Impact of immunosuppression on incidence of post-transplant diabetes mellitus in solid organ transplant recipients: Systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Solid organ transplantation is a life-saving intervention for end-stage organ disease. Post-transplant diabetes mellitus (PTDM) is a common complication in solid organ transplant recipients, and significantly compromises long-term survival beyond a year. AIM: To perform a systematic review and meta-analysis to estimate incidence of PTDM and compare the effects of the 3 major immunosuppressants on incidence of PTDM. METHODS: Two hundred and six eligible studies identified 75595 patients on Tacrolimus, 51242 on Cyclosporine and 3020 on Sirolimus. Random effects meta-analyses was used to calculate incidence. RESULTS: Network meta-analysis estimated the overall risk of developing PTDM was higher with tacrolimus (OR = 1.4 95%CI: 1.0-2.0) and sirolimus (OR = 1.8; 95%CI: 1.5-2.2) than with Cyclosporine. The overall incidence of PTDM at years 2-3 was 17% for kidney, 19% for liver and 22% for heart. The risk factors for PTDM most frequently identified in the primary studies were age, body mass index, hepatitis C, and African American descent. CONCLUSION: Tacrolimus tends to exhibit higher diabetogenicity in the short-term (2-3 years post-transplant), whereas sirolimus exhibits higher diabetogenicity in the long-term (5-10 years post-transplant). This study will aid clinicians in recognition of risk factors for PTDM and encourage careful evaluation of the risk/benefit of different immunosuppressant regimens in transplant recipients.
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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) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 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 it