The Association of Pre-Transplant C-Peptide Level with the Development of Post-Transplant Diabetes: A Cohort Study
Bibliographic record
Abstract
Key Points A pretransplant fasting C-peptide level ≥3000 pmol/L was associated with a nearly 20-fold increased odds of post-transplant diabetes mellitus at 1 year post kidney transplantation. In a restricted cohort with a body mass index between 20 and 35 kg/m 2 , a pretransplant C-peptide ≥3000 pmol/L was the only factor independently associated with post-transplant diabetes mellitus. Hemoglobin A1c at 1 year post kidney transplant was significantly higher (5.9% versus 5.5%, [ P =0.02]) in those with a high versus low pretransplant C-peptide levels. Background Post-transplant diabetes mellitus (PTDM) is an important complication after kidney transplantation that results in reduced patient and allograft survival. Although there are established risk factors for PTDM, whether pretransplant C-peptide levels associate with PTDM is unknown. Therefore, in this study, we aimed to examine the association of pretransplant C-peptide levels with PTDM. Methods This was a cohort study of nondiabetic adult patients who underwent kidney transplant in Nova Scotia, Canada, between January 1, 2016, and March 31, 2021, with fasting C-peptide levels measured before transplant. Multivariable logistic regression was used to determine the association of pretransplant C-peptide (dichotomized around the median) with PTDM at 1 year post transplant. Given the known association between pretransplant obesity and PTDM, we repeated our primary analysis in a cohort restricted to a BMI of 20–35 kg/m 2 . Results The median C-peptide value was 3251 (Q1 2480, Q3 4724); pretransplant C-peptide level was dichotomized at 3000 pmol/L. PTDM occurred in 25 (19%) individuals. Thirty percent of patients in the high and only 2% of patients in the low C-peptide groups developed PTDM ( P <0.001). A C-peptide level ≥3000 pmol/L was strongly associated with PTDM in multivariable analysis (OR=18.9, 95% CI, 2.06 to 174.2). In a restricted cohort with a BMI of 20–35 kg/m 2 , an elevated pretransplant C-peptide remained independently associated with the risk of PTDM (OR=15.7, 95% CI, 1.64 to 150.3). C-peptide was the only factor independently associated with PTDM in this restricted BMI cohort. Conclusions A pretransplant C-peptide level ≥3000 pmol/L was associated with a nearly 20-fold increased odds of PTDM at 1 year post kidney transplantation. Identifying patients with high pretransplant C-peptide levels may therefore help identify those at risk for PTDM who may benefit from focused preventative and therapeutic interventions and support.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".