New and emerging concepts in managing and preventing community‐associated methicillin‐resistant <i>Staphylococcus aureus</i> infections
Bibliographic record
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) infections occurring within communities are increasing and can affect healthy individuals who have had little to no experience with hospital or healthcare settings (community-associated MRSA, CA-MRSA). CA-MRSA infections have multiple presentations which can make diagnosis and timely treatment difficult yet often manifest as a skin and soft tissue infection (SSTI) requiring dermatological intervention. There is emerging evidence of multiple environmental sources of bacteria that may contribute to recurrence. As with other infections, preventing transmission and recurrence depends on adherence to hand-washing and personal hygiene practices. Pharmaceutical intervention should be culture- rather than empirically-guided. The goal of this review is to provide dermatologists with a brief summary of the diagnostic features of CA-MRSA infections and updated strategies for management and prevention of transmission and recurrence of CA-MRSA infections, infections likely to present to dermatology offices.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".