Methicillin-resistant<i>Staphylococcus aureus</i>colonisation: epidemiological and molecular characteristics in an acute-care tertiary hospital in Singapore
Bibliographic record
Abstract
Current knowledge of methicillin-resistant Staphylococcus aureus (MRSA) colonisation in relation to epidemiological characteristics is incomplete. We conducted a cross-sectional study at an acute-care tertiary infectious diseases hospital of MRSA isolates identified through routine surveillance from January 2009 to December 2011. We randomly selected 205 MRSA isolates (119 inpatients) from 798 isolates (427 inpatients) for molecular profiling using multilocus sequence typing. Multilevel multinomial logistic regression was used to estimate odds ratio (OR) assessing the predilection of MRSA strains for anatomic sites, and associations of strains with human immunodeficiency virus (HIV) infection. The most frequent sequence types (STs) were 239, 22 and 45. The proportion of ST22 increased over the sampling period, replacing ST239 as the dominant lineage. However, ST239 remained the most prevalent among HIV-seropositive individuals who were six times more likely to be colonised with this strain than non-HIV patients (adjusted OR (aOR) 6.44, 95% confidence interval (CI) 1.94-21.36). ST45 was >24 times more likely to be associated with perianal colonisation than in the nares, axillae and groin sites (aOR 24.20, 95% CI 1.45-403.26). This study underlines the clonal replacement of MRSA in Singapore as previously reported but revealed, in addition, key strain differences between HIV-infected and non-infected individuals hospitalised in the same 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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".