Do Biochemical Measures Change in Living Kidney Donors?
Bibliographic record
Abstract
BACKGROUND: Living kidney donation provides a unique opportunity to assess possible biochemical changes attributable to small decrements in glomerular filtration rate. We reviewed studies which followed 5 or more healthy donors, where changes in biochemical measures or anemia were assessed at least 4 months after nephrectomy. METHODS: We searched MEDLINE, EMBASE, and Science Citation databases, and reviewed reference lists from 1966 through June 2006. We abstracted data on study and donor characteristics and biochemical outcomes of interest. RESULTS: Eight studies examined at least one outcome of interest. The average time after donation ranged from 0.4 to 11 years, the postdonation creatinine clearance ranged from 73 to 99 ml/min, and the decrement after donation ranged from 11 to 38 ml/min. Nephrectomy did not change hemoglobin, erythropoietin, serum phosphate, calcium or C-reactive protein levels. The studies were inconsistent as to whether parathyroid hormone levels increased and 1,25-dihydroxyvitamin D levels decreased after nephrectomy. Uric acid levels increased variably post-donation. Plasma homocysteine increased in the single study included in this review. CONCLUSIONS: The mechanistic changes described above and their prognostic significance need clarification. Based on existing evidence, it is not necessary to routinely monitor living kidney donors for changes in these biochemical 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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".