The comparative effects of intensive glucose lowering in diabetes patients aged below or above 65 years: Results from the <scp>ADVANCE</scp> trial
Bibliographic record
Abstract
AIMS: For relatively old patients with diabetes, current guidelines recommend adjustment of glycaemic goals based on patients' cognitive function, or coexisting chronic illnesses. However, the evidence which supports the efficacy and safety of intensive glucose lowering in older patients with diabetes is scarce. The objective of the present study was to compare the efficacy and safety of intensive glucose lowering in patients with type 2 diabetes stratified by age (<65 and ≥ 65 years), and examine whether the effects differ according to patients' characteristics in the older patient group. MATERIALS AND METHODS: The effects of intensive glucose lowering (to a target glycated haemoglobin [HbA1c] concentration of ≤48 mmol/mol [6.5%]) on major clinical outcomes were evaluated by Cox regression models according to subgroups defined by baseline age of <65 or ≥ 65 years in the ADVANCE trial (n = 11 140). RESULTS: Over a median follow-up of 5 years, intensive glucose lowering significantly decreased the risk of the composite of major macrovascular and microvascular events (hazard ratio 0.90, 95% confidence interval 0.82-0.98), with no heterogeneity in the effects across age subgroups (p for heterogeneity = 0.44). Relative effects on all-cause death, cardiovascular death, and components of major vascular events were also similar (P for heterogeneity ≥0.06), except for severe hypoglycaemia, which was of greater risk for patients aged <65 years. Absolute benefits and harms were broadly consistent across subgroups. Among patients aged ≥65 years, randomized treatment effects did not differ significantly across different levels of cognitive function or coexisting chronic illnesses. CONCLUSIONS: Our results suggest that an intensive glycaemic control strategy to reduce HbA1c to 48 mmol/mol (6.5%) provided broadly similar benefits and harms and may be recommended for older, as well as younger, patients.
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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 | 0.005 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".