Metformin use in the first year after kidney transplant, correlates, and associated outcomes in diabetic transplant recipients: A retrospective analysis of integrated registry and pharmacy claims data
Bibliographic record
Abstract
Abstract While guidelines support metformin as a therapeutic option for diabetic patients with mild‐to‐moderate renal insufficiency, the frequency and outcomes of metformin use in kidney transplant recipients are not well described. We integrated national U.S. transplant registry data with records from a large pharmaceutical claims clearinghouse (2008‐2015). Associations (adjusted hazard ratio, 95% LCL aHR 95% UCL ) of diabetes regimens (with and excluding metformin) in the first year post‐transplant with patient and graft survival over the subsequent year were quantified by multivariate Cox regression, adjusted for recipient, donor, and transplant factors and propensity for metformin use. Among 14 144 recipients with pretransplant type 2 diabetes mellitus, 4.7% filled metformin in the first year post‐transplant; most also received diabetes comedications. Compared to those who received insulin‐based regimens without metformin, patients who received metformin were more likely to be female, have higher estimated glomerular filtration rates, and have undergone transplant more recently. Metformin‐based regimens were associated with significantly lower adjusted all‐cause ( aHR 0.18 0.41 0.91 ), malignancy‐related ( aHR 0.45 0.45 0.99 ), and infection‐related ( aHR 0.12 0.32 0.85 ) mortality, and nonsignificant trends toward lower cardiovascular mortality, graft failure, and acute rejection. No evidence of increased adverse graft or patient outcomes was noted. Use of metformin‐based diabetes treatment regimens may be safe in carefully selected kidney transplant recipients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".