Clinical and Histopathological Findings in HIV-positive to HIV-positive Kidney Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: The spectrum of histological findings in transplanted kidneys from HIV-positive donors to HIV-positive recipients is relatively unexplored. This study describes the type and timing of histological diagnoses observed in this unique cohort. METHODS: Adequate biopsies were analyzed at implantation and posttransplant between September 2008 and May 2022. Histological disease spectrum, distributions over time, and relevant clinical characteristics and management were reported for both for-cause and protocol biopsies. RESULTS: Twenty-four implantation biopsies from 31 deceased donors and 179 allograft biopsies (100 for-cause, 79 protocol) from 50 recipients were analyzed. Most rejection episodes occurred in the first year posttransplant. Eighteen recipients (36%) had at least 1 episode of biopsy-confirmed acute/chronic T cell-mediated rejection (TCMR) or active antibody-mediated rejection (AMR). Protocol biopsies showed no active AMR or acute/chronic TCMR. However, 9 of 79 biopsies identified borderline/suspicious TCMR. Common nonrejection diagnoses were interstitial fibrosis and tubular atrophy, ascending pyelonephritis, and calcineurin inhibitor toxicity. Classic and suspected HIV-associated nephropathy (HIVAN) were identified in 3 and 6 patients, respectively. Protocol biopsies diagnosed 1 case of classic HIVAN and 6 cases of suspected HIVAN. AMR most adversely affected kidney function and significantly contributed to graft failure. CONCLUSIONS: The histological findings in this cohort of HIV-positive kidney transplant recipients who received grafts from unmatched HIV-positive donors revealed a spectrum of abnormalities. Protocol biopsies added to surveillance on borderline rejection and assisted in the recognition of HIVAN. Confirmed rejection occurred in 18 recipients (36%). Understanding the factors contributing to this may assist in the optimization of immunosuppressive protocols in the future.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".