Influence of Maternal Birth Status on Her Offspring: a Systematic Review and Meta-Analyses
Bibliographic record
Abstract
parity and LBW/PT/SGA.The study quality was assessed for biases in sample selection, exposure assessment, confounder adjustment, analyses, outcome assessment and attrition.Meta-analyses were performed using the random effect model.Unadjusted odds ratio (OR), weighted mean difference and 95% confidence intervals (CI) were calculated.The MOOSE statement criteria were followed.RESULTS: Forty studies were included.Most of them had moderate risk of bias due to failure to adjust for confounding factors.The results are presented in the table.Primiparity was associated with a reduction in birth weight (WMD 282g, 95% CI 79, 486g).CONCLUSIONS: Primiparity is associated with a significantly increased risk of LBW/SGA birth; however, the impact of confounding factors can not be underscored.BW was significantly lower in primipara mothers (an effect size similar to smoking in pregnancy).GM and GGM were not associated with LBW/PT.7 iNflueNce of MaterNal Birth status oN her offsPriNG: a systeMatic reVieW aNd Meta-aNalyses *Ps shah, V shah Knowledge synthesis Group, toronto, ontario BACKGROUND: Maternal low birth weight (LBW), preterm (PT) and/ or small for gestational age (SGA) status has been suggested as a precursor for infants being born LBW, PT or SGA.Exact mechanism by which intergenerational factors affect BW and GA are unknown; however, genetic modifiers and maternal environmental or constitutional factors are suspected to play a role.OBJECTIVE: To systematically review the risks for mothers who were LBW/ PT/SGA of having an infant being born LBW/PT/SGA.DESIGN/METHODS: Medline, Embase, CINAHL and bibliographies of identified articles were searched for English language studies of mother-infant pair being LBW, PT or SGA.Data were extracted by two authors independently and discrepancies were resolved by consensus.Study quality was assessed for biases in sample selection, exposure and outcome assessment, confounder adjustment, attrition, and analyses.When appropriate, the results were meta-analyzed and odds ratio (OR) and 95% confidence interval (CI) were calculated.MOOSE criteria were followed for meta-analyses.RESULTS: Twenty two studies from various sources (single center, regional or national databases) were included.The studies had low or moderate risk of bias.The results according to maternal LBW/preterm/SGA status for infants LBW/preterm/SGA status are reported in the Table.CONCLUSIONS: Maternal LBW/PT/SGA status was associated with an increased risk of LBW/PT/SGA status in the index child.Further research in the causation and prevention of this intergenerational association is needed.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.026 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".