Hypoglycaemia events with <scp>iGlarLixi</scp> versus premix biphasic insulin aspart 30 ( <scp>BIAsp</scp> 30) in people with type 2 diabetes advancing from basal insulin: An analysis of the <scp>SoliMix</scp> trial
Bibliographic record
Abstract
AIMS: To explore details of the incidence and rates of daytime and nocturnal hypoglycaemia, levels of hypoglycaemia, and relationship to glycated haemoglobin (HbA1c), when comparing iGlarLixi versus premixed biphasic insulin aspart 30 (BIAsp 30) in the SoliMix randomized controlled trial. MATERIALS AND METHODS: This exploratory analysis of SoliMix used logistic regression and negative binomial regression analyses to assess between-treatment differences in the incidence and rates of hypoglycaemia by time of day. A negative binomial model was used to derive estimated annualized hypoglycaemia rates as a function of HbA1c. RESULTS: iGlarLixi was associated with lower incidence and rates of American Diabetes Association Level 2 (<54 mg/dL [<3.0 mmol/L]) hypoglycaemia during both night and day versus BIAsp 30. Incidence and rates of Level 1 (<70 to ≥54 mg/dL [<3.9 to ≥3.0 mmol/L]) hypoglycaemia were also mostly shown to be reduced with iGlarLixi versus BIAsp 30. Severe (Level 3) events were too few for analysis (n = 3). iGlarLixi was associated with lower modelled event rates of Level 2 and Level 1 hypoglycaemia over a wide range of HbA1c levels versus BIAsp 30. CONCLUSIONS: These results show that the lower HbA1c levels and weight benefit seen with iGlarLixi versus premixed BIAsp 30 in people with type 2 diabetes advancing their basal insulin therapy in the SoliMix trial are also accompanied by a lower risk of hypoglycaemia at any time of day and across a broad range of HbA1c levels.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".