Metformin use and risk of total joint replacement in patients with diabetes: a longitudinal cohort study of Alberta’s Tomorrow Project
Bibliographic record
Abstract
PURPOSE: To characterize the association between metformin use and risk of total joint replacement in patients with diabetes using data from Alberta's Tomorrow Project (ATP), a population-based cohort study of chronic diseases in Alberta, Canada. METHODS: The ATP participants with incidence of diabetes after enrollment were included and followed up to March 31, 2021. Metformin use, including daily doses, was measured by a time-varying approach during the follow-up. A multivariable Cox regression model was used to characterize the association between metformin use and risk of total joint replacement, after controlling for time-related variation in drug use, clinical status, BMI, lifestyles and concurrent medications. RESULTS: Among 3,001 incident cases of diabetes (52% females, age at diagnosis 61.3 ± 9.5 years, average follow-up of 7.3 ± 4.7 years), the rate of total joint replacement was 7.57 per 1,000 person-year (PY) for metformin users and 9.31 per 1,000 PY for non-metformin users, with rate ratio = 0.81 (95% CI = 0.59-1.11, p-value = 0.09). In multivariable Cox regression analysis, metformin use was not significantly associated with risk of total joint replacement, with hazard ratio of 0.74 (95% CI = 0.52-1.03, p-value = 0.07) for patients with metformin medication, HR = 0.75 (95% CI = 0.46-1.22) for 0-1.0 g/day metformin use, and HR = 0.73 (95% CI = 0.49-1.08) for 1.0 + g/day use ('no metformin use' as the reference group). CONCLUSIONS: Although our findings are not statistically significant, our study suggests clinically a potential benefit of metformin use in reducing risk of total joint replacement in patients with diabetes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".