Does hemodiafiltration improve the removal of homocysteine?
Bibliographic record
Abstract
High prevalence of hyperhomocysteinemia is common in hemodialysis (HD) patients and could contribute to worsen the cardiovascular risk. Beyond vitamin B status, dialysis modality itself could influence homocysteine (Hcy) levels. The objective was compare the reduction rate (RR) of Hcy and cysteine in stable dialyzed patients treated by standard HD or hemodiafiltration (HDF). Seventy-five patients undergoing stable dialysis through standard high-flux HD (n = 35) or HDF (n = 40) were included. Biological parameters were determined before and after a midweek dialysis session. Urea percent reduction per session and Kt/V index (K, body urea clearance, T, time of dialysis, and V, urea distribution volume), defined as a marker of dialysis efficacy, were similar between HD and HDF groups. By contrast, higher RR of beta2 microglobulin (β2m) was observed in HDF compared with HD (78.6 vs. 72.0%, respectively; P < 0.001). Likewise, higher RR of Hcy was obtained with HDF compared to HD (46.0 vs. 41.5%, respectively; P < 0.05), whereas the RR of cysteine was similar in both groups. Interestingly, a positive correlation between Hcy RR and urea Kt/V index was observed (r = 0.29, P < 0.05) and between Hcy RR and β2m RR (r = 0.45, P < 0.001). Time-averaged concentration (TAC) of Hcy was lower with HDF compared with HD (17.8 vs. 19.1 μmol/L, respectively), although not significant. There was no difference in median Hcy according to dialysis modality for neither pre- nor postdialysis levels. Significant higher removal of Hcy was observed with HDF compared with standard HD, although urea Kt/V index was similar. Enhanced removal of middle molecules, such as β2m, could be involved in Hcy RR improvement with HDF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".