Serum cystatin C performs similarly to traditional markers of kidney function in the evaluation of donor kidney function prior to and following unilateral nephrectomy
Bibliographic record
Abstract
UNLABELLED: Background and objectives. It is essential that candidates for kidney donation be carefully screened to ensure safety of donation and monitored following unilateral nephrectomy as previous experience has demonstrated loss of kidney function of up to 50% following donation. The low-molecular-weight protein cystatin C (cysC) has been introduced as an alternative to serum creatinine for estimation of glomerular filtration rate (GFR). In particular, serum cysC is sensitive to detect mild GFR reduction between 60 and 90 ml/min/1.73 m(2) that would make it a potentially effective screening and monitoring test in live kidney donors. Design, setting, participants and measurements. We examined the utility of cysC as compared to other traditional measures of kidney function, including serum creatinine and 24-h urine for creatinine clearance, in the evaluation of kidney function in 51 consecutive live kidney donors both prior to and following unilateral nephrectomy. RESULTS: This is the largest experience reported in the living kidney donor population. We found that living kidney donors at our centre lost approximately 30-35% of kidney function following unilateral nephrectomy and this remained stable >1 year. Furthermore, we observed that cysC correlated well with all other markers of kidney function and detected acute changes in kidney function immediately post-nephrectomy. CONCLUSIONS: Overall, however, cysC did not confer any advantage with respect to preoperative assessment of kidney function or for monitoring following live kidney donation as compared to more traditional measures.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".