A randomized trial of adding insulin glargine vs. avoidance of insulin in people with Type 2 diabetes on either no oral glucose‐lowering agents or submaximal doses of metformin and/or sulphonylureas. The Canadian INSIGHT (Implementing New Strategies with Insulin Glargine for Hyperglycaemia Treatment) Study
Bibliographic record
Abstract
AIMS: Insulin is generally withheld until people with Type 2 diabetes are unresponsive to other therapies. However, its potential advantages suggest that it could be added earlier to achieve glycaemic goals; this possibility was tested in a clinical trial. METHODS: Consenting adults aged 18-80 years with Type 2 diabetes for at least 6 months, HbA1c of 7.5-11%, and on 0, 1 or 2 oral agents, were randomized to one of two therapeutic approaches for 24 weeks: evening insulin glargine plus self-titration by 1 unit/day if the fasting plasma glucose (FPG) was > 5.5 mmol/l; or conventional therapy with physician adjustment of oral glucose-lowering agents if capillary FPG levels were > 5.5 mmol/l. The primary outcome was the first achievement of two consecutive HbA1c levels <or= 6.5%. RESULTS: Two hundred and six participants were allocated to glargine and 199 to oral agents. Compared with control subjects, participants receiving glargine: (i) were 1.68 times more likely to achieve two consecutive HbA1c levels <or= 6.5% (95% CI 1.00-2.83; P = 0.049); (ii) reduced their HbA1c by 1.55 vs. 1.25% (P = 0.005), achieving adjusted means of 7.0 vs. 7.2% (P = 0.0007); (iii) had lower FPG (P = 0.0001), non-high-density lipoprotein (HDL) cholesterol (P = 0.02) and triglycerides (P = 0.02); (iv) had greater increases in treatment satisfaction (P = 0.045); and (v) had a 1.9-kg greater increase in weight (P < 0.0001). No differences in hypoglycaemia were noted. CONCLUSIONS: Adding insulin glargine is more likely to achieve a lower HbA(1c) level than conventional therapy with oral agents.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".