Determinants of birth asphyxia among preterm newborns in Ethiopia: a systematic review and meta-analysis of observational studies protocol
Bibliographic record
Abstract
Abstract Background Birth asphyxia accounted for nearly 50% of neonatal mortality in Sub-Saharan African countries. This scenario has been worst in Ethiopia where every two out of three deaths attributed to birth asphyxia. Moreover, studies conducted in Ethiopia were highly variable and inconclusive to estimate the pooled prevalence and determinants of perinatal birth asphyxia among preterm babies. Objective This study aimed to estimate the pooled prevalence of birth asphyxia and its determinants among preterm newborns in Ethiopia. Methods The protocol for this review is registered at PROSPERO with registration number CRD42020158224. A comprehensive online databases (PubMed, HINARI, Scopus, EMBASE, Science direct, and Cochrane library database), Google Scholar, African Journals online, other gray and online repository accessed studies will be searched using different search engines. In addition, maternity and infant care databases uploaded at Ethiopian Health Development Journal and Ethiopian Journal of Health Sciences will be searched until 30 June 2020. Newcastle-Ottawa Quality Assessment Scale (NOS) will be used for critical appraisal of studies. Three reviewers will screen all retrieved articles, conduct data extraction, and then critically appraise all identified studies. All identified observational studies reporting the prevalence of birth asphyxia and associated factors among neonates in Ethiopia will be considered. The analysis of data will be done using STATA 11.0. We will demonstrate pooled estimates and determinants of birth asphyxia with effect size and 95% confidence interval. Heterogeneity among the included studies will be assessed through the CochraneQtest statistics andI2test. Publication bias will be checked using funnel plot and Egger’s test. Finally, statistical significance level will be declared at apvalue of less than 0.05. Discussion The result from this systematic review will inform and guide health policy planners to invest limited resources on maternal and neonatal health. Furthermore, it will be a stimulus for future cumulative meta-analysis researchers in developing nations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.052 | 0.082 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.018 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.059 | 0.004 |
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".