Prevalence of multidrug-resistant bacteria in Ethiopia: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Multidrug-resistant (MDR) bacteria are a significant public-health threat worldwide, especially in low- and middle-income countries. Comprehensive data are important to understand the magnitude of multidrug resistance (MDR), however these are not available in Ethiopia. METHODS: ). Funnel plot was used to check for publication bias. The quality of each article was checked using the Newcastle-Ottawa checklist adapted for cross-sectional studies. RESULTS: = 97.48%, P < 0.001). Funnel plot revealed no publication bias. Sidama (81.7%) had the highest MDR and Tigray (51.1%) the lowest. The greatest source of MDR was from multiple sites of infection (MSI) (76.8%); the least was from bloodstream infections (62.9%). MDR was higher in studies conducted on hospital-acquired infections (72.1%) compared with both hospital- and community-acquired infections (69.8%). CONCLUSION: Our study indicates a high prevalence of MDR in Ethiopia. Sidama region, MSI and hospital-acquired infections showed the highest MDR in subgroup analysis. Regional hospitals should implement infection prevention and proper use of antibiotics in the community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".