Effect of hemodialysis and hemofiltration on plasma <scp>C.E.R.A</scp>. concentrations
Bibliographic record
Abstract
C.E.R.A., a continuous erythropoietin receptor activator, is a long-acting erythropoiesis-stimulating agent approved for the treatment of anemia in patients with chronic kidney disease. Although the large molecular weight and the carbohydrate chain make it unlikely that C.E.R.A. could be removed during hemodialysis or hemofiltration, no such data have been published. In vitro studies were performed to assess the removal of C.E.R.A. during hemodialysis and hemofiltration, using both low-flux and high-flux membranes and parameters very similar to those used in clinical practice. Clinical pharmacokinetic studies of plasma C.E.R.A. concentrations in patients undergoing hemodialysis were also performed following subcutaneous injection of C.E.R.A. In the in vitro studies, plasma C.E.R.A. concentrations were not significantly different from baseline values in the primed blood reservoir over a 4-hour period during hemodialysis (P = 0.12). C.E.R.A. concentrations in the plasma obtained from the venous end of the hemofilter increased proportionally with the plasma total protein concentrations, reflecting the consequence of hemoconcentration and suggesting that C.E.R.A and plasma total proteins were retained by hemofiltration membranes to a similar degree. These in vitro studies showed that C.E.R.A. was not removed by simulated hemodialysis or hemofiltration either via transmembrane transport or adsorption to the membrane. The results were corroborated by the clinical pharmacokinetic data, which showed no detectable changes in plasma C.E.R.A. concentrations during hemodialysis using either low-flux or high-flux dialyzers. These results suggest that C.E.R.A. can be administered to patients at any time during hemodialysis or hemofiltration without appreciable loss in the extracorporeal circuit.
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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".