Physiologic volume of phosphorus during hemodialysis: Predictions from a pseudo one‐compartment model
Bibliographic record
Abstract
The kinetics of plasma phosphorus concentrations during hemodialysis (HD) are complex and cannot be described by conventional one- or two-compartment kinetic models. It has recently been shown by others that the physiologic (or apparent distribution) volume for phosphorus (Vr-P) increases with increasing treatment time and shows a large variation among patients treated by thrice weekly and daily HD. Here, we describe the dependence of Vr-P on treatment time and predialysis plasma phosphorus concentration as predicted by a novel pseudo one-compartment model. The kinetics of plasma phosphorus during conventional and six times per week daily HD were simulated as a function of treatment time per session for various dialyzer phosphate clearances and patient-specific phosphorus mobilization clearances (K(M)). Vr-P normalized to extracellular volume from these simulations were reported and compared with previously published empirical findings. Simulated results were relatively independent of dialyzer phosphate clearance and treatment frequency. In contrast, Vr-P was strongly dependent on treatment time per session; the increase in Vr-P with treatment time was larger for higher values of K(M). Vr-P was inversely dependent on predialysis plasma phosphorus concentration. There was significant variation among predicted Vr-P values, depending largely on the value of K(M). We conclude that a pseudo one-compartment model can describe the empirical dependence of the physiologic volume of phosphorus on treatment time and predialysis plasma phosphorus concentration. Further, the variation in physiologic volume of phosphorus among HD patients is largely due to differences in patient-specific phosphorus mobilization clearance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".