Risks and Policies Focused on Hospital Infections and Contaminated Textiles
Bibliographic record
Abstract
Background: Recent published studies demonstrate that clinical textiles and other wearables are a source of hospital infections. This Workshop will address three aspects of the issue: a) a review of the current infectious outbreaks and their specific pathogens; b) the multiple publics at risk for healthcare infections; and c) the basis for current standards and future policies in the EU, US, and elsewhere. Workshop format: Introduction by DF Goldsmith; outbreak of pediatric mucormycosis in New Orleans by CDC scientists; methicillin-suspectible Staphylcocus aureus contamination of clinical staff lanyards in London; laundry contamination by zygomycetes in Hong Kong by KY Yuen; control of hospital infections by the use of copper oxide in Tel Aviv; Summary by MP Muller. The populations at risk for textile transmitted infections include patients, healthcare providers, the general public visiting hospitals and nursing homes; and laundry employees by DF Goldsmith.Standards and Policy Introduction by D Hoefer; Hohenstein Institute testing for <20 colony forming units (CFU) by D Hoefer; "Hygienically Clean" in the US by DF Goldsmith; improved technologies including improvements in detergents, bleaches and temperature; biocidical naocopper fiber treatments; and possible reduction to <15 CFU. Conclusions and Future Public Health Issues, Surveillance by DF Goldsmith and D Hoefer. Synthesis: Transmission of healthcare infections is an area needing more epidemiology research and leadership. This will become a higher concern with the findings of drug resistant pathogens and the need for improving prevention control technologies.
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 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 | 0.000 |
| 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) | 0.001 | 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".