Adequacy of Daily Hemofiltration (HF): Clinical Evaluation of Standard Kt/V
Bibliographic record
Abstract
Standard Kt/V (stdKt/V) has been proposed as a dose measure for daily therapies (adequate therapy defined as stdKt/V ≥ 2.0), but this parameter is difficult to evaluate without determining equilibrated Kt/V (eKt/V). We determined eKt/V in 34 urea kinetic modeling (UKM) sessions from 13 patients undergoing daily HF (6 times/wk) in 2 different centers with a single-pool Kt/V (spKt/V) goal of 0.40. The patient characteristics were as follows: age 55 ± 19 (SD) years; 9 males; 3 diabetics; and dry weight 71.1 ± 14.4 kg. Urea concentration was measured pre-HF, and 0 and 60 min post-HF. spKt/V and eKt/V were calculated using the 0- and 60-min post-HF urea concentrations, respectively, and eKt/V was corrected for urea generation post-HF. eKt/V was also predicted from spKt/V using the Daugirdas-Schneditz (DS) rate equation. stdKt/V was calculated using the Gotch fixed-volume kinetic model equation. Results: Treatment and UKM parameters Mean ± SD Treatment time, hour 2.32 ± 0.68 Blood flow rate, ml/min 485 ± 23 Replacement fluid volume, L 12.7 ± 2.1 Net volume removed, L 1.1 ± 0.8 Measured spKt/V 0.441 ± 0.041 Measured eKt/V 0.388 ± 0.063* Predicted eKt/V 0.350 ± 0.047 stdKt/V, per week 1.95 ± 0.26 Measured eKt/V was greater than that predicted (*p < 0.001). We conclude that 1) the DS rate equation cannot be used to accurately predict eKt/V during daily HF and 2) daily HF with an exchange (replacement plus removed) volume of 20% of body weight (13.8 L/71.1 kg = 19.4%) delivers a weekly stdKt/V of ∼ 2.0.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".