Can zero-hour cortical biopsy predict early graft outcomes after living donor renal transplantation?
Bibliographic record
Abstract
INTRODUCTION: The aim of this study was to identify relevance of subclinical pathological findings in the kidneys of living donors and correlate these with early graft renal function. METHODS: This was a prospective study on 84 living donor kidney transplant recipients over a period of two years. In all the donors, cortical wedge biopsy was taken and sent for assessment of glomerular, mesangial, and tubule status. The graft function of patients with normal histology was compared with those of abnormal histological findings at one, three, and six months, and one year post-surgery. RESULTS: Most abnormal histological findings were of mild degree. Glomerulosclerosis (GS, 25%), interstitial fibrosis (IF, 13%), acute tubular necrosis (ATN 5%), and focal tubal atrophy (FTA, 5%) were the commonly observed pathological findings in zero-hour biopsies. Only those donors who had histological changes of IF and ATN showed progressive deterioration of renal function at one month, three months, six months, and one year post-transplantation. In donors with other histological changes, no significant effect on graft function was observed. CONCLUSIONS: Zero-hour cortical biopsy gave us an idea of the general status of the donor kidney and presence or absence of subclinical pathological lesions. A mild degree of subclinical and pathological findings on zero-hour biopsy did not affect early graft renal function in living donor kidney transplantation. Zero-hour cortical biopsy could also help in discriminating donor-derived lesions from de novo alterations in the kidney that could happen subsequently.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".