Dual-Kidney Transplants as an Alternative for Very Marginal Donors: Long-Term Follow-Up in 63 Patients
Bibliographic record
Abstract
BACKGROUND: Organ shortage has led to the use of dual-kidney transplant (DKT) of very marginal donors into a single recipient to increase the use of marginal organs. To date, few data are available about the long-term outcome of DKT and its usefulness to increase the pool of available organ. METHODS: We conducted a single-center cohort study of DKTs with longitudinal follow-up over an 8-year period. Between 1999 and 2007, 63 DKTs were performed. All kidneys from donors younger than 75 years refused by all centers for single transplantation, and kidneys from donors aged 75 years or older were routinely evaluated based on preimplantation glomerulosclerosis. Renal function, patient or graft survival, and perioperative complications were compared with 66 single kidneys from expanded criteria donors (ECD) and 63 ideal kidney donors. RESULTS: After a median follow-up of 56 months, patient or graft survival was similar between the three groups. Twelve-, 36-, and 84-month creatinine clearance were similar for DKT and ECD (12 months: 58 and 59 mL/min; 36 months: 54 and 60 mL/min; and 84 months: 62 and 51 mL/min, respectively). For the study period, the routine evaluation of very marginal kidneys for DKT in our center has led to an increase of 47% in the transplants from donors aged 50 years or older, which represent 12% at the level of our organ procurement organization. CONCLUSIONS: DKT patients can expect long-term results comparable with single kidney ECD. The implementation of a DKT program in our unit safely increased the pool of organs from marginal donors.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".