Vancomycin resistant enterococci healthcare associated infections.
Bibliographic record
Abstract
BACKGROUND: Vancomycin-resistant enterococci (VRE) are among the most common healthcare associated multidrug-resistant organisms. Purpose of the article was to review recent data regarding the epidemiology, clinical issues and infection control of this organisms. METHODS: A PubMed-MEDLINE search was carried out. RESULTS: The European Antimicrobial Resistance Surveillance System (EARSS) highlights a large variability between the various european countries, with VRE ranging from <2% (Finland, Holland) to >20% (Ireland, Greece, Portugal). Italy shows a low rate level (4.2%). In USA according to the National Healthcare Safety Network (NHSN) in 2006-2007 overall 33% of enterococci were resistant to vancomycin, whereas in Canada VRE prevalence showed to be much lower <10%. Although with some methodological limits, several studies showed that infections caused by VRE are more serious and associated to a higher mortality rate and economic burden compared to those caused by vancomycin susceptible enterococci (VSE). The average increased associated mortality was over two-fold. Resistance to newer antimicrobial agents as daptomycin and linezolid has been described, complicating treatment options for infections caused by these organisms. CONCLUSION: Control measures aimed at reducing the incidence of VRE colonization and infection in healthcare settings should include: hand washing with an antiseptic or a waterless antiseptic agent, routine screening for vancomycin resistance among clinical isolates, rectal surveillance cultures, contact isolation for patients with VRE and antimicrobial stewardship.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".