Clearance of small molecules in different dialyzer flow configurations
Bibliographic record
Abstract
To overcome problems of insufficient clearance, multiple dialyzers may be placed in series or in parallel. The present study aimed to investigate in vitro the overall clearance of small molecules in different dialyzer configurations in which mutual flow directions were changed. Single pass tests were performed with low flux Fresenius F6HPS dialyzers placed in series (12 tests), in parallel (6) and in single use (2). As blood substitute, either high concentrated (45 mS) bicarbonate dialysate (AB solution – MW20‐180) or a trisodiumphosphate (Na3PO4– MW395) concentration (30 mS) was used. Standard blood and dialysate flows of 250 and 500 mL/min, respectively, were applied. Furthermore, clearance was derived from conductivity measurements in the inlet and outlet bloodline, correcting for the overall ultrafiltration rate of 0.5 L/h (AB) and 0.1 L/h (Na3PO4). Compared to the standard setup using a single dialyzer with counter current flows, clearance increases by 3 to 8%(AB) and by 15 to 18%(Na3PO4) using two dialyzers in parallel and in series, respectively. With co‐current flows in a serial dialyzer set up, clearance increases by 16%(AB) and 22%(Na3PO4) compared to the single dialyzer use. Changing subsequently the counter current flows to co‐current in one and both dialyzers in series, the overall clearance decreases by 2 to 9%, respectively, for the AB solution, and by 8 to 15% for the Na3PO4 concentration. With respect to the parallel dialyzer setup, a split dialysate flow (250 mL/min in each dialyzer) counter current to the blood flow, increases the clearance by 4 and 12%, respectively. In conclusion, overall clearance is most ameliorated using two dialyzers in series with counter current flows.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".