Prevalence of Methicillin-Resistant Staphylococcus aureus (MRSA) Nasal Colonization among Healthy AAU Undergraduates
Bibliographic record
Abstract
Background: The colonization of different parts of human body by Staphylococcus aureus has been incriminated in many disease conditions and has become a major problem in the control of both community and hospital associated infections. A healthy carrier can therefore serve as a pool for regular and consistent release of the organism to the community. Objective: This study was carried out to assess the level of nasal colonization by MRSA among apparently healthy undergraduate students of Adekunle Ajasin University, Akungba-Akoko, Nigeria. Materials and Methods: A well-structured questionnaire which captured participants’ biodata and determined their suitability for the investigation was administered on each volunteer. Nasal swab samples for the culture and isolation of S. aureus were obtained from 350 apparently healthy students spread across the five faculties of the University. Samples were cultured on Manitol Salt Agar and MacConkey agar. Confirmed S. aureus isolates were screened for methicillin resistance using Cefoxitin disc. Susceptibility of all isolates was done on Meuller-Hinton agar using disc diffusion method. Results: The volunteers were made up of 142 males and 198 females with mean age of 19.5 ± 2.1. Ninety-eight samples (28%) were positive for S. aureus out of which 9(2.6%) were screened positive for MRSA. Other organism isolated is Coagulase –ve Staphylococci. The frequency of isolation of MRSA was higher (1.7%) among the female volunteers. S. aureus isolates were susceptible to Erythromycin (86.5), Augmentin (80.9%) and Gentamycin (80.9%) and highly resistant to Tetracycline 21(89%). High resistance was shown by MRSA to Penicillin, Ampicillin, Tetracycline and Cotrimoxazole. Conclusion: A prevalence rate of 2.6% MRSA observed in this study was high enough to generate concern, since they were all healthy carriers. Prophylactic treatment and personal hygiene are therefore advocated among this studied group to curb its spread.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Prevalence study of MRSA nasal colonization among Nigerian undergraduates; a microbiology/epidemiology question.
It measures MRSA colonization among Nigerian undergraduates, not research practice.
Microbiology prevalence study of MRSA nasal colonization in students, not metaresearch.
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 | 0.001 | 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".