Recovery Rate of Children From Pneumonia and Its Predictors in Ethiopia: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Background Sub‐Saharan Africa accounts for the majority of child pneumonia mortality and morbidity. The pooled recovery rate of children from pneumonia and its predictors is not well known in Ethiopia. Aim The aim of this systematic review and meta‐analysis is to determine the pooled recovery rate of children from pneumonia and its predictors in Ethiopia. Methods The major databases used to search articles were Web of Science, Science Direct, PubMed, Google Scholar, and African journals online. The data were extracted independently from eligible primary studies using a standardized spreadsheet. The quality of the included studies was assessed using the Newcastle–Ottawa scale critical appraisal checklist for the cohort study. The pooled effect size with a 95% CI was estimated by the random‐effects model of meta‐analysis. The amount of heterogeneity across the studies was assessed by I 2 . A sensitivity analysis was conducted. Results In this systematic review and meta‐analysis, 6173 children with pneumonia were included; out of these, 4871 had recovered. The pooled recovery rate of children from pneumonia was 17.7 (95% CI: 14.61–20.79) per 100 children per day. Children who lived in rural areas (AHR = 0.81, 95% CI: 0.74–0.88), stunted children (AHR = 0.77, 95% CI: 0.56–0.99), children with dangerous signs (AHR = 0.78, 95% CI: 0.66–0.9), not fully vaccinated children (AHR = 0.55, 95% CI: 0.11–0.99), comorbid children (AHR = 0.57, 95% CI: 0.48–0.65), and children with a history of respiratory infection (AHR = 0.86, 95% CI: 0.76–0.96) had a lower recovery rate from pneumonia. Conclusion In the current study, the recovery rate of children from pneumonia was 17.7 per 100 child‐days. Children living in rural areas recovered more slowly. Healthcare providers should give special attention at admission for screening of children with stunted, danger signs, not fully vaccinated, comorbid, and histories of respiratory tract infection.
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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 | 0.018 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.053 |
| Bibliometrics | 0.007 | 0.006 |
| 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".