Evidence map›Paper›PMID 40632790›Full record

ArticleJournal of medical Internet research2025

Association Between COVID-19 During Pregnancy and Preterm Birth by Trimester of Infection: Retrospective Cohort Study Using Large-Scale Social Media Data.

Ari Z Klein, Shriya Kunatharaju, Su Golder, Lisa D Levine, Jane C Figueiredo, Graciela Gonzalez-Hernandez

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Ari Z KleinDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID http://orcid.org/0000-0002-8281-3464
Shriya KunatharajuDepartment of Genetics, University of Pennsylvania, Philadelphia, PA, United States.ORCID http://orcid.org/0000-0001-6042-1745
Su GolderDepartment of Health Sciences, University of York, York, United Kingdom.ORCID http://orcid.org/0000-0002-8987-5211
Lisa D LevineDepartment of Obstetrics and Gynecology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID http://orcid.org/0000-0002-6811-7980
Jane C FigueiredoDepartment of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID http://orcid.org/0000-0001-8040-3341
Graciela Gonzalez-HernandezDepartment of Computational Biomedicine, Cedars-Sinai Medical Center, Pacific Design Center, Ste. G549F, 700 N. San Vicente Blvd., West Hollywood, CA, 90069, United States, 1 310-423-3521.ORCID http://orcid.org/0000-0002-6416-9556

Funding

Social Media Mining for PharmacovigilanceR01LM011176 · NLM · UNIVERSITY OF PENNSYLVANIA · PI GONZALEZ HERNANDEZ, GRACIELA, SHEN, LI · 2012 to 2021
$4.5M
AI Methods for Large Scale Epidemiological Studies using Patient Reports of Medication Adherence and TolerabilityR01LM014731 · NLM · CEDARS-SINAI MEDICAL CENTER · PI GONZALEZ HERNANDEZ, GRACIELA, SHEN, LI · 2025 to 2025
$3.5M
Enriching SARS-CoV-2 sequence data in public repositories with information extracted from full text articlesR01AI164481 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI GONZALEZ HERNANDEZ, GRACIELA, SCOTCH, MATTHEW · 2021 to 2023
$1.9M
NIAID NIH HHS R01 AI164481NLM NIH HHS R01 LM011176NLM NIH HHS R01 LM014731
6 · The paper itself

Abstract

Background: Preterm birth, defined as birth at <37 weeks of gestation, is the leading cause of neonatal death globally and the second leading cause of infant mortality in the United States. There is mounting evidence that COVID-19 infection during pregnancy is associated with an increased risk of preterm birth; however, data remain limited by trimester of infection. The ability to study COVID-19 infection during the earlier stages of pregnancy has been limited by available sources of data. Objective: The objective of this study was to use self-reports in large-scale social media data to assess the association between the trimester of COVID-19 infection and preterm birth. Methods: In this retrospective cohort study, we used natural language processing and machine learning, followed by manual validation, to identify self-reports of pregnancy on Twitter and to search these users' collection of publicly available tweets for self-reports of COVID-19 infection during pregnancy and, subsequently, a preterm birth or term birth outcome. Among the users who reported their pregnancy on Twitter, we also identified a 1:1 age-matched control group, consisting of users with a due date before January 1, 2020-that is, without COVID-19 infection during pregnancy. We calculated the odds ratios (ORs) with 95% CIs to compare the frequency of preterm birth for pregnancies with and without COVID-19 infection and by the timing of infection: first trimester (1-13 weeks), second trimester (14-27 weeks), or third trimester (28-36 weeks). Results: Through August 2022, we identified 298 Twitter users who reported COVID-19 infection during pregnancy, a preterm birth or term birth outcome, and maternal age: 94 (31.5%) with first-trimester infection, 110 (36.9%) with second-trimester infection, and 95 (31.9%) with third-trimester infection. In total, 26 (8.8%) of these 298 users reported preterm birth: 8 (8.5%) with first-trimester infection, 7 (6.4%) with second-trimester infection, and 12 (12.6%) with third-trimester infection. In the 1:1 age-matched control group, 13 (4.4%) of the 298 users reported preterm birth. Overall, the odds of preterm birth were significantly higher for pregnancies with COVID-19 infection compared to those without (OR 2.08, 95% CI 1.06-4.28; P=.046). In particular, the odds of preterm birth were significantly higher for pregnancies with COVID-19 infection during the third trimester (OR 3.16, 95% CI 1.36-7.29; P=.007). The odds of preterm birth were not significantly higher for pregnancies with COVID-19 infection during the first trimester (OR 2.05, 95% CI 0.78-5.08; P=.12) or second trimester (OR 1.50, 95% CI 0.54-3.82; P=.44) compared to those without infection. Conclusions: Based on self-reports in large-scale social media data, the results of our study suggest that COVID-19 infection particularly during the third trimester is associated with higher odds of preterm birth.

Indexed as

COVID-19Pregnancy Complications, InfectiousPregnancy TrimestersPremature BirthSocial MediaAdultFemaleHumansInfant, NewbornPregnancyRetrospective StudiesSARS-CoV-2COVID-19epidemiologymachine learningnatural language processingpregnancypreterm birthsocial media

Identifiers

PMID40632790
PMCPMC12266298

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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.