MRSA prevalence in a teaching hospital in Western Saudi Arabia
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of Methicillin Resistant Staphylococcus aureus (MRSA) colonization in our institution. METHODS: A 5-day period prevalence study of all adult and pediatric patients. Excluded areas were the adult intensive care unit (screened on admission and weekly thereafter), the outpatient hemodialysis population (screened monthly), and newborns. Our facility is a referral/teaching hospital for the National Guard population and their dependants in Western Saudi Arabia. A total of 240 patients were screened. Nasal sampling was carried out and isolation/identification of MRSA was performed using standard microbiological methods. RESULTS: The total number of patients sampled was 240 and of those 10 (4%) were colonized. The 10 positives were found in 4 patient care areas; adult male medicine 5, adult male oncology 3, adult female medicine one, adult high dependency unit one. These patients care areas had 69 patients (42 males and 27 females). Ten (14%) were colonized by MRSA; 9 males (21%) and one female (3%). Statistical analysis Chi Square for discontinuous variables, "F" test for continuous variables found that one), male gender (p=0.04), 2) the presence of a long term invasive device (p=0.04), 3), length of stay (p=0.004) were predictive of MRSA colonization. CONCLUSION: The overall prevalence of MRSA colonization in our hospital was low, however a sub-segment of the population identified as male, having long term invasive devices, and hospitalized more than 2 weeks, were frequently colonized. Any strategy, in our hospital, to control the spread of MRSA should include the testing of this population.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".