The AMerican PREGNANcy Mother–Child CohorT: description and prevalence of baseline outcomes and medication dispensing
Bibliographic record
Abstract
Purpose: This study aims to present the AMerican PREGNANcy Mother-Child CohorT (AM-PREGNANT) and its maternal and linked-child characteristics. Methods: AM-PREGNANT was built using the Merative™ MarketScan® Commercial Database. We updated and implemented a hierarchical algorithm using ICD-9-CM and ICD-10-CM codes to identify pregnancies in individuals aged 15-45 years (2003-2021). A unique family identifier linked mothers to their children. Enrollment required continuous coverage for 90 days before, during, and 42 days after pregnancy for the mothers and 1 year after birth for the linked children. Pregnancy outcomes were categorized as deliveries, spontaneous abortions, and induced abortions. We characterized AM-PREGNANT (2004-2020) by sociodemographic factors, pregnancy history, comorbidities, and medication dispensing by pregnancy outcome. Medication dispensing, identified through filled prescriptions using drug claims, was analyzed for the 90 days before pregnancy until the last menstrual period (LMP), throughout pregnancy, and from delivery through the postpartum period. Linked children were assessed for low birth weight (LBW), preterm birth, congenital malformations, and other characteristics. Maternal and gestational age distributions were compared with United States (US) national estimates. Results: We identified 7,991,200 pregnancies from 6,079,647 persons (2003-2021). Applying continuous enrollment criteria and restricting the study period to 2004-2020 resulted in 4,767,208 pregnancies. Of these, 76.9% resulted in deliveries, 17.3% were spontaneous abortions, and 5.9% were induced abortions. The established linked mother-child cohort comprises 2,578,990 pregnancies. The mean maternal age in the linked mother-child cohort was 30.4 years (SD, 5.4). The mean gestational age at delivery was 38.6 weeks. Infections were the most prevalent maternal comorbidity (11.8%). Among deliveries, the prevalence of medication dispensing in mothers before, during, and after pregnancy were 63.2%, 88.7%, and 82.9%, respectively. Among linked children, 52.1% were male, 12.0% were preterm, and 4.5% had low birth weight. The prevalence of major congenital malformations was 13.1%. The characteristics of children with continuous enrollment were similar to those without, except for medication dispensing during the first year of life (62.9% vs. 45.6%). Both maternal and gestational age distributions of AM-PREGNANT were comparable to the US national estimates. Conclusion: AM-PREGNANT is a valuable cohort for studying medication safety in mothers and children. Strict enrollment criteria ensured reliable data, minimizing the risk of misclassification. This cohort is a key resource for multi-country perinatal pharmacoepidemiological studies.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".