30.0, 39.2] vs 70.8 [58.5, 72.4], P = .014). Following 6 months of HCL use, greater dopamine (24.0 [12.3, 27.6] vs −18.5 [−36.5, −4.8], P = .014), and growth hormone (6.3 [4.6, 16.8] vs 0.5 [−0.8, 3.0], P = .050) responses to hypoglycemia were observed. Conclusions: Six months of HCL use in high-risk adults with severe IAH increased glucose TIR and improved GRI without increased hypoglycemia, and partially restored counter-regulatory responses. Clinical trial registration: ACTRN12617000520336
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".