Phosphorus dynamics during hemodialysis
Bibliographic record
Abstract
We studied phosphorus (P) dynamics and its relation to urea dynamics in a wide range of dialyses by measuring predialysis and postdialysis serum P levels and all removed P and urea in dialysate during 455 hemodialyses. Dialyses were performed at different frequencies (range 3-6 treatments/wk); duration of dialysis (t) (range 80-560 minutes), varied blood and dialysate flow, and with high-flux and low-flux membranes. Kt/V-P, Kt/V-urea, weekly removal of P-and urea and removal volumes (Vr) and their relationships to varying dialyses, and predialysis concentrations, and protein catabolic rates were studied in linear and multiple regression analyses. A weekly dialysis time of > 30 hours was needed to maintain serum P concentration normal without the use of phosphate binders. Vr-P as a percentage of body weight was dependent on predialysis serum P and increased steeply as predialysis serum P decreased and dialysis time was prolonged. There was no relationship between Vr-urea and Vr-P. Phosphorus removal per week was mainly dependent on weekly frequency, and time on dialysis and > 38 h/wk were necessary to remove the recommended P intake. Phosphorus shows highly variable dynamics during dialysis. The body maintains extracellular P concentration by releasing P from large compartments when the dialysis time is prolonged and the serum concentration of P decreases during dialysis. Vr-P shows huge variation between patients and in an individual patient, depending on predialysis serum P. Kt/V is inaccurate in describing P removal. To remove P efficiently, it is most important to perform long and more frequent hemodialysis.
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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 | 0.001 |
| 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) | 0.002 | 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".