GFR Assessment of Living Kidney Donors Candidates
Bibliographic record
Abstract
Living kidney donation provides the best outcomes (survival, cost, and quality of life) of all renal replacement modalities. Living kidney donors, on the other hand, are at the increased risk of end-stage kidney disease (ESKD) after donation compared with healthy nondonors for multiple possible reasons. Extensive predonation screening is required to assess eligibility for donation to avoid the rejection of suitable candidates and minimize acceptance of donors with increased risk of ESKD. The association between the lower predonation glomerular filtration rate (GFR) and increased ESKD risk in donors highlights the relevance of GFR assessment for living kidney donor candidates. However, the method to evaluate GFR is still debated, and the thresholds of acceptable predonation GFR vary across guidelines. All guidelines favor GFR measurement with an exogenous tracer over estimated GFR, but only the British Transplant Society guidelines mandates it. While the Kidney Disease Improving Global Outcomes Group guidelines advocates for age-independent GFR thresholds, most other guidelines propose various age-dependent GFR thresholds with resulting profound differences in assessment of donor suitability between guidelines. Many important questions are not addressed by any guidelines, including the approach to discordant GFR measurement and estimated GFR results, the use of method-specific GFR thresholds and thresholds dependent on comorbidities or race. Further data are required exploring the associations between these variables and the course of postdonation GFR. Last, GFR evaluation studies conducted in approved donors and not in those initially presenting as potential candidates are questionable regarding their suitability for potential donor evaluation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".