Evaluation of emergency department ultrasound machines for the presence of occult blood
Bibliographic record
Abstract
OBJECTIVES: Bedside ultrasound in the emergency department is a common diagnostic tool, especially when evaluating trauma patients. Many trauma patients have blood on their chest and abdomen that may contact the probe during examination. The primary aim of this study was to investigate whether occult blood contamination was present on the emergency department ultrasound machine, both after daily use and after use in trauma. METHODS: For a period of 31 days, the ultrasound machine at the trauma centre emergency department in Saskatoon, Saskatchewan, was tested once daily and following all Level 1 traumas. The ultrasound machine probes and keyboard were swabbed, and contamination was detected using a commercially available phenolphthalein blood testing kit. Any visible blood contamination was also noted. The machine was then cleaned following each positive test and re-tested to ensure the absence of contamination. RESULTS: Over the study period, the ultrasound machine tested positive for occult blood contamination on 10% of daily tests and on 43% of assessments after its use in trauma. The curvilinear probe was most frequently contaminated (daily, 6%; trauma, 26%), followed by the keyboard (daily, 3%; trauma, 26%), but both lacked visible contamination. CONCLUSIONS: In this single centre study, there was evidence of occult blood on the emergency department ultrasound machine after both routine use and major trauma cases, highlighting the need for a standardized cleaning and disinfection protocol.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 0.001 |
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".