Estimation of backfiltration flow rate in commercially available high flux dialyzers: Importance of water purification system for dialysate
Bibliographic record
Abstract
Several types of high flux dialyzers were developed and introduced for clinical applications to improve solute removal efficiency. In these dialyzers, internal filtration/backfiltration (IF/BF) is induced by pressure drop of blood and dialysate flow in a countercurrent manner under less net filtration. Higher IF/BF flow rate increased convective transport of the solute in addition to diffusive transport. In previously published papers, we reported the effects of IF on solute removal efficiency of the dialyzer during an analytical and an experimental study and the measurement of the internal filtration flow rate (QIF) by Doppler ultrasonography. Average blood flow rate (QBav) at a cross‐sectional plane was measured by pulse Doppler and the longitudinal QBav profile along the dialyzer was obtained using a probe slider that can move the probe in parallel along the dialyzer. This is a suitable method for a bedside monitoring of the IF/BF flow rate of dialyzers because it is noninvasive to the patient and produces reliable data with higher reproducibility. Internal backfiltration flow rate (QBF) in six types of commercially available high flux dialyzers, having a higher 50 ml/min of β2‐microglobulin clearance (CL‐β2 m), were examined by Doppler ultrasonography under 10 ml/min/m2 of net filtration flow rate. As a result, a wide range of QBF value, 12.1–28.4 ml/min, was obtained among those dialyzers. It means a fair amount of BF, 2.9–6.8 liter per session, occurs in a typical hemodialysis treatment. Strict management of dialysate purification is required for a dialyzer with a relatively larger BF. On the other hand, no correlation between the CL‐β2 m value and the QBF value was seen because the CL‐β2 m value depends on not only the IF/BF flow rate but also diffusive property of the membrane. The BF flow rate in every dialyzer should be examined to avoid suffering from the invasion of endotoxin and its fragment for safety.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".