Prediction of metabolic syndrome following a first pregnancy.

Journal: American journal of obstetrics and gynecology
PMID: 38527600

Abstract

BACKGROUND: The prevalence of metabolic syndrome is rapidly increasing in the United States. We hypothesized that prediction models using data obtained during pregnancy can accurately predict the future development of metabolic syndrome.

Authors

  • Tetsuya Kawakita
    Department of Obstetrics and Gynecology, Eastern Virginia Medical School, Norfolk, VA. Electronic address: Tetsuya.x.kawakita@gmail.com.
  • Philip Greenland
    Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; Department of Medicine (Cardiology), Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA. Electronic address: p-greenland@northwestern.edu.
  • Victoria L Pemberton
    Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
  • William A Grobman
    Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH.
  • Robert M Silver
    Department of Obstetrics and Gynecology, University of Utah, Salt Lake City, UT.
  • C Noel Bairey Merz
  • Rebecca B McNeil
    RTI International, Durham, NC.
  • David M Haas
    Department of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, IN.
  • Uma M Reddy
    Department of Obstetrics and Gynecology, Columbia University, New York, NY.
  • Hyagriv Simhan
    Department of Obstetrics, Gynecology, and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA.
  • George R Saade
    Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, The University of Texas Medical Branch at Galveston, Galveston, Texas.

Keywords

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