An improved method for determining renal sufficiency using volume of distribution and weight from bolus 99mTc-DTPA, two blood sample, paediatric data
Bibliographic record
Abstract
OBJECTIVES: To find an improved method of determining renal sufficiency by exploring power functions for estimating normal value, E(arg), single compartment glomerular filtration rate (G1), rate constant (gamma) and renal sufficiency index, RSI = gamma/E(gamma) = G1/E(G1), using compartment volume (V), patient mass ( W), patient age (A), patient height (H), and sex (S). To present the best estimator of normal, E(G1) = f(V, W). METHODS: One hundred and thirty 99mTc-diethylenetriaminepentaacetic acid (99mTc-DTPA) combined imaging and G1 studies in 97 children were screened by findings and history to obtain 44 normal studies of patients 1.46-18.5 years of age with blood samples at 109 (90-214) and 152 (120-246) min. Normal studies were used to generate predictive formulae. RESULTS: For power functions, [equation: see text] the statistically acceptable formulae in descending order of adjusted R2 were f(V, W), f(V,A), f(V,H), f(V), f(W,A,H), f( W), f(H) and f(A). Relationships of the body surface area type, f(W, H, S) and f(W, H), were statistically unwarranted. Kleiber's law, E(G1) proportional to W(3/4), with E(G1) = 6.9190W(0.7618) found here, allowed confirmation of GFRinulin approximately 0.87G1. The best estimator is f(V, W) = 10.998V(0.64717 W(0.20185), and may relate to a volumetric measure of body habitus. To verify methods, Monte Carlo simulation of the glomerular filtration rate (GFR) and f(V, W) was performed and yielded less than 5% precision error, 98% of the time. Normal RSI from f(V, W) had the smallest standard deviation, 11.3%, no regression bias over a six-fold range on a Bland-Altman ratio plot, p = 0.4, and good agreement with clinical classification at 95% specificity (RSI > 0.8589, Cohen's Kappa 0.70+/-0.062 (mean+/-bootstrap standard error). CONCLUSIONS: The best RSI from f(V, W) is RSI = 90.927gammaV(0.35283)W(-0.20185) and should detect mildly (14.1%) reduced renal sufficiency.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".