Role of maternal mental health disorders on stillbirth and infant mortality risk: a protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Maternal mental health disorders such as anxiety and depression are major public health concerns. Evidence shows a link between maternal mental health disorders and preterm birth and low birth weight. However, the impacts of maternal mental health disorders on stillbirth and infant mortality have been less investigated and inconsistent findings have been reported. Thus, using the available literature, we plan to examine whether prenatal maternal mental health disorders impact the risk of stillbirth and infant mortality. Methods and analysis This systematic review and meta-analysis will adhere to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and will be registered with the International Prospective Register of Systematic Reviews. Systematic searches will be conducted (from database inception to December 2019) in Medline, Embase, PsycINFO and Scopus for studies examining the association of prenatal mental health disorders and stillbirth and infant mortality. The search will be limited to studies published in English language and in humans only, with no restriction on the year of publication. Two independent reviewers will evaluate records and assess the quality of individual studies. The Newcastle–Ottawa scales and GRADE (Grading of Recommendations, Assessment, Development and Evaluations) approach will be used to assess the methodological quality and bias of the included studies. In addition to a narrative synthesis, a random-effects meta-analysis will be conducted when sufficient data are available. I 2 statistics will be used to assess between-study heterogeneity in the estimated effect size. Ethics and dissemination As it will be a systematic review and meta-analysis based on previously published evidence, there will be no requirement for ethical approval. Findings will be published in a peer-reviewed journal and will be presented at various conferences. PROSPERO registration number 159834.
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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 | 0.091 | 0.123 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.023 | 0.037 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.071 | 0.007 |
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".