Contact

  • Academic
    jliu99@stanford.edu
    University - Student Department: School of Medicine Position: Graduate, Medicine

Additional Info

  • Mail Code: 9025

All Publications

  • Leveraging electronic health records to identify risk factors for recurrent pregnancy loss across two medical centers: a case-control study. Research square Roger, J., Xie, F., Costello, J., Tang, A., Liu, J., Oskotsky, T., Woldemariam, S., Kosti, I., Le, B., Snyder, M. P., Giudice, L. C., Torgerson, D., Shaw, G. M., Stevenson, D. K., Rajkovic, A., Glymour, M. M., Aghaeepour, N., Cakmak, H., Lathi, R. B., Sirota, M. 2023

    Abstract

    Recurrent pregnancy loss (RPL), defined as 2 or more pregnancy losses, affects 5-6% of ever-pregnant individuals. Approximately half of these cases have no identifiable explanation. To generate hypotheses about RPL etiologies, we implemented a case-control study comparing the history of over 1,600 diagnoses between RPL and live-birth patients, leveraging the University of California San Francisco (UCSF) and Stanford University electronic health record databases. In total, our study included 8,496 RPL (UCSF: 3,840, Stanford: 4,656) and 53,278 Control (UCSF: 17,259, Stanford: 36,019) patients. Menstrual abnormalities and infertility-associated diagnoses were significantly positively associated with RPL in both medical centers. Age-stratified analysis revealed that the majority of RPL-associated diagnoses had higher odds ratios for patients <35 compared with 35+ patients. While Stanford results were sensitive to control for healthcare utilization, UCSF results were stable across analyses with and without utilization. Intersecting significant results between medical centers was an effective filter to identify associations that are robust across center-specific utilization patterns.

    View details for DOI 10.21203/rs.3.rs-2631220/v1

    View details for PubMedID 36993325

    View details for PubMedCentralID PMC10055527

  • LEVERAGING ELECTRONIC HEALTH RECORD DATA TO IDENTIFY PHENOTYPES ASSOCIATED WITH PREGNANCY LOSS MAY LEAD TO IMPROVED UNDERSTANDING OF RECURRENT PREGNANCY LOSS Roger, J., Tang, A., Woldemariam, S., Oskotsky, T., Wen, T., Liu, J., Kosti, I., Le, B., Cakmak, H., Snyder, M., Aghaeepour, N., Shaw, G., Stevenson, D., Giudice, L. C., Glymour, M., Rajkovic, A., Lathi, R., Sirota, M. ELSEVIER SCIENCE INC. 2022: E107

    View details for Web of Science ID 000891804600262