Post-traumatic stress disorder, child abuse history, birthweight and gestational age: a prospective cohort study
Bibliographic record
Abstract
OBJECTIVE: To determine the extent to which prenatal post-traumatic stress disorder (PTSD) is associated with lower birthweight and shorter gestation, and to explore the effects of childhood maltreatment as the antecedent trauma exposure. DESIGN: Prospective three-cohort study. SETTING: Ann Arbor and Detroit, Michigan, United States. SAMPLE: In all, 839 diverse nulliparas in PTSD-positive (n = 255), trauma-exposed, resilient (n = 307) and non-exposed to trauma (n = 277) cohorts. METHODS: Standardised telephone interview before 28 weeks of gestation to ascertain trauma history, PTSD, depression, substance use, mental health treatment history and sociodemographics, with chart abstraction to obtain chronic condition history, antepartum complications and prenatal care data, as well as outcomes. MAIN OUTCOME MEASURES: Infant birthweight and gestational age per delivery record. RESULTS: Infants born to women with PTSD during pregnancy had a mean birthweight 283 g less than infants of trauma-exposed, resilient women and 221 g less than infants of non-exposed women (F(3,835) = 5.4, P = 0.001). PTSD was also associated with shorter gestation in multivariate models that took childhood abuse history into account. Stratified models indicated that PTSD subsequent to child abuse trauma exposure was most strongly associated with adverse outcomes. PTSD was a stronger predictor than African American race of shorter gestation and a nearly equal predictor of birthweight. Prenatal care was not associated with better outcomes among women abused in childhood. CONCLUSIONS: Abuse-related PTSD may be an additional or alternative explanation for adverse perinatal outcomes associated with low socio-economic status and African American race in the USA. Biological and interventions research is warranted along with replication studies in other nations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".