Role of Xpert PCR kit in estimating Methicillin-resistant Staphylococcus Aureus in teaching tertiary level hospital in Pakistan
Bibliographic record
Abstract
Abstract Background: The colonization of MRSA increases therisk of MRSA infection, making it crucial to identify colonized patients accurately and rapidly. The conventional culture-based method for detecting MRSA colonization has limitations in terms of sensitivity and turnaround time, leading to delayed implementation of infection control measures. A rapid PCR-based method can provide accurate results within a few hours and may help in identifying colonized patients promptly. Materials and Methods: Nasal and skin swab specimens were collected from all patients admitted to medical/surgical units of the Aga Khan University Hospital from 1st April 2022 to 31st December 2022 for culture-based and PCR-based MRSA detection (MRSA Xpert). Results: Culture identified 10.9% MRSA positive specimens whereas Xpert MRSA assay showed 100% sensitivity and 95.4% specificity. Conclusion: Our set of specimens showed a high correlation between culture-based and molecular-based methods for detecting MRSA.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".