Neurocognitive Function with Conventional Hemodialysis versus Post-Dilution Hemofiltration as Initial Treatment in ESKD Patients: A Randomized Controlled Trial – The DA-VINCI Study
Bibliographic record
Abstract
INTRODUCTION: The ideal modality choice and dialysis prescription during the first renal replacement therapy (RRT) session remain unclear. We conducted a pilot study to determine the safety risk for hemodialysis (HD) versus hemofiltration (HF) and its relationship with neurocognitive assessment on incident RRT patients. METHODS: Twenty-four incident RRT patients were included. Patients were randomized to the conventional HD group or post-dilution HF group. Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MOCA) tests were applied in all patients before and after session, and brain magnetic resonance image (MRI) was performed in 7 patients from the conventional HD group and 8 patients from the post-dilution HF group before and after the intervention. RESULTS: Baseline characteristics were similar between groups. Compared to conventional HD, post-dilution HF had longer treatment time. There were no significant changes in blood pressure after RRT in both groups. The MMSE test showed no significant differences between groups or within groups. The MOCA test showed an increase in the total score for the post-dilution HF group with no significant changes between groups. The MRI evaluation showed no differences between or within groups. CONCLUSION: Post-dilution HF is a safe alternative for the first HD session in incident RRT; it allows longer treatment time if ultrafiltration is required and has a similar neurological risk than conventional HD. This is a pilot study and that larger studies are needed to confirm the findings.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".