Development and Validation of a Predictive Model for Maternal Cardiovascular Morbidity Events in Patients With Hypertensive Disorders of Pregnancy
Among individuals with HDP, our multilabel neural network model predicted CV events at delivery admission with good classification and events within 1 year of delivery with fair classification.
Authors
- Jerome J. Federspiel (ORCID: https://orcid.org/0000-0003-0321-6280)
- Kim Boggess
- Svati H. Shah (ORCID: https://orcid.org/0000-0002-3495-2830)
- Quinn Lanners (ORCID: https://orcid.org/0000-0001-7401-9239)
- Matthew Engelhard (ORCID: https://orcid.org/0000-0003-4112-9639)
- Vijay Krishnamoorthy (ORCID: https://orcid.org/0000-0003-4153-2348)
- Marie‐Louise Meng (ORCID: https://orcid.org/0000-0001-8089-3993)
- Johanna Quist‐Nelson (ORCID: https://orcid.org/0000-0003-3390-5239)
- Ashraf S. Habib (ORCID: https://orcid.org/0000-0002-6980-1856)
- Michael Pencina (ORCID: https://orcid.org/0000-0002-1968-2641)
- Matthew Fuller (ORCID: https://orcid.org/0000-0001-9066-5409)
- Yuqi Li (ORCID: https://orcid.org/0000-0001-9298-1990)
Institutions
- University of North Carolina at Chapel Hill (US)
- Duke University (US)
- Clinical Research Institute (US)
Publication Details
- Journal
- Anesthesia & Analgesia
- Published
- 2024-11-06
- DOI
- https://doi.org/10.1213/ane.0000000000007278
- Primary Topic
- Cardiovascular Issues in Pregnancy
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- National Center for Advancing Translational Sciences