Health of Newborns and Infants Born to Women With Disabilities: A Meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CONTEXT: Women with disabilities are at elevated risk for pregnancy, delivery, and postpartum complications. However, there has not been a synthesis of literature on the neonatal and infant health outcomes of their offspring. OBJECTIVE: We examined the association between maternal disability and risk for adverse neonatal and infant health outcomes. DATA SOURCES: Cumulative Index to Nursing and Allied Health Literature, Embase, Medline, and PsycINFO were searched from database inception to January 2020. STUDY SELECTION: Studies were included if they reported original data on the association between maternal physical, sensory, or intellectual and/or developmental disabilities and neonatal or infant health outcomes; had a referent group of women with no disabilities; were peer-reviewed journal articles or theses; and were written in English. DATA EXTRACTION: We used standardized instruments to extract data and assess study quality. DerSimonian and Laird random effects models were used for pooled analyses. RESULTS: Thirty-one studies, representing 20 distinct cohorts, met our inclusion criteria. Meta-analyses revealed that newborns of women with physical, sensory, and intellectual and/or developmental disabilities were at elevated risk for low birth weight and preterm birth, with smaller numbers of studies revealing elevated risk for other adverse neonatal and infant outcomes. LIMITATIONS: = 17), with lack of control for confounding a common limitation. CONCLUSIONS: In future work, researchers should explore the roles of tailored preconception and perinatal care, along with family-centered pediatric care particularly in the newborn period, in mitigating adverse outcomes among offspring of women with disabilities.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it