Long-Term Effect of an Ethanol/Sodium Citrate Locking Solution on the Mechanical Properties of Hemodialysis Catheters
Bibliographic record
Abstract
PURPOSE: To investigate the effect of a 30% ethanol/4% sodium citrate catheter locking solution on the mechanical properties of hemodialysis (HD) catheters over 36 weeks. METHODS: Twenty-one HD catheters were used in this study. Three catheters, not exposed to locking solutions, underwent mechanical testing to determine baseline properties. Nine of the remaining 18 catheters were filled with normal saline and underwent mechanical testing in groups of three at 12, 24 and 36 weeks. Similarly, nine catheters were filled with the 30% ethanol/4% sodium citrate locking solution and tested in a similar manner. RESULTS: The average force required to break the catheter lumens tended to be smaller in the catheters exposed to 30% ethanol/4% sodium citrate compared to saline controls at 12 and 24 weeks; however, there were no statistically significant differences between the groups after 36 weeks of exposure. The forces required to break these HD catheters are magnitudes greater than forces generated during a typical HD session. CONCLUSIONS: We conclude that the 30% ethanol/4% sodium citrate locking solution had an effect on the mechanical properties of the catheters investigated, but not to the degree that would preclude further in vivo investigation. Further studies are necessary to determine the safety and efficacy of this catheter locking solution.
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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 | 0.001 |
| 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 | 0.000 |
| 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".