P.248: Characteristics and outcomes of living donor kidney transplant recipients at King Faisal Hospital Rwanda.
Bibliographic record
Abstract
Introduction: Establishing a living donor kidney transplant program in a limited resource setting while upholding internationally accepted ethical and regulatory requirements and aiming for outstanding outcomes is a challenging task. To reduce medical referrals abroad and make surgical care more accessible to patients from Rwanda and the region, King Faisal Hospital Rwanda (KFH) established the country’s first living donor kidney transplant program, which launched in May 2023. We describe the socio-demographic features and initial outcomes of living donor kidney transplant recipients in our new program. Methods: A retrospective analysis was conducted across kidney transplant recipients, including their demographics, clinical characteristics, and initial surgical and clinical outcomes. The surgical techniques and kidney transplant evaluation, management, and follow-up are similar to those used at reputable transplant hospitals worldwide. Results: Twenty living donor kidney transplants were performed over nine months, from May 2023 through January 2024. The mean age of the recipients was 44.8 years, with 45% of the recipients being between 46 and 60 years, and 75% being male. Seventeen transplants were performed between related donors (parents and siblings), and only three donations were from unrelated donors. The primary diagnoses of kidney failure were diabetic nephropathy (35%), hypertension (35%), and chronic glomerulonephritis (25%). There was one allograft biopsy-proven cellular mediated rejection. Two recipients developed lymphocele during the first three postoperative months. Among the twenty recipients, new onset diabetes occurred in two recipients post-transplantation. Only one recipient required hospital readmission post-transplant because of ureteric stenosis. The mean serum creatinine at 1 month, 3 months, 6 months, and 9 months was 118.3, 94.3, 86.4, and 91.8 micromol/L respectively. Conclusion: Rwanda’s living donor transplant program emphasizes sustainable and equitable access to care. Furthermore, ongoing transplant surgical and medical education emphasizes in-country training within Rwanda with support through academic partnerships. Program structure, protocols, and results are comparable to those achieved in Europe and North America. To come to a more accurate conclusion, further studies with a comparatively larger cohort and a longer follow-up period will be needed.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".