Nitric Oxide Charged Catheters as a Potential Strategy for Prevention of Hospital Acquired Infections
Bibliographic record
Abstract
Background. Hospital-acquired infections are associated with catheterization. ENOX generates an anti-infective barrier on catheters by charging them with nitric oxide (NO). In vitro, NO– charged (NO+) urinary catheters slowly release low concentrations of NO upon contact with urine and prevent bacterial colonization and biofilm formation onto catheters. Aims: (1) to assess in vitro the anti-infective properties of other types of NO+ catheters; (2) to evaluate the safety and tolerability of NO+ urinary catheters in a phase 1 clinical study. Methods. (1) Tracheal, dialysis and biliary catheters were charged with NO. NO+ and non-charged (NO–) control tracheal, and dialysis and biliary catheters were contaminated with Pseudomonas aeruginosa (102 CFU/ml) and Escherichia coli (101, 102 and 103CFU/ml) for 24-hour incubation period. Bacterial colonization onto catheters and planktonic growth in culture medium was assessed using standard plating methods. (2) Safety and tolerability of NO+ urinary catheters was assessed in 6 patients undergone radical prostatectomy catheterized for 7–21 days and followed for 50 days, and compared to 6 patients catheterized with NO– catheter. Safety was evaluated by the number of NO-related adverse events (AEs) and serious AEs (SAEs). Results. (1) NO+ catheters prevented Pseudomonas aeruginosa and Escherichia coli colonization onto tracheal, and dialysis and biliary catheters, respectively. Inoculation of NO– dialysis and biliary catheters with 101, 102 and 103 CFU/ml of Escherichia coli resulted in up to 108 CFU/ml of planktonic bacteria in culture media. In contrast, NO+ dialysis catheters killed all planktonic bacteria at all inoculations, whereas NO+ biliary catheter killed all planktonic bacteria at 101 and 102 CFU/ml inoculations and reduced the number of planktonic bacteria by 3 logs at 103CFU/ml inoculation, in comparison to NO– control catheters. (2) All patients catheterized with NO+ catheter successfully completed the study without experiencing NO-related AEs such as priapism and local irritation. No differences in hematological, biochemical and coagulation parameters were detected between both groups throughout the study. Conclusion. These data highlights the potential of NO-based platform technology as a safe and effective strategy for preventing catheter-associated HAI's. Disclosures. D. Greenberg, ENOX: Shareholder, Licensing agreement or royalty; M. Mizrahi, ENOX: Employee, Salary; Y. Av-Gay, ENOX: Board Member and Shareholder, Licensing agreement or royalty
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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 | 0.002 |
| 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".