Vancomycin Sensitivity of Staphylococcus Aureus Isolates from Hospital Patients in Karachi, Pakistan
Bibliographic record
Abstract
Methicillin-resistant Staphylococcus aureus (S. aureus) (MRSA), resistant to all antibiotics including Vancomycin, has been reported in Japan, USA, Canada and Brazil. Hence, the main objective of this study was to evaluate the possible presence of Vancomycin resistant or intermediate S.aureus in Karachi. A total of 850 clinical isolates were collected from two civil hospitals in the city between February 2006 and January 2007. They were identified using standard bacteriological methods.Sensitivity to recommended antibiotics was determined by disc diffusion, agar dilution, and E-test quantitative minimum inhibitory concentration (MIC). Susceptibility to natural or semi-natural products was determined by the agar dilution method. Out of 850 isolates, 250 were MRSA, of which 22% were resistant to 4 □g/ml Vancomycin, 24% to 8 □g/ml, 15.2% to 16 □g/ml, 10% to 20 □g/ml, and 13.2% to 30 □g/ml; the remaining 15.6% were sensitive to all used concentrations. Although we did not detect any Vancomycin-resistant S. aureus (VRSA), we found that 13% of the strains were intermediates (VISA), i.e. resistant to 30 □g/ml of Vancomycin. Because of the continuously increasing prevalence of VISA, it is imperative to minimize the use of Vancomycin. Indeed, the drug should only be prescribed for the treatment of documented, culture-proven infections with MRSA that are not susceptible to routine or alternative agents. This should help avoid the consequences of the development of Vancomycin resistant S. aureus (VRSA) in our environment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".