Beta‐2‐Microglobulin in nocturnal hemodialysis – A comparative study in low and high flux dialysers
Bibliographic record
Abstract
In end‐stage renal failure, impaired renal catabolism leads to retention of beta 2 microglobulin (ß2M), identified as the major constituent of hemodialysis (HD) related amyloidosis. It has been previously shown that, while using a high flux (HF) HD membrane, nocturnal hemodialysis (NHD) with its increased time and frequency provides a much higher clearance of ß2M compared to conventional HD. We compared serum ß2M levels between low flux (LF) and HF in a group of 9 NHD patients who dialyse 8 hours 6 nights/week. Fresenius polysulfone LF membrane size F6‐F8 HPS dialyser were used for the first 15 months (mth) of NHD (SA 1.3–1.8 m2). Subsequently, polysulfone HF FX80 dialyzer were used (SA 1.8 m2). Blood flow and dialysate flow rates were unchanged throughout the study. ß2M levels were measured at 6, 12, 15 mth on LF and at 6, 12 mth on HF. Albumin, homocysteine (Hcy), and phosphate (Phos) levels were also recorded at these times. ß2M levels trended upwards during the 15 mth on LF (36.6 ± 10.57 at 6 mth vs 47.1 ± 11.7 at 15 mth). On introduction of HF, there was a significant fall in ß2M at 6 mth to 12.4 ± 3.5 (p < 0.003), while ß2M levels were unchanged at 12 mth of HF. A downward trend in Hcy levels with the use of HF was noted (12.9 ± 2.9 at 0 mth Vs 11.1 ± 3.7 at 12 mth). Plasma albumin and Phos levels remained unchanged as did the use of Phos supplementation. Levels of ß2M continued to rise on NHD with LF, indicating inadequate clearance. With the introduction of HF there was a significant fall in ß2M levels consistent with improved clearance. The implications of this are that ß2M clearance may be time and frequency dependent only if dialyser membrane flux is adequate.
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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".