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209. 222 Association between aspirin use during pregnancy and cardiovascular risk factors 2-7 years after delivery

Author

Theilen, Lauren, primary, Greenland, Philip, additional, Varagic, Jasmina, additional, Catov, Janet, additional, Shanks, Anthony L., additional, Thorsten, Vanessa R., additional, Parker, Corette, additional, McNeil, Rebecca B., additional, Mercer, Brian M., additional, Hoffman, Matthew, additional, Wapner, Ronald J., additional, Haas, David M., additional, Simhan, Hyagriv, additional, Grobman, William A., additional, Chung, Judith H., additional, Levine, Lisa D., additional, Merz, Noel Bairey, additional, Saade, George R., additional, and Silver, Bob M., additional

Published
2021
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215. Leaders in the Successful Pursuit of Nontraditional Careers in Medicine

Author

Baugh, Christopher W., primary, Bloomberg, Mark A., additional, Borden, Spencer, additional, Chandler, Maria Young, additional, Fastow, Joseph S., additional, Gertler, Jonathan P., additional, Kalish, Richard, additional, Levine, Lisa Bard, additional, Ober, N. Stephen, additional, and Slavin, Peter L., additional

Published
2011
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216. Using Twitter Data for Cohort Studies of Drug Safety in Pregnancy: Proof-of-concept With ß-Blockers.

Author

Klein, Ari Z., O'Connor, Karen, Levine, Lisa D., and Gonzalez-Hernandez, Graciela

Subjects
PREGNANCY, NEONATAL intensive care units, MOBILE apps, MEDICAL personnel, MEDICAL care
Abstract

Background: Despite the fact that medication is taken during more than 90% of pregnancies, the fetal risk for most medications is unknown, and the majority of medications have no data regarding safety in pregnancy. Objective: Using ß-blockers as a proof-of-concept, the primary objective of this study was to assess the utility of Twitter data for a cohort study design--in particular, whether we could identify (1) Twitter users who have posted tweets reporting that they took medication during pregnancy and (2) their associated pregnancy outcomes. Methods: We searched for mentions of ß-blockers in 2.75 billion tweets posted by 415,690 users who announced their pregnancy on Twitter. We manually reviewed the matching tweets to first determine if the user actually took the ß-blocker mentioned in the tweet. Then, to help determine if the ß-blocker was taken during pregnancy, we used the time stamp of the tweet reporting intake and drew upon an automated natural language processing (NLP) tool that estimates the date of the user's prenatal time period. For users who posted tweets indicating that they took or may have taken the ß-blocker during pregnancy, we drew upon additional NLP tools to help identify tweets that report their pregnancy outcomes. Adverse pregnancy outcomes included miscarriage, stillbirth, birth defects, preterm birth (<37 weeks gestation), low birth weight (<5 pounds and 8 ounces at delivery), and neonatal intensive care unit (NICU) admission. Normal pregnancy outcomes included gestational age =37 weeks and birth weight =5 pounds and 8 ounces. Results: We retrieved 5114 tweets, posted by 2339 users, that mention a ß-blocker, and manually identified 2332 (45.6%) tweets, posted by 1195 (51.1%) of the users, that self-report taking the ß-blocker. We were able to estimate the date of the prenatal time period for 356 pregnancies among 334 (27.9%) of these 1195 users. Among these 356 pregnancies, we identified 257 (72.2%) during which the ß-blocker was or may have been taken. We manually verified an adverse pregnancy outcome--preterm birth, NICU admission, low birth weight, birth defects, or miscarriage--for 38 (14.8%) of these 257 pregnancies. We manually verified a gestational age =37 weeks for 198 (90.4%) and a birth weight =5 pounds and 8 ounces for 50 (22.8%) of the 219 pregnancies for which we did not identify an adverse pregnancy outcome. Conclusions: Our ability to detect pregnancy outcomes for Twitter users who posted tweets reporting that they took or may have taken a ß-blocker during pregnancy suggests that Twitter can be a complementary resource for cohort studies of drug safety in pregnancy. [ABSTRACT FROM AUTHOR]

Published
2022
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217. Screening Echocardiogram in High-Risk Women with Class III Obesity to Predict the Risk of Preeclampsia.

Author

Hopkins, Maeve K., Levine, Lisa D., Koelper, Nathanael C., and Durnwald, Celeste

Subjects
*OBESITY complications, *RISK factors of preeclampsia, *ECHOCARDIOGRAPHY, *HYPERTENSION, *CARDIOVASCULAR diseases in pregnancy, *CONFIDENCE intervals, *MULTIPLE regression analysis, *MEDICAL screening, *WOMEN, *RETROSPECTIVE studies, *RISK assessment, *DESCRIPTIVE statistics, *ODDS ratio, *LONGITUDINAL method, *COMORBIDITY
Abstract

Objective  Women with obesity and other comorbidities such as hypertension and diabetes are at an increased risk of preeclampsia and perinatal morbidity. This study evaluates whether screening echocardiogram can identify women with obesity at a higher risk of preeclampsia. Methods  We conducted a retrospective cohort study of women with class III obesity (body mass index [BMI] ≥40 kg/m 2) and one or more medical comorbidities associated with an increased risk of preeclampsia (such as diabetes, hypertension, and rheumatologic disease) undergoing screening echocardiogram. Abnormal findings were defined as the presence of one or more of the following: diastolic dysfunction, ejection fraction of ≤45%, or cardiac chamber enlargement or hypertrophy. Multivariable logistic regression was used to estimate the odds ratio (OR) of gestational hypertension/mild preeclampsia, severe preeclampsia, and any preterm delivery <37 weeks associated with abnormal echocardiographic findings when controlling for potential confounders. Results  Of 267 eligible women, 174 (64%) underwent screening echocardiograms. Sixty-nine women (40%) had abnormal echocardiograms. Maternal clinical characteristics were similar between women with normal echocardiographic findings and women with abnormal findings. Women with abnormal echocardiograms were more likely to have chronic hypertension (78 vs. 62%, p  = 0.04) and a history of preeclampsia (27 vs. 10%, p  = 0.02). After controlling for confounders, women with abnormal echocardiogram were at an increased risk of hypertensive disorders of pregnancy, OR 6.80 (95% confidence interval [CI] 3.32–13.93, p  = 0.01), and in particular severe preeclampsia, OR 8.77 (95% CI 3.90–19.74, p  = 0.01). Conclusion  Among pregnant women with class III obesity and medical comorbidities, screening echocardiogram may help identify a subset of women at the highest risk of developing preeclampsia. Key Points Women with obesity and comorbid conditions are at a high risk of abnormal echocardiogram. Women with obesity, medical comorbid conditions, and abnormal echo are at a high risk of preeclampsia. Screening echocardiogram can help identify obese women at the highest risk of severe preeclampsia. [ABSTRACT FROM AUTHOR]

Published
2022
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235. Syncytiotrophoblast extracellular microvesicle profiles in maternal circulation for noninvasive diagnosis of preeclampsia

Author

Levine, Lisa, primary, Habertheuer, Andreas, additional, Ram, Chirag, additional, Korutla, Laxminarayana, additional, Schwartz, Nadav, additional, Hu, Robert W., additional, Reddy, Sanjana, additional, Freas, Andrew, additional, Zielinski, Patrick D., additional, Harmon, Joey, additional, Molugu, Sudheer Kumar, additional, Parry, Samuel, additional, and Vallabhajosyula, Prashanth, additional

Published
2020
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