Three‐month course of intragraft transcriptional changes in kidney allografts with early histological minimal injury – a cohort study
Bibliographic record
Abstract
The tubulitis with/without interstitial inflammation not meeting criteria for T-cell-mediated rejection (minimal allograft injury) is the most frequent histological findings in early transplant biopsies. The course of transcriptional changes in sequential kidney graft biopsies has not been studied yet. Molecular phenotypes were analyzed using the Molecular Microscope® Diagnostic System (MMDx) in 46 indication biopsies (median 13 postoperative days) diagnosed as minimal allograft injury and in corresponding follow-up biopsies at 3 months. All 46 patients with minimal injury in early biopsy received steroid pulses. MMDx interpreted indication biopsies as no-rejection in 34/46 (74%), T-cell-mediated rejection (TCMR) in 4/46 (9%), antibody-mediated rejection in 6/46 (13%), and mixed rejection in 2/46 (4%) cases. Follow-up biopsies were interpreted by MMDx in 37/46 (80%) cases as no-rejection, in 4/46 (9%) as TCMR, and in 5/46 (11%) as mixed rejection. Follow-up biopsies showed a decrease in MMDx-assessed acute kidney injury (P = 0.001) and an increase of atrophy–fibrosis (P = 0.002). The most significant predictor of MMDx rejection scores in follow-up biopsies was the tubulitis classifier score in initial biopsies (AUC = 0.84, P = 0.002), confirmed in multivariate binary regression (OR = 16, P = 0.016). Molecular tubulitis score at initial biopsy has the potential to discriminate patients at risk for molecular rejection score at follow-up biopsy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".