Evidence map›Paper›PMID 39939846›Full record

ArticleBMC pregnancy and childbirth2025

Pre-conception clinical risk factors differ between spontaneous and indicated preterm birth in a densely phenotyped EHR cohort.

Jean M Costello, Hannah Takasuka, Jacquelyn Roger, Ophelia Yin, Alice Tang, Tomiko Oskotsky, Marina Sirota, John A Capra

Abstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Lived experience of spontaneous preterm birth following spontaneous preterm labor: the primary caregiver's perspective.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Article
  4. A Compassion-Focused Approach to Support Parents After Preterm Birth.Clinical child and family psychology review · 2025
    Review
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Jean M Costello *Bakar Computational Health Sciences Institute, UCSF, San Francisco, USA.
Hannah Takasuka *Graduate Program in Oral and Craniofacial Sciences, UCSF, San Francisco, USA.
Jacquelyn RogerGraduate Program in Biological and Medical Informatics, UCSF, San Francisco, USA.
Ophelia YinDepartment of Obstetrics, Gynecology & Reproductive Sciences, UCSF, San Francisco, USA.
Alice TangGraduate Program in Bioengineering, UCSF and UC Berkeley, San Francisco and Berkeley, USA.
Tomiko OskotskyBakar Computational Health Sciences Institute, UCSF, San Francisco, USA.
Marina Sirota *Bakar Computational Health Sciences Institute, UCSF, San Francisco, USA. Marina.Sirota@ucsf.edu.
John A Capra *Bakar Computational Health Sciences Institute, UCSF, San Francisco, USA. tony@capralab.org.

Funding

UCSF INTEGRATED DDS-PHD TRAINING PROGRAMT32DE007306 · NIDCR · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Yukiko Nakano · 1996 to 2026
$15.4M
REPRODUCTIVE ENDOCRINOLOGYT32HD007263 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MELLON, SYNTHIA H · 1985 to 2023
$4.1M
NICHD NIH HHS T32 HD007263NIDCR NIH HHS T32 DE007306NIH HHS T32DE007306
6 · The paper itself

Abstract

backgroundPreterm birth (PTB) is the leading cause of infant mortality. Risk for PTB is influenced by multiple biological pathways, many of which are poorly understood. Some PTBs result from medically indicated labor following complications from hypertension and/or diabetes, while many others are spontaneous with unknown causes. Previously, investigation of potential risk factors has been limited by a lack of data on maternal medical history and the difficulty of classifying PTBs as indicated or spontaneous. Here, we leverage electronic health record (EHR) data (patient health information including demographics, diagnoses, and medications) and a supplemental curated pregnancy database to overcome these limitations. Novel associations may provide new insight into the pathophysiology of PTB as well as help identify individuals who would be at risk of PTB.

methodsWe quantified associations between maternal diagnoses and preterm birth both with and without controlling for maternal age and socioeconomic factors within a University of California, San Francisco (UCSF), EHR cohort with 10,643 births (n

resultsThirty diagnoses significantly and robustly (False Discovery Rate (FDR) < 0.05) associated with indicated PTBs compared to term. We discovered known (hypertension, diabetes, and chronic kidney disease) and less established (blood, cardiac, gynecological, and liver diagnoses) associations. Essential hypertension had the most significant association with indicated PTB (adjusted p

conclusionsOur study underscores the limitations of approaches that combine indicated and spontaneous births. When combined, significant associations were almost entirely driven by indicated PTBs, although the spontaneous and indicated groups were of a similar size. Investigating the spontaneous population has the potential to reveal new pathways and understanding of the heterogeneity of PTB.

Indexed as

Electronic Health RecordsPregnancy ComplicationsPremature BirthAdultCohort StudiesFemaleHumansInfant, NewbornPregnancyRisk FactorsSan FranciscoYoung AdultDiagnosis associationsElectronic health recordsIndicated preterm birthSpontaneous preterm birth

Identifiers

PMID39939846
PMCPMC11817080

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Registered trials

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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.