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American Heart Association

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Final ID: Su2008

Leveraging Large Language Models to Extract Parity from the Electronic Health Record and Reveal Hidden Cardiovascular Risk Factors: A Retrospective Study of Takotsubo Cardiomyopathy

Abstract Body (Do not enter title and authors here): Background: Takotsubo cardiomyopathy (TTCM) is a form of heart failure first described in the 1990s that was believed to be triggered by significant emotional events or stressors - giving it the moniker “broken heart syndrome”. It is now known that both emotional and physiological stressors can induce TTCM in at-risk individuals. Incidence of TTCM is skewed with 80-90% of cases occurring in females over age 50. One small cohort-based study reported an association between parity and risk of TTCM.
Hypothesis and Purpose: We propose that parity is a risk factor for TTCM that can be quantified using a data science approach using real world data (RWD) to evaluate long-term biological impact of parity on cardiovascular health. To evaluate the association, we propose to develop a novel methodology to replicably extract parity information from the structured and unstructured data in the electronic health record (EHR).
Study Design and Methods: Analysis was conducted using an access-limited, privacy-preserving analytic platform hosting >7.3 million unique records of clinical encounters at a multistate integrated health system. The study cohort was restricted to data from individuals 50-80 years old with ≥1 electrocardiogram in the clinical record. Parity data was determined for 99.8% of records using a replicable, novel method to capture structured and unstructured data. Association between TTCM and parity was evaluated in the cohort.
Results: Parity information for 122,769 females was extracted from clinical record data. There were no demographic differences observed in the parity cohort. We observed a 10-20% increased TTCM risk (Figure) among females with nonzero parity values compared to nulliparous controls (n=14,081).To validate our methodology for extracting and analyzing parity data in relation to disease risk, we leveraged the established inverse association between parity and ovarian cancer as a proof-of-concept, which was confirmed in our analysis.
Conclusion: Our findings suggest that women with higher parity are at greater risk of developing TTCM. This finding points to potential pregnancy-related contributions to the significant sex-bias in prevalence of TTCM.
  • Natterson-horowitz, Barbara  ( University of California Los Angeles , Los Angeles , California , United States )
  • Alger, Heather  ( Anumana, Inc , Cambridge , Massachusetts , United States )
  • Milan, Christopher  ( University of California Los Angeles , Los Angeles , California , United States )
  • Niesen, Michiel  ( nference, Inc , Cambridge , Massachusetts , United States )
  • Author Disclosures:
    Barbara Natterson-Horowitz: DO NOT have relevant financial relationships | Heather Alger: DO have relevant financial relationships ; Employee:Anumana, Inc:Active (exists now) ; Consultant:American Heart Association:Active (exists now) ; Employee:nference, Inc:Past (completed) | Christopher Milan: No Answer | Michiel Niesen: DO have relevant financial relationships ; Employee:nference, inc.:Past (completed)
Meeting Info:

Scientific Sessions 2025

2025

New Orleans, Louisiana

Session Info:
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