Multiplex PCR assays for the detection of clinically relevant antibiotic resistance genes in staphylococci isolated from patients infected after cardiac surgery
Bibliographic record
Abstract
Multiresistant staphylococci (82 Staphylococcus aureus and 114 coagulase-negative staphylococci) were characterized by testing with rapid multiplex polymerase chain reaction (PCR) assays for species identification and detection of associated antibiotic resistance genes. These 196 staphylococci were isolated from 149 adult patients who developed wound infection after elective coronary artery bypass grafts and/or valve surgery. The multiplex PCR assays allowed identification of the most common staphylococcal species with S. aureus- and Staphylococcus epidermidis-specific primers as well as the detection of the erythromycin resistance genes ermA, ermB, ermC and msrA, the aminoglycoside resistance gene aac(6')-aph(2"), the oxacillin resistance gene mecA and the penicillin resistance gene blaZ. There was a very good correlation between the genotypic analysis by PCR and the phenotype determined by standard methods of susceptibility testing and identification of staphylococcal species: 100% for erythromycin resistance, 98.0% for gentamicin resistance, 99.0% for oxacillin resistance, 100% for penicillin resistance and 100% for S. aureus and S. epidermidis species identification. This study suggests that the incidence and distribution of the tested clinically relevant antibiotic resistance genes in staphylococci associated with infections after cardiac surgery do not differ from those in strains from other infections. These multiplex PCR assays may be used as diagnostic tools to replace or complement standard methods of susceptibility testing and identification of staphylococci.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".