Evidence map›Paper›PMID 42282186›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Development of Longitudinal, Linked Maternal-Infant Cohorts using the Epic Cosmos Electronic Health Record Dataset.

Stephanie A Leonard, Kevin Dysart, Alison Callahan, Sara Siadat, Jiaqi Zhang, Sara C Handley, Krista F Huybrechts, Irogue Igbinosa, Brian T Bateman

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Stephanie A LeonardDepartment of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California.ORCID 0000-0001-8213-1319
Kevin DysartDivision of Neonatology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.ORCID 0000-0003-2715-2293
Alison CallahanDivision of Computational Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California.ORCID 0000-0001-5163-380X
Sara SiadatDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California.ORCID 0000-0002-1972-7977
Jiaqi ZhangDepartment of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California.
Sara C HandleyDivision of Neonatology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.ORCID 0000-0001-8436-4351
Krista F HuybrechtsDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.ORCID 0000-0001-5805-8430
Irogue IgbinosaDepartment of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California.ORCID 0000-0002-1606-5381
Brian T BatemanDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California.ORCID 0000-0001-5950-8683

Funding

Stanford Women's Reproductive Health Research Career Development ProgramK12HD103084 · NICHD · STANFORD UNIVERSITY · PI LESLEE L SUBAK · 2020 to 2026
$2.2M
The impact of delivery hospital organizational structure and culture on perinatal outcomesK23HD109426 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI Sara Christine Handley · 2023 to 2026
$621k
Optimizing treatment of chronic hypertension in pregnancy using a national distributed data networkK01HL171699 · NHLBI · STANFORD UNIVERSITY · PI Stephanie A. Leonard · 2024 to 2026
$514k
NHLBI NIH HHS K01 HL171699NICHD NIH HHS K12 HD103084NICHD NIH HHS K23 HD109426
6 · The paper itself

Abstract

Background: Epic Cosmos is a relatively new centralized electronic health record dataset with high potential utility in perinatal epidemiologic research. Objectives: The study objectives were to develop replicable steps to create longitudinal, linked maternal-infant cohorts in Cosmos, assess completeness of key variables, evaluate potential selection bias with restrictions for longitudinal healthcare encounters, and provide an example epidemiologic analysis. Methods: We created maternal-infant cohorts by starting with live births during 2023-2024 recorded in the BirthFact data table and joining with additional data tables as needed. We selected and created variables for perinatal characteristics, common comorbidities, and routinely measured vital signs and laboratory values, and assessed variable completeness. We sequentially restricted the birth cohort for maternal-infant linkage and longitudinal healthcare from first-trimester prenatal care encounter through infant follow-up care within 12 weeks post-discharge from birth hospitalization. Finally, we conducted an example analysis of the association between high systolic blood pressure in the first trimester (≥140 mm Hg) and later onset of preeclampsia among those with chronic hypertension. Results: The total linked birth cohort included 2,624,186 pregnancies. Completeness was >90% for most variables assessed but was 77% for racial and ethnic group and 76% for body mass index at delivery. Characteristics of the cohort were similar to those reported for the entire United States birth population based on birth certificate data, including similar regional and racial-ethnic composition. Longitudinal cohort restriction requiring linked records from first trimester prenatal care through infant follow-up care reduced the cohort size to 509,148 pregnancies. However, restriction had minimal effects on cohort characteristics. In the example analysis, high systolic blood pressure was associated with increased risk of preeclampsia among those with chronic hypertension (aRR: 1.26; 95% CI: 1.22, 1.30). Conclusions: This study provides a rigorous and reproducible approach to creating longitudinal, linked maternal-infant cohorts in Epic Cosmos and the analytical findings suggest high data quality and representativeness.

Indexed as

electronic health record dataepidemiologic methodsmedical informaticsneonatologyobstetricsperinatal care

Identifiers

PMID42282186
PMCPMC13252481

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.