Effect of ultrafiltration during hemodialysis on hepatic and total-body water: an observational study
Bibliographic record
Abstract
BACKGROUND: The hepatic circulation is involved in adaptive systemic responses to circulatory stress. However, it is vulnerable to both chronic hypervolemia and cardiac dysfunction. The influence of hemodialysis (HD) and ultrafiltration (UF) upon liver water content has been understudied. We conducted a detailed pilot study to characterize the effects of HD upon liver water content and stiffness, referenced to peripheral fluid mobilization and total body water. METHODS: We studied 14 established HD patients without liver disease. Magnetic resonance imaging (MRI) together with ultrasound-based elastography and bioimpedance assessment were employed to measure hepatic water content and stiffness, body composition, and water content in the calf pre- and post-HD. RESULTS: Mean UF volume was 8.13 ± 4.4 mL/kg/hr. Fluid removal was accompanied with effective mobilization of peripheral water (measured with MRI within the thigh) from 0.85 ± 0.21 g/mL to 0.83 ± 0.18 g/mL, and reduction in total body water (38.9 ± 9.4 L to 37.4 ± 8.6 L). However, directly-measured liver water content did not decrease (0.57 ± 0.1 mL/g to 0.79 ± 0.3 m L/g). Liver water content and IVC diameter were inversely proportional (r = - 0.57, p = 0.03), a relationship which persisted after dialysis. CONCLUSIONS: In contrast to the reduced total body water content, liver water content did not decrease post-HD, consistent with a diversion of blood to the hepatic circulation, in those with signs of greater circulatory stress. This novel observation suggests that there is a unique hepatic response to HD with UF and that the liver may play a more important role in intradialytic hypotension and fluid shifts than currently appreciated.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".