Bacteriological Assessment of Stethoscopes Used by Medical Students in Nigeria: Implications for Nosocomial Infection Control
Bibliographic record
Abstract
Our study assessed bacteria on swabs taken from the surface of the diaphragm of stethoscopes used by medical students in Nigeria. We found bacterial contamination on 80.1% of the stethoscopes. Staphylococcus aureus and Pseudomonas aeruginosa were major isolates. Bacterial colonization was highest among stethoscopes cleaned with only water and those never cleaned with any agent or never cleaned at all. The difference was statistically significant (chi2 = 31.9, p < .05). Stethoscopes from students who cleaned them after use on each patient and from those who practised handwashing after contact with each patient had significantly lower bacterial contamination (chi2 = 26.9; p < .05 and chi2=31.9, p < 0.05, respectively). Isolates of Staphylococcus aureus showed the highest susceptibility to antibiotics, while the most effective antibiotics were Ciproflox and Erythromycin. Integration of stethoscope care in the training curriculum of medical schools will enhance the control nosocomial infections.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".