The Outcome of Tapered Steroid Regimen When Used to Treat Acute Borderline Cellular Rejection After Kidney Transplant: A Single-Center Experience
Bibliographic record
Abstract
Background: Treatment of acute borderline cellular rejection (BCR) after kidney transplant has shown mixed results with no consensus on the necessity and modality of interventions. Methods: The emphasis of our study was to assess the histopathologic response when BCR of kidney transplant is being treated with rapid steroid regimen. We analyzed all diagnosed acute BCR between 2018 and 2020. Patients were divided to a treatment responder group (RG) and non-responder group (NRG). All diagnosed BCR were treated with rapid steroid regimen and followed by a biopsy to assess response. Demographic data, recipients' comorbidities and clinical data, donor type, and induction immunosuppression regimen data were collected. Results: Ninety-one patients had acute BCR and were treated with rapid steroid followed by a repeat biopsy. Sixty-three (69%) patients showed persistence BCR and were considered NRG. Age, gender, and race were similar between the two groups. Class I and II calculated panel reactive antibodies were similar between the groups. No significant difference in the median serum creatinine (SCr) was noted between the groups. RG and NRG had a median SCr of 1.6 mg/dL (1.2 - 2.1) and 1.5 mg/dL (1.4 - 2.0), respectively (P < 0.79). The median SCr at the time of the follow-up biopsy was not different between the groups: SCr of 1.6 mg/dL (1.2 - 2.0) vs. 1.4 mg/dL (1.2 - 2.2) for the RG and NRG, respectively (P < 0.93). Conclusion: When rapid steroid regimen was used to treat acute BCR after kidney transplant, only smaller number of patients showed response based on the histology evaluation of the follow-up post-treatment biopsies.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".