Leveraging health records to identify diagnoses associated with recurrent pregnancy loss across two medical centers

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. In this study, we aim to identify diagnoses associated with RPL and generate hypotheses about RPL etiology utilizing electronic health record (EHR) data. 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 EHR databases. In total, our study includes 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 are significantly positively associated with RPL in both medical centers. Age-stratified analysis revealed that the majority of RPL-associated diagnoses have higher odds ratios for patients <35 years compared with 35+ years patients. While Stanford results are sensitive to control for healthcare utilization, UCSF results are stable across analyses with and without utilization.

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Publication Details

Journal
iScience
Published
2026-01-07
DOI
https://doi.org/10.1016/j.isci.2026.114633
Primary Topic
Reproductive System and Pregnancy
Type
article
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article

Leveraging health records to identify diagnoses associated with recurrent pregnancy loss across two medical centers

Jacquelyn Roger, J Costello, Ruth B. Lathi, Aleksandar Rajkovic et al.
iScience
Reproductive System and Pregnancy
article

Leveraging health records to identify diagnoses associated with recurrent pregnancy loss across two medical centers

Jacquelyn Roger, J Costello, Ruth B. Lathi, Aleksandar Rajkovic, Hakan Cakmak, Michael Snyder, Brian L. Le, Linda C. Giudice, Tomiko Oskotsky, Nima Aghaeepour, Gary M. Shaw, Jay Liu, Idit Kosti, Sarah Woldemariam, Marina Sirota, David K. Stevenson, Feng Xie, Dara Torgerson, Alice Tang, M.Maria Glymour
article en

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. In this study, we aim to identify diagnoses associated with RPL and generate hypotheses about RPL etiology utilizing electronic health record (EHR) data. 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 EHR databases. In total, our study includes 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 are significantly positively associated with RPL in both medical centers. Age-stratified analysis revealed that the majority of RPL-associated diagnoses have higher odds ratios for patients <35 years compared with 35+ years patients. While Stanford results are sensitive to control for healthcare utilization, UCSF results are stable across analyses with and without utilization.

iScienceVol. 29(2)
University of California, San Francisco (US), Stanford Medicine (US), Stanford University (US)
Good health and well-being
Openalex Percentile: Top 96%
Reproductive System and Pregnancy
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