Intensive Glycemic Control Is Not Associated With Fractures or Falls in the ACCORD Randomized Trial
Bibliographic record
Abstract
OBJECTIVE: Older adults with type 2 diabetes are at high risk of fractures and falls, but the effect of glycemic control on these outcomes is unknown. To determine the effect of intensive versus standard glycemic control, we assessed fractures and falls as outcomes in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) randomized trial. RESEARCH DESIGN AND METHODS: ACCORD participants were randomized to intensive or standard glycemia strategies, with an achieved median A1C of 6.4 and 7.5%, respectively. In the ACCORD BONE ancillary study, fractures were assessed at 54 of the 77 ACCORD clinical sites that included 7,287 of the 10,251 ACCORD participants. At annual visits, 6,782 participants were asked about falls in the previous year. RESULTS: During an average follow-up of 3.8 (SD 1.3) years, 198 of 3,655 participants in the intensive glycemia and 189 of 3,632 participants in the standard glycemia group experienced at least one nonspine fracture. The average rate of first nonspine fracture was 13.9 and 13.3 per 1,000 person-years in the intensive and standard groups, respectively (hazard ratio 1.04 [95% CI 0.86-1.27]). During an average follow-up of 2.0 years, 1,122 of 3,364 intensive- and 1,133 of 3,418 standard-therapy participants reported at least one fall. The average rate of falls was 60.8 and 55.3 per 100 person-years in the intensive and standard glycemia groups, respectively (1.10 [0.84-1.43]). CONCLUSIONS: Compared with standard glycemia, intensive glycemia did not increase or decrease fracture or fall risk in ACCORD.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".