Prevalence of Neonatal Sepsis in Ethiopia: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction. Neonatal sepsis is a systemic infection occurring in infants during the first 4 weeks of life and is a major cause of mortality and morbidities of newborns due to their age-related weak and immature immune systems. In Ethiopia, despite many studies being conducted on neonatal sepsis, the reported findings are inconsistent. The aim of this study is to determine the prevalence of neonatal sepsis to enhance the utility and interpretation of the evidence. Methods. An extensive systematic review and meta-analysis were performed to extract studies on the prevalence of neonatal sepsis in Ethiopia. The PubMed, Cochrane Library, ScienceDirect, Web of Science, and Google Scholar were systematically searched. Two independent authors selected and extracted the data from each included article. The heterogeneity of included studies was assessed using the Higgins I2 test, and a random-effects model was performed in Stata/se Version 14. Results. Eighteen studies with a sample size of 10,495 study subjects were included with a reported range of neonatal sepsis from 17% to 78%. The pooled prevalence of neonatal sepsis was 45% (95% CI: 35, 55; I2=99.3% , p<0.01 ). Early onset neonatal sepsis was found to have a prevalence of 75.4% (95% CI: 68.3, 82.6). Subgroup analysis in the study area (i.e., by region) was calculated revealing the highest neonatal sepsis in Amhara region at 64.4% (95% CI: 44.9, 84.0) and the lowest in Southern Nations, Nationality, and People at 28% (95% CI: 16, 40). Conclusion. In this review, the prevalence of neonatal sepsis in Ethiopia was found to be high, especially in terms of early onset neonatal sepsis. As a result of the findings, it is important to consider the early and optimal points for interventions to better manage the prevalence and outcomes of neonatal sepsis. Further research is needed to investigate the neonatal sepsis status at different regions and associated factors for neonatal sepsis not yet studied.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.036 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".