Validation of the Virga GFR Equation in a Renal Transplant Population
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Bibliographic record
Abstract
BACKGROUND: Virga and colleagues derived a glomerular filtration rate (GFR) equation which demonstrated a superior performance over Cockcroft-Gault (C-G) and modified diet in renal disease-isotope dilution mass spectrometry (MDRD-IDMS) formulas in chronic kidney disease (CKD) patients. AIM: To validate the performance of the Virga equation on 103 renal transplant patients. METHODS: We compared the performances of the MDRD-IDMS, C-G and Virga equations using inulin clearance as a reference test. Error, accuracy, relative accuracy, precision, scatter, and coefficient of variance of each equation were tested. RESULTS: The mean absolute percentage error in estimated GFR by the new equation was 39.8 +/- 36.34% (mean +/- SD). Relative accuracy at 10, 30 and 50% range were 18.44, 48.54 and 73.78%, respectively. It has a bias of 0.09 +/- 0.169 and a precision of 19.69. Inulin clearance (GFR) in stages 1-4 were 106.19 +/- 14.11, 71.17 +/- 7, 42.37 +/- 8.40 and 22.92 +/- 3.48 ml/min/1.73 m(2), respectively. Comparative statistics in the overall population and in patients with transplant CKD stage 3T showed that the MDRD-IDMS equation had better accuracy. The performance of MDRD-IDMS over the Virga equation was clearly superior for males. In patients with CKD stage 2T, the Virga equation showed superiority over MDRD-IDMS. In the overall and subpopulations, the Virga equation performed better than the C-G equation. CONCLUSION: Among renal transplant patients, the results suggest that the best GFR estimate is probably obtained using the MDRD-IDMS equation in moderate kidney failure whilst the Virga formula was superior to MDRD-IDMS for patients with mild kidney failure. As in untransplanted patients, estimating GFR with the MDRD-IDMS equation is not advisable in the range of normal renal function because of its known underestimation of renal function.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 it