Effects of intraperitoneal heparin on peritoneal transport in a chronic animal model of peritoneal dialysis
Bibliographic record
Abstract
BACKGROUND: Heparin has anti-inflammatory effects and is often added to the peritoneal dialysis fluid to prevent fibrin formation. Conjugation of heparin to the surface of biomaterials has been shown to improve its biocompatibility. In this study, we describe for the first time an experimental chronic peritoneal dialysis model with repeated dwell studies in non-uraemic rats and evaluate the effect of addition of heparin to glucose-based peritoneal dialysis fluid on peritoneal fluid and solute transport. METHODS: Wistar male rats, weighing 340+/-15 g, with implanted peritoneal catheters were infused during 1 month, twice per day with 20 ml of Dianeal 1.36%+antibiotics (AB; n = 10) or Dianeal 1.36%+antibiotics+heparin 2500 U/l (HAB; n = 9). After 10 (DS 1) and 30 days (DS 2), a dwell study was performed in rats with free access to drinking water, by infusing 30 ml of Dianeal 3.86%. Dialysate samples were obtained at 0, 2, 30, 60, 120 and 240 min. Blood samples were drawn before and at the end of the dwell. Radiolabelled serum albumin was used as macromolecular volume marker. RESULTS: Peritoneal volumes during DS 1 were significantly greater for the HAB group as compared with the AB group. No differences in ultrafiltration were found during DS 2 for HAB vs AB. However, peritoneal volumes were significantly higher for DS 2 compared with DS 1 in the AB group. The amount of glucose absorbed over time did not differ between the solutions, while fluid absorption tended to be lower in the HAB group. CONCLUSIONS: Heparin may improve peritoneal fluid transport possibly due to better healing and reduced peritoneal inflammation as shown in this novel animal model of chronic peritoneal dialysis with repeated dwell studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".