Pharmacokinetics of small hyperbranched polyglycerols as an osmotic agent for peritoneal dialysis: Plasma exposure, organ distribution and excretion in rats
Bibliographic record
Abstract
BACKGROUND: Small hyperbranched polyglycerol (HPG) has been recently of interest for peritoneal dialysis, but its pharmacokinetics is barely understood. This study investigated the absorption, distribution and excretion of 1 and 3 kDa HPG. METHODS: H-labelled HPG-containing solutions intraperitoneally (IP) or intravenously (IV). Radioactivity in tissues, urine and faeces was counted using a scintillation counter. Pharmacokinetic parameters were calculated using WinNonlin software. RESULTS: During 8-h dwell with IP injected therapeutic dose of HPG-based hypertonic solutions, the plasma levels of 1 kDa HPG reached the peak at 2 h, followed by a decrease to the end, whereas 3 kDa HPG increased for the duration of the 8 h. At the experimental endpoint, the distribution of both sizes of HPG in major organs was minimal, whereas most of 1 kDa HPG was excreted via urine, and of 3 kDa remained in peritoneal cavity. The elimination of both 1 and 3 kDa HPG after either IP or IV administration was significantly delayed by 5/6 Nx or BNx as compared to naive controls. Further, 24-h faecal excretion of HPG (3 kDa) was <5% of injected dose that was not different between healthy and BNx rats. CONCLUSION: Data suggest size-dependent peritoneal absorption of osmotic HPG that are not specifically absorbed by any of the organs tested. The clearance of small HPG mainly depends on kidney excretion, implying the risk of HPG accumulation in patients with end-stage kidney disease who receive maintenance dialysis with HPG.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".