Accuracy to Estimate Rates of Decline in Glomerular Filtration Rate in Renal Transplant Patients
Bibliographic record
Abstract
BACKGROUND: We examined the use of the Cockroft Gault (C-G) test, Modified Diet in Renal Disease 2 (MDRD2) test, and inverse serum creatinine (Delta1/Scr) to estimate rates of decline in renal transplant function using isotope glomerular filtration rate (GFR) as a reference test. METHODS: Percent changes in estimated GFR (DeltaeGFR) were compared to simultaneous changes in isotope GFR (DeltaiGFR) in 72 patients. RESULTS: The number of iGFR was 508 with a mean of 7.15+/-3.15 scans per patient. There was a decline in iGFR of 16.14+/-21.37 ml/min over the study duration of 88.9+/-57.6 months. DeltaeGFR and Delta1/Scr correlated significantly with DeltaiGFR. Accuracy to predict DeltaiGFR from the eGFRs was limited to <65% concordance within 30% range from changes in iGFR. Slope analyses showed a significantly lower percent annual loss in mean iGFR of 6.03% than that of the C-G of 8.62% and MDRD2 of 8.96% (P<0.001). The within patient variability measured from the standard deviation (ml/min) of root mean square of 4.69 for iGFR was significantly higher than that for C-G and MDRD2 of 2.46 and 2.94, respectively. iGFR and eGFR at first observation correlated significantly (P<0.001) with last observation. CONCLUSIONS: iGFR is significantly more variable within patient than the other predictors, and the two estimators predict the iGFR with a high sensitivity but low specificity. This is a clinically reasonable combination. Predicted percent of annual loss in iGFR appears to be smaller than that using the two estimators.
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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) | 0.000 | 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 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".