Bibliographic record
Abstract
Introduction and Objective: Encrustation of urologic devices can increase patient morbidity thereby limiting their clinical use.Alteration of stent materials and coatings has been attempted to limit encrustation.Encrustation is associated with organic salt deposits.Our objective was to develop a urologic device encrustation model that would mimic the in vivo process better than the ones that currently rely on either the actions of enzymes or bacteria.The ideal model would be: 1) rapid, 2) sterile, and 3) reproducible, using chemical solutions.Methods: Four different stent types were tested using this model (Sof-Flex® [Cook Urological], Optima® [Bard Urological], Percuflex Plus® and Triumph®[both Boston Scientific Corp.], with each stent used in duplicate.Stent segments (1.5cm) were suspended in 500 mL artificial urine (AU) anchored to pipette tips positioned in the buoyant midsection of a pipette tip box.A modified version of Brooks and Keevil's AU was used containing 7.5mM CaCl 2 .This media was replaced daily to better represent in vivo conditions and maintain sterility.Stent pieces were incubated at 37 o C with 5.0 mM ammonium oxalate solution added constantly at a rate of 0.4 mL/min.After 7 days, the encrustation was photographed, physically removed and weighed.The mass of encrustation was compared amongst the different stent types.The results were the average of six independent experiments.Results: The slow, continuous addition of ammonium oxalate to AU promoted perpetual precipitation and deposition of crystals on all exposed surfaces.After 7 days, all device segments harboured visible surface encrustation.Encrustation was found to be the greatest on the Triumph® devices (8.20 ± 0.33mg/cm 2 ) followed by Sof-Flex (6.00 ± 0.38), Percuflex Plus (5.45 ± 0.56) and Optima (4.38 ± 0.86).These differences were found to be statistically significant (p = 0.004).Conclusions: This novel method can rapidly yield in vitro urologic device encrustation in the magnitude of milligrams/cm 2 .The protocol can be modified to hasten or slow the encrustation rate.One further benefit is the ability to test multiple stents simultaneously.This is the first method to produce non-urease-based encrustation in such a short period, using a setting of sterile artificial urine that is reproducible and closely mimics physiologic conditions.This model may be used in the future to advance stent design with the goal of improving clinical outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.489 | 0.310 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".