Abstract 15777: Induction Immunosuppression is Associated With a Lower Incidence of Post-transplant Diabetes Mellitus in Heart Transplant Recipients: A Propensity-adjusted Analysis
Bibliographic record
Abstract
Introduction: Post-transplant diabetes mellitus (PTDM) is a common complication among heart transplant recipients resulting in heightened risk of diabetes-related complications and death. While there is evidence that certain maintenance immunosuppression drugs like tacrolimus increase the risk of PTDM, it is not known whether induction immunosuppression does the same. We therefore evaluated whether induction immunosuppression in the early post-transplant period with IL-2 inhibitors, alemtuzumab or anti-thymocyte globulin is associated with PTDM after accounting for potential confounding by indication. Methods: Using data from the Scientific Registry of Transplant Recipients, we conducted a cohort study of 23,946 US adults who received a heart transplant in January 2008-December 2018. PTDM was defined as new diagnosis of diabetes at any time 6 months after transplant. We excluded patients with prior organ transplants and diabetes. We used logistic regression to construct propensity scores for predictors of induction immunosuppression and risk factors for PTDM including demographic, clinical and immunologic factors, pre-transplant therapies, steroids, functional status, and transplant year. We estimated the effect of induction immunosuppression in propensity-adjusted Cox proportional hazards models and produced fully adjusted Kaplan-Meier curves using inverse probability of treatment weights. Results: The average age was 54 (SD=12.5) years, 26% were female and 12,303 (51%) received induction immunosuppression. Over 84,969 person-years, 2,678 (11%) developed PTDM (32 cases/1,000 person-years). In the propensity-adjusted analysis, induction immunosuppression was associated with a 20% lower rate of PTDM (Figure 1; hazard ratio=0.80, 95% confidence interval 0.74-0.87). Conclusions: Adult heart transplant recipients who received induction immunosuppression had a 20% lower rate of PTDM compared to those who did not receive it.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".