Sinonasal methicillin-resistant Staphylococcus aureus: updates on treatment
Bibliographic record
Abstract
PURPOSE OF REVIEW: Over the past two decades, the management of methicillin-resistant Staphylococcus aureus (MRSA) in chronic rhinosinusitis has posed significant challenges. This document reviews current management techniques and novel treatment modalities for sinonasal MRSA infections. RECENT FINDINGS: Topical antibiotic therapy, that is, drops (ofloxacin) and ointments (mupirocin) as off-label use for the management of MRSA chronic sinusitis, has shown beneficial results. Other more recently trialed nonantibiotic modalities such as antimicrobial photodynamic therapy and colloidal silver irrigation are also showing promise. SUMMARY: Sinonasal MRSA is considered to be associated with recalcitrant chronic sinusitis. Advancements in systemic and local antibiotics in its management have been slow and unsatisfactory. Attention is shifting to the use of nonantibiotic antibacterial treatments. Knowledge of these options is critical to improve the overall management of these chronic patients.
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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".