Analysis of neonatal mortality risk factors in Brazil: a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
To identify, using a systematic review and meta-analysis of observational studies, which risk factors are significantly associated with neonatal mortality in Brazil, and to build a comprehensive national analysis on neonatal mortality. This review included observational studies on neonatal mortality, performed between 2000 and 2018 in Brazilian cities. The MEDLINE, Elsevier, Cochrane, LILACS, SciELO, and OpenGrey databases were used. For the qualitative analysis, the Newcastle-Ottawa Scale was used. For the quantitative analysis, the natural logarithms of the risk measures and their confidence intervals were used, as well as the DerSimonian and Laird method as a random effects model, and the Mantel–Haenszel model for heterogeneity estimation. A confidence level of 95% was considered. The qualitative analysis resulted in six studies of low and four studies of intermediate-low bias risk. The following exposure factors were significant: absence of partner, maternal age ≥35 years, male gender, multiple gestation, inadequate and absent prenatal care, presence of complications during pregnancy, congenital malformation in the assessed pregnancy, Apgar < 7 at the fifth minute, low and very low birth weight, gestational age ≤ 37 weeks, and caesarean delivery. The most significant risk factors presented in this study are modifiable, allowing aiming at a real reduction in neonatal deaths, which remain high in the country. Identificar, através de uma revisão sistemática e da metanálise de estudos observacionais, quais fatores de risco associam-se significativamente com a mortalidade neonatal no Brasil e construir uma análise nacional abrangente sobre a mortalidade neonatal. Foram avaliados os estudos observacionais sobre mortalidade neonatal realizados entre os anos 2000 e 2018 em cidades brasileiras. Usaram-se as bases MEDLINE, Elsevier, Cochrane, LILACS, SciELO e OpenGrey. Para a análise qualitativa, foi utilizada a Escala Newcastle-Ottawa. Para a análise quantitativa, foram utilizados os logaritmos naturais das medidas de risco e de seus intervalos de confiança, o método de DerSimonian e Laird como modelo de efeitos aleatórios, e o modelo de Mantel-Haenszel para estimativa da heterogeneidade. Considerou-se nível de confiança de 95%. A análise qualitativa resultou em seis estudos de baixo e quatro estudos de intermediário-baixo risco de viés. Foram significativos os seguintes fatores de exposição: ausência de companheiro, idade materna ≥ 35 anos, sexo masculino, gestação múltipla, pré-natal inadequado e ausente, presença de intercorrências durante a gestação, de malformação congênita na gestação em estudo, Apgar < 7 no quinto minuto, baixo e muito baixo peso ao nascer, idade gestacional ≤ 37 semanas e parto cesariano. Os fatores de risco mais significativos apresentados neste estudo são modificáveis, o que possibilita almejar uma redução real das mortes neonatais, que ainda permanecem elevadas no país.
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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 | 0.025 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.011 | 0.012 |
| 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) | 0.002 | 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".