Intensification of medication and glycaemic control among patients with type 2 diabetes – the <scp>ADVANCE</scp> trial
Bibliographic record
Abstract
AIMS: The aim of this study was to assess associations between patient characteristics, intensification of blood glucose-lowering treatment through oral glucose-lowering therapy and/or insulin and effective glycaemic control in type 2 diabetes. METHODS: 11 140 patients from the Action in Diabetes and Vascular disease: preterAx and diamicroN-MR Controlled Evaluation (ADVANCE) trial who were randomized to intensive glucose control or standard glucose control and followed up for a median of 5 years were categorized into two groups: effective glycaemic control [haemoglobin A1c (HbA1c) ≤ 7.0% or a proportionate reduction in HbA1c over 10%] or ineffective glycaemic control (HbA1c > 7.0% and a proportionate reduction in HbA1c less than or equal to 10%). Therapeutic intensification was defined as addition of an oral glucose-lowering agent or commencement of insulin. Pooled logistic regression models examined the associations between patient factors, intensification and effective glycaemic control. RESULTS: A total of 7768 patients (69.7%), including 3198 in the standard treatment group achieved effective glycaemic control. Compared to patients with ineffective control, patients with effective glycaemic control had shorter duration of diabetes and lower HbA1c at baseline and at the time of treatment intensification. Treatment intensification with addition of an oral agent or commencement of insulin was associated with a 107% [odds ratio, OR: 2.07 (95% confidence interval, CI: 1.95-2.20)] and 152% [OR: 2.52 (95% CI: 2.30-2.77)] greater chance of achieving effective glycaemic control, respectively. These associations were robust after adjustment for several baseline characteristics and not modified by the number of oral medications taken at the time of treatment intensification. CONCLUSIONS: Effective glycaemic control was associated with treatment intensification at lower HbA1c levels at all stages of the disease course and in both arms of the ADVANCE trial.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".