Effects of TZD Use and Discontinuation on Fracture Rates in ACCORD Bone Study
Bibliographic record
Abstract
CONTEXT: In trials, thiazolidinediones (TZDs) increase fracture risk in women, but the effects of discontinuation are unknown. OBJECTIVE: The objective was to investigate the effects of TZD use and discontinuation on fractures in women and men. DESIGN: This was a longitudinal observational cohort study using data from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial bone ancillary study. Duration of TZD use and discontinuation during ACCORD, assessed every 2-4 months at clinic visits, were modeled as time-varying covariates in proportional hazards models for occurrence of first non-spine fracture. PARTICIPANTS: We studied a total of 6865 participants in ACCORD BONE. MAIN OUTCOME MEASURES: Main outcome measures were centrally adjudicated non-spine fracture. RESULTS: Average age was 62.4 (SD, 6.6) years; average duration of diabetes was 11.1 (SD, 7.8) years. Rosiglitazone was used by 74% and pioglitazone by 13% of participants. During a mean follow-up of 4.8 (SD, 1.5) years, 262 men and 287 women experienced at least one non-spine fracture. The fracture rate was higher in women with 1-2 years of TZD use (hazard ratio [HR] = 2.32; 95% confidence interval [CI], 1.49, 3.62) or >2 years of TZD use (HR = 2.01; 95% CI, 1.35, 2.98), compared with no use. The fracture rate was reduced in women who had discontinued TZD use for 1-2 years (HR = 0.57; 95% CI, 0.35, 0.92) or > 2 years (HR = 0.42; 95% CI, 0.24, 0.74) compared with current users. TZD use and discontinuation were not associated with non-spine fractures in men. CONCLUSIONS: TZD use was associated with increased non-spine fractures in women, but not men, with type 2 diabetes. When women discontinued TZD use, the fracture effects were attenuated.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".