Evaluation of Polyethylene Glycol-Based Antimicrobial Coatings on Urinary Catheters in the Prevention of <i>Escherichia coli</i> Infections in a Rabbit Model
Bibliographic record
Abstract
Introduction and Objective: Catheter-associated urinary tract infections are a major cause of patient morbidity and mortality. Despite many attempts to design biomaterials that might reduce the risk, none has had a profound impact on reducing the incidence of this most common nosocomial infection. Recent in vitro work, however, has shown promise for a silver-based biomaterial coating composed of methoxylated polyethylene glycol 3,4-dihydroxyphenylalanine (mPEG-DOPA3) in reducing uropathogen attachment and biofilm formation. The aim of this work was to investigate whether these results translate into a meaningful impact on infection development and bacterial adherence in an in vivo rabbit model. Materials and Methods: New Zealand white rabbits were randomized into groups of 12 and had the following catheters inserted: Group 1—uncoated polyurethane, Group 2—Coating A (mPEG-DOPA3 + 2 mg/mL AgNO3), and Group 3—Coating B (mPEG-DOPA3 + 10 mg/mL AgNO3). Each rabbit was challenged with 108 colony-forming units of Escherichia coli GR-12 instilled directly into the bladder at the time of catheter insertion and urine was monitored over 7 days for bacterial counts. Catheters were retrieved and evaluated for encrustation and attachment analysis, and tissues collected for histopathologic characterization and bacterial invasion. Results: Urinary bacterial colony counts were lower among rabbits in the Coating A group vs controls (4/11 vs 10/12, respectively) (p = 0.029), and there were fewer rabbits with invasive infections (3/12 vs 9/12, p = 0.02). More encrustation was observed among animals in the Coating B group vs controls (7.22 vs 2.69 mg/cm2, p = 0.033). There were no significant differences in tissue effects between groups. Conclusions: The use of a mPEG-DOPA3 urinary catheter coating effectively reduced urinary pathogen counts, while not causing adverse tissue effects in this model. Further clinical evaluation is warranted.
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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 | 0.002 | 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 | 0.000 |
| 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".