ΔCt-informed, calibrated logistic regression accurately attributes <i>mecA</i> in <i>Staphylococcus aureus</i> -positive wound specimens
interpretability in polymicrobial specimens tested by panel-based molecular assays and can reduce unnecessary MRSA-directed antibiotics. IMPORTANCE: attribution without additional instrumentation or workflow changes. Accurate attribution reduces biologically implausible MRSA calls while preserving detection of probable MRSA, supporting more rational antimicrobial stewardship in polymicrobial wound infections.
Authors
- Keagan H. Lee (ORCID: https://orcid.org/0009-0000-3222-3274)
- Hans Norouzi (ORCID: https://orcid.org/0009-0002-0222-8167)
- Mehdi Dehghani
- Shabnam Dehghan
- Howard L. Martin
Institutions
- Excel Diagnostics Imaging (US)
- CS Diagnostics (DE)
Publication Details
- Journal
- Microbiology Spectrum
- Published
- 2026-03-31
- DOI
- https://doi.org/10.1128/spectrum.03230-25
- Primary Topic
- Antimicrobial Resistance in Staphylococcus
- Type
- article
- Field-Weighted Citation Impact
- 0.00