Effects of Randomization to Intensive Glucose Control on Adverse Events, Cardiovascular Disease, and Mortality in Older Versus Younger Adults in the ACCORD Trial
Bibliographic record
Abstract
OBJECTIVE: We explore the effect of randomized treatment, comparing intensive to standard glucose-lowering strategies on major cardiovascular outcomes, death, and severe adverse events in older versus younger participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. RESEARCH DESIGN AND METHODS: Participants with type 2 diabetes (n = 10,251) with a mean age of 62 years, a median duration of diabetes of 10 years, and a median A1C of 8.1% (65 mmol/mol) were randomized to treatment strategies targeting either A1C <6.0% (42 mmol/mol) or 7.0-7.9% (53-63 mmol/mol) and followed for a mean of 3.7 years. Outcomes were analyzed within subgroups defined by baseline age (<65 vs. ≥65 years). RESULTS: Older and younger ACCORD participants achieved similar intensive-arm A1C levels and between-arm A1C differences. Within the older subgroup, similar hazards of the cardiovascular primary outcome and total mortality were observed in the two arms. While there was no intervention effect on cardiovascular mortality in the older subgroup, there was an increased risk in the intensive arm for the younger subgroup (older hazard ratio [HR] = 0.97; younger HR = 1.71; P = 0.03). Regardless of intervention arm, the older subgroup experienced higher annualized rates of severe hypoglycemia (4.45% intensive and 1.36% standard) than the younger subgroup (2.45% intensive and 0.80% standard). CONCLUSIONS: Intensive glucose lowering increased the risk of cardiovascular disease and total mortality in younger participants, whereas it had a neutral effect in older participants. The intensive to standard relative risk of severe hypoglycemia was similar in both age subgroups, with higher absolute rates in older participants within both treatment arms.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".