Acute Tubular Injury in Protocol Biopsies of Renal Grafts: Prevalence, Associated Factors and Effect on Long-Term Function
Bibliographic record
Abstract
Acute tubular injury (ATI) is commonly observed in renal allografts, especially early after transplantation. This study analyzes prevalence and associated clinical conditions of ATI in serial protocol biopsies (pBx) and indication biopsies (iBx), and its impact on long-term graft function. 612 pBx from 204 patients taken at 6 weeks, 3 and 6 months, and 151 iBx performed within the first year of transplantation were evaluated. Prevalence of ATI in pBx was 40% (6 weeks), 34% (3 months) and 37% (6 months), and 46% in iBx. ATI was associated with delayed graft function and prolonged cold ischemia time in pBx, and with acute rejections in iBx. The GFR at 1 and 2 years after transplantation correlated inversely with the frequency of ATI in both pBx and iBx (p < 0.001). Prevalence of chronic changes at 6 months was not significantly related to ATI (patients without ATI: 36%, patients with multiple ATI findings: 54%). ATI is linked to inferior long-term graft function. While this suggests lack of recovery from ATI with permanent allograft damage, the underlying molecular mechanisms need yet to be uncovered. Prevention of the potential pathogenetic factors identified in this study might be the key point to attain good long-term graft function.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".