Efficacy of Acute Cellular Rejection Treatment According to Banff Score in Kidney Transplant Recipients: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The poor prognosis classically associated with Banff grade 2 acute cell-mediated rejection (CMR) may be due to unrecognized antibody-mediated damage. We thus performed a systematic review of the literature to determine the rate of response to treatment in kidney transplant recipients with pure CMR, stratified by Banff class. METHODS: In addition to a manual search, databases interrogated included Excerpta Medica Database (EMBASE), Medical Literature Analysis and Retrieval System Online (MEDLINE), Evidence-Based Medicine (EBM) databases, Central, PubMed and CINAHL. Studies providing functional and/or histological response rates to the treatment of CMR rejection by Banff class (1997 or more recent) were included. RESULTS: Among the 746 articles identified, 5 articles were included in the final review. Two studies excluded some, and 2 excluded all features of antibody-mediated rejection, while providing data on functional recovery. The absence of functional recovery was reported in 4% of borderline, 15% for Banff grade 1A and IB pooled, 0% to 25% of Banff grade 1B alone, 11% to 20% of Banff grade 2A, and 38% of Banff grade 2B rejections. CONCLUSIONS: The rate of functional recovery of pure Banff IIA CMR overlapped with that of Banff grade 1 CMR, whereas Banff grade 2B showed worse prognosis. There was important heterogeneity in the definition of response to treatment and paucity of data describing the histological response to treatment stratified by Banff class. There is a pressing need to standardize outcome metrics for the reversibility of rejection in kidney transplant recipients in order to design high-quality trials for novel therapeutic alternatives.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".