Clinical effectiveness of rapid tests for methicillin resistant Staphylococcus aureus(MRSA) in hospitalized patients: a systematic review
Bibliographic record
Abstract
BACKGROUND: Methicillin resistant Staphylococcus aureus (MRSA) are often resistant to multiple classes of antibiotics. The research objectives of this systematic review were to evaluate the clinical effectiveness of polymerase chain reaction (PCR) versus chromogenic agar for MRSA screening, and PCR versus no screening for several clinical outcomes, including MRSA colonization and infection rates. METHODS: An electronic literature search was conducted on studies evaluating polymerase chain reaction techniques and methicillin (also spelled meticillin) resistant Staphylococcus aureus that were published from 1993 onwards using Medline, Medline In-Process & Other Non-Indexed Citations, BIOSIS Previews, and EMBASE. Due to the presence of heterogeneity in the selected studies, the clinical findings of individual studies were described. RESULTS: Nine studies that compared screening for MRSA using PCR versus screening using chromogenic agar in a hospital setting, and two studies that compared screening using PCR with no or targeted screening were identified. Some studies found lower MRSA colonization and acquisition, infection, and transmission rates in screening with PCR versus screening with chromogenic agar, and the turnaround time for screening test results was lower for PCR. One study reported a lower number of unnecessary isolation days with screening using PCR versus screening with chromogenic agar, but the proportion of patients isolated was similar between both groups. The turnaround time for test results and number of isolation days were lower for PCR versus chromogenic agar for MRSA screening. CONCLUSIONS: The use of PCR for MRSA screening demonstrated a lower turnaround time and number of isolation days compared with chromogenic agar. Given the mixed quality and number of studies (11 studies), gaps remain in the published literature and the evidence remains insufficient. In addition to screening, factors such as the number of contacts between healthcare workers and patients, number of patients attended by one healthcare worker per day, probability of colonization among healthcare workers, and MRSA status of hospital shared equipment and hospital environment must be considered to control the transmission of MRSA in a hospital setting.
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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 | 0.011 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".