Molecular epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) isolates from major hospitals in Riyadh, Saudi Arabia
Bibliographic record
Abstract
The few studies that have reported the incidence of methicillin-resistant Staphylococcus aureus (MRSA) in Saudi Arabia have indicated that a diverse number of circulating MRSA strains have been detected in several major hospitals. Thus, this study was designed to track the presence of MRSA strains in major hospitals in Riyadh, Saudi Arabia, and perform comparative chromosomal DNA analysis of MRSA strains for epidemiological investigation using pulsed-field gel electrophoresis (PFGE). Correlation of the PFGE types generated with microbiological and clinical data of the isolates was attempted. Screening for decreased susceptibility to vancomycin among the isolates was also done. A dendogram was generated using PFGE macrorestriction fragments and 6 types were identified (M1-M6) with M1 being predominant and widespread. A clear link between PFGE types and some clinical and microbiological data available for the strains was found. For example, M1 was statistically associated with male patients, whereas the unique types were associated with female patients, M2 was associated with isolates from wounds and age group <5 years, and M4 was associated with isolates from patients admitted to intensive care units. M5 was highly correlated with low sensitivity to linezolid. No vancomycin-resistant isolates were detected.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".