Bibliographic record
Abstract
MRSA/MRSE infections appear to be increasing in prevalence and virulence. Prevalence has increased from 2.4% of all infected TJAs in 1975 to 37% in 2006. In addition work from several centers has shown that cure rates for these infections are far below that of nonresistant organisms. In a recent study from our institution 50 consecutive cases of MRSA/MRSE were treated with two-stage exchange with a Prostalac spacer as the interval operation. Final reinfection rate was 18% which was far worse than the 4% failure reported from our center in MS staph species. This high failure rate is supported by work from other centers. Clearly with the increasing prevalence and virulence of MRSA/MRSE new strategies are needed. The rest of this talk will focus on 2 different strategies: prevention and treatment. Prevention strategies can either target carriers or all patients. In a study by Kim et al. carriers were targeted and they reported a 50% reduction in surgical site infections. At our institution a recent program was implemented where all surgical patients were targeted. Results from this will be presented. While prevention strategies seem quite hopeful new treatment options have to be looked at. Traditionally vancomycin has been the mainstay of local and systemic treatment. Other options currently being explored include such agents as fusidic acid, daptomycin and liniazid. Research is looking at the effectiveness of these agents both locally and systemically. MRSA/MRSE infections are becoming increasingly difficult to treat. New strategies for combatting these will include both new prevention and treatment strategies as outlined in this talk.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.016 |
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".