Renal transplant outcomes in patients with autosomal dominant tubulointerstitial kidney disease
Bibliographic record
Abstract
INTRODUCTION: Autosomal dominant tubulointerstitial kidney disease (ADTKD) is a rare genetic cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD). We aimed to compare renal transplant outcomes in people with ESRD due to ADTKD to those with other causes of renal failure. METHODS: Patients with clinical characteristics consistent with ADTKD by the criteria outlined in the 2015 KDIGO consensus were included. We compared ADTKD transplant outcomes with those of 4633 non-ADTKD renal transplant recipients. RESULTS: We included 31 patients who met diagnostic criteria for ADTKD in this analysis, 23 of whom had an identified mutation (28 were categorized as definite-ADTKD and 3 as suspected ADTKD). Five patients received a second transplant during follow-up. In total, 36 grafts were included. We did not identify significant differences between groups in terms of graft or patient survival after transplantation. Twenty-five transplant biopsies were performed during follow-up, and none of these showed signs of recurrent ADTKD post-transplant. CONCLUSION: In patients with ESRD due to ADTKD, we demonstrate that transplant outcomes are comparable with the general transplant population. There is no evidence that ADTKD can recur after transplantation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".