Escalation of antimicrobial resistance among MRSA part 2: focus on infections and treatment
Bibliographic record
Abstract
Introduction MRSA is associated with causing a variety of infections including skin and skin structure infections, catheter and device-related (e.g. central venous catheter, prosthetic heart valve) infections, infectious endocarditis, blood stream infections, bone, and joint infections (e.g. osteomyelitis, prosthetic joint, surgical site), central nervous system infections (e.g. meningitis, brain/spinal cord abscess, ventriculitis, hydrocephalus), respiratory tract infections (e.g. hospital-acquired pneumonia, ventilator-associated pneumonia), urinary tract infections, and gastrointestinal infections. The emergence and spread of multidrug resistant (MDR) MRSA clones has limited therapeutic options. Older agents such as vancomycin, linezolid and daptomycin and a variety of newer MRSA antimicrobials and combination therapy are available to treat serious MRSA infections.Areas covered The authors discuss infections caused by MRSA as well as common older and newer antimicrobials and combination therapy for MRSA infections. A literature search of MRSA was performed via PubMed (up to September 2022), using the keywords: antimicrobial resistance; β-lactams; multidrug resistance, Staphylococcus aureus, vancomycin; glycolipopeptides.Expert opinion Innovation, discovery, and development of new and novel classes of antimicrobial agents are critical to expand effective therapeutic options. The authors encourage the judicious use of antimicrobials in accordance with antimicrobial stewardship programs along with infection-control measures to minimize the spread of MRSA.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".