Investigation of Current Infection-Control Practices for Ultrasound Coupling Gel
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Ultrasound coupling gel may serve as a vector for the spread of bacteria and has been the causative agent for significant health care-associated infections. The purpose of this study was to document existing infection-control procedures and level of contamination present within nonsterile ultrasound gel from several clinical departments at a single institution. A second purpose was to examine the effectiveness of clinician education and manufacturer-based ultrasound additives on ultrasound gel contamination and in vitro bacterial proliferation, respectively. METHODS: Compliance with Health Canada recommended infection-control policies were determined by survey. Contamination of in-use ultrasound gel bottles was determined by inspecting cultures after 72 hours of incubation. After infection-control education, a 28-day interval assessment was used to examine contamination rates in newly provided ultrasound gel. The ability of ultrasound gel containing parabens to prevent bacterial growth was examined in cultures grown with and without ultrasound gel. RESULTS: Practitioners were not compliant with Health Canada recommendations, but the baseline ultrasound gel contamination rate within these departments was only 2.5%. Education in infection control did not improve the contamination rate over 28 days. Contamination was discovered in ultrasound gel supplied directly from the manufacturer. Ultrasound gel suppressed but did not prevent bacterial growth in a species- and time-specific manner. CONCLUSIONS: The source of contamination for in-use ultrasound gel may be of manufacturer or human origin. Because additives to the ultrasound gel are not bactericidal, sterile ultrasound gel should be used for invasive and high-risk cases, and improving infection-control policies is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".