Switching From Saline Solution to an Antimicrobial Solution for Pre-Catheter Skin Cleansing
Bibliographic record
Abstract
The Infection Prevention and Control team at Rotherham Foundation Trust made the decision to switch from saline solution to an antimicrobial solution for skin cleansing prior to urinary catheterisation. The first stage of the switch has taken place in the community, with secondary care likely to follow suit at a later stage. The rationale for the switch, the two year journey it took to implement the changes and the parameters by which the success of the switch will be evaluated, are discussed in this article. Catheter-associated urinary tract infections (CAUTI) are a cause of considerable concern and any measures which can be taken to potentially reduce the rate of CAUTI’s should be given careful consideration. In 2012 the Infection Prevention and Control team at Rotherham Foundation Trust switched from saline solution to an antimicrobial solution (Octenilin® cleaning solution sachets) for skin cleansing prior to urinary catheterisation to try to reduce CAUTI’s. Initially, Octenilin cleansing solution sachets were intended for use solely for patients with a current or historical confirmed result of MRSA in the urine and/or other sites. However, use has been extended to other patients, including those with a history of E. coli or Klebsiella, Gram-negative organisms frequently identified as a source of UTI’s. Early feedback from using Octenilin cleansing solution sachets in place of saline solution has indicated a high level of satisfaction from both patients and health-care professionals. Reports of catheterisation-associated trauma have reduced significantly and no CAUTI’s have been identified to date.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".