Ari Z Klein, Shriya Kunatharaju, Su Golder, Lisa D Levine, Jane C Figueiredo, Graciela Gonzalez-Hernandez
{"title":"妊娠期COVID-19与妊娠期感染早产之间的关系:使用大规模社交媒体数据的回顾性队列研究","authors":"Ari Z Klein, Shriya Kunatharaju, Su Golder, Lisa D Levine, Jane C Figueiredo, Graciela Gonzalez-Hernandez","doi":"10.2196/66097","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e66097"},"PeriodicalIF":5.8000,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12266298/pdf/","citationCount":"0","resultStr":"{\"title\":\"Association Between COVID-19 During Pregnancy and Preterm Birth by Trimester of Infection: Retrospective Cohort Study Using Large-Scale Social Media Data.\",\"authors\":\"Ari Z Klein, Shriya Kunatharaju, Su Golder, Lisa D Levine, Jane C Figueiredo, Graciela Gonzalez-Hernandez\",\"doi\":\"10.2196/66097\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":16337,\"journal\":{\"name\":\"Journal of Medical Internet Research\",\"volume\":\"27 \",\"pages\":\"e66097\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2025-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12266298/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Medical Internet Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2196/66097\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Internet Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2196/66097","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
摘要
背景:早产,定义为:目的:本研究的目的是利用大规模社交媒体数据中的自我报告来评估COVID-19感染的三个月与早产之间的关系。方法:在这项回顾性队列研究中,我们使用自然语言处理和机器学习,然后进行人工验证,以识别Twitter上的怀孕自我报告,并搜索这些用户收集的公开推文,以查找怀孕期间COVID-19感染的自我报告,以及随后的早产或足月分娩结果。在推特上报告怀孕的用户中,我们还确定了一个1:1年龄匹配的对照组,由预产期在2020年1月1日之前的用户组成,即怀孕期间没有感染COVID-19。我们计算了95% ci的优势比(or),比较了感染COVID-19和未感染COVID-19的妊娠的早产频率,以及感染的时间:妊娠早期(1-13周)、妊娠中期(14-27周)或妊娠晚期(28-36周)。结果:截至2022年8月,我们确定了298名在怀孕期间报告COVID-19感染、早产或足月分娩结果和母亲年龄的Twitter用户:94名(31.5%)患有妊娠早期感染,110名(36.9%)患有妊娠中期感染,95名(31.9%)患有妊娠晚期感染。在这298名使用者中,共有26人(8.8%)报告了早产:8人(8.5%)发生妊娠早期感染,7人(6.4%)发生妊娠中期感染,12人(12.6%)发生妊娠晚期感染。在1:1年龄匹配的对照组中,298名用户中有13名(4.4%)报告早产。总体而言,与未感染COVID-19的孕妇相比,感染COVID-19的孕妇早产的几率显著高于未感染COVID-19的孕妇(OR 2.08, 95% CI 1.06-4.28;P = .046)。特别是,妊娠晚期感染COVID-19的孕妇早产的几率明显更高(OR 3.16, 95% CI 1.36-7.29;P = .007)。妊娠早期感染COVID-19的孕妇早产的几率没有显著升高(OR 2.05, 95% CI 0.78-5.08;P= 0.12)或妊娠中期(or 1.50, 95% CI 0.54-3.82;P=.44)。结论:基于大规模社交媒体数据中的自我报告,我们的研究结果表明,COVID-19感染,特别是在妊娠晚期,与更高的早产几率相关。
Association Between COVID-19 During Pregnancy and Preterm Birth by Trimester of Infection: Retrospective Cohort Study Using Large-Scale Social Media Data.
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.
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.