Impact of flow and surface area on middle molecule clearance
Bibliographic record
Abstract
Urea is still clinically applied as standard marker to quantify dialysis adequacy. The removal of middle molecules has however been proven in some studies to have a long‐term effect on mortality. Therefore, the present study is aimed at investigating the impact of blood and dialysate flow, and membrane surface area on middle molecule removal in low flux Fresenius F6HPS dialyzers. Blood and dialysate flows were varied within the clinical range of 300–500 mL/min and 500–800 mL/min, respectively, while ultrafiltration rate was kept constant at 0.1 L/h. Single pass tests were performed in vitro in a single dialyzer (3 tests) and in serially (5 tests) and parallel (3 tests) connected dialyzers. The blood substitution fluid consisted of bicarbonate dialysate in which radioactive labeled vitamin B12 (MW1355) was dissolved. Middle molecule concentrations of samples taken at the inlet and outlet blood line were derived from radioactivity measurements and were applied to calculate the dialyzer clearance as well as the reduction ratio. For the latter, the surrogate middle molecule vitamin B12 was assumed as distributed according to a two‐pool kinetic model. Adding a second dialyzer in series or parallel ameliorates significantly overall dialyzer clearance and reduction ratio, except for the highest applied blood flow rate of 500 mL/min. Better solute removal is also obtained with higher dialysate flows, while the use of higher blood flows seemed only advantageous when using a single dialyzer. Analysis of the ultrafiltration profiles in the different configurations illustrated that enhancing the internal filtration rate ameliorates the convective transport of middle molecules. In conclusion, adequate solute removal results from a number of interactions, as there are, blood and dialysate flow rates, membrane surface area, filtration profile, and concentration profiles in the blood and dialysate compartment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".