Short-term effects of hemodiafiltration versus conventional hemodialysis on erythrocyte performance
Bibliographic record
Abstract
Hemodiafiltration (HDF) is a renal replacement therapy that is based on the principles of diffusion and convection for the elimination of uremic toxins. A significant and increasing number of end-stage renal disease (ESRD) patients are treated with HDF, even in the absence of definite and conclusive survival and anemia treatment data. However, its effects on red blood cell (RBC) physiological features have not been examined in depth. In this study, ESRD patients under regular HDF or conventional hemodialysis (cHD) treatment were examined for RBC-related parameters, including anemia, hemolysis, cell shape, redox status, removal signaling, membrane protein composition, and microvesiculation, in repeated paired measurements accomplished before and right after each dialysis session. The HDF group was characterized by better redox potential and suppressed exovesiculation of blood cells compared with the cHD group pre-dialysis. However, HDF was associated with a temporary but acute, oxidative-stress-driven increase in hemolysis, RBC removal signaling, and stomatocytosis, probably associated with the effective clearance of dialyzable natural antioxidant components, including uric acid, from the uremic plasma. The nature of these adverse short-term effects of HDF on post-dialysis plasma and RBCs strongly suggests the use of a parallel antioxidant therapy during the HDF session.
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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 | 0.000 | 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 | 0.000 | 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".