Toward the development of evidence-based guidelines for the management of methicillin-resistant Staphylococcus aureus otitis.
Bibliographic record
Abstract
OBJECTIVES: (1) To determine the causative bacteriology of discharging ears in a case series from a tertiary/quaternary academic centre serving an urban population and from a review of the literature and (2) to develop treatment guidelines for methicillin-resistant Staphylococcus aureus (MRSA) otorrhea based on the best available evidence. METHODS: A retrospective analysis of all "ear" cultures from the microbiology laboratory at St. Paul's Hospital, Vancouver, was performed to ascertain a qualitative analysis on the susceptibility and bacteriology data. A systematic review of the literature was performed for all studies examining the bacteriology, susceptibility, and treatment for any MRSA infection producing otorrhea. RESULTS: Staphylococcus aureus and Pseudomonas aeruginosa (PA) were present in 39.7% and 13.5%, respectively, of ear cultures obtained at our institution versus 9.9 to 54.1% and 25.0 to 48.6% in identified studies in the literature. Methicillin-sensitive Staphylococcus aureus (MSSA) was present more frequently than MRSA (31.2% vs 8.5% at our institution; 16.9% vs 6.9% in the literature). MRSA isolates were often resistant to gentamicin (14.8%) and ciprofloxacin (7.7%) but susceptible to trimethoprim-sulfamethoxazole (TMP-SMX) (85.3%) and fusidic acid (96.3%), suggesting a preponderance of the "community strain" of MRSA. CONCLUSION: The susceptibility of MRSA to antibiotics in commonly used otic drops (ie, gentamicin and ciprofloxacin) is low. Based on the available data, we suggest an evidence-based approach to the management of MRSA otorrhea considering whether the strain is community or hospital acquired and whether the tympanic membrane is intact.
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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 | 0.068 | 0.159 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.017 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.013 | 0.007 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".