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Does pregnancy complication history improve cardiovascular disease risk prediction? Findings from the HUNT study in Norway.
Markovitz, Amanda R; Stuart, Jennifer J; Horn, Julie; Williams, Paige L; Rimm, Eric B; Missmer, Stacey A; Tanz, Lauren J; Haug, Eirin B; Fraser, Abigail; Timpka, Simon; Klykken, Bjørnar; Dalen, Håvard; Romundstad, Pål R; Rich-Edwards, Janet W; Åsvold, Bjørn Olav.
Afiliación
  • Markovitz AR; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.
  • Stuart JJ; Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Boston, MA, USA.
  • Horn J; Mathematica Policy Research, 955 Massachusetts Avenue, Cambridge, MA, USA.
  • Williams PL; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.
  • Rimm EB; Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Boston, MA, USA.
  • Missmer SA; Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Postboks, N-7491 Trondheim, Norway.
  • Tanz LJ; Department of Obstetrics and Gynecology, Levanger Hospital, Nord-Trøndelag Hospital Trust, Kirkegata 2, Levanger, Norway.
  • Haug EB; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.
  • Fraser A; Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.
  • Timpka S; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.
  • Klykken B; Department of Nutrition, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.
  • Dalen H; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA, USA.
  • Romundstad PR; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.
  • Rich-Edwards JW; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA, USA.
  • Åsvold BO; Division of Adolescent and Young Adult Medicine, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, 333 Longwood Ave, Boston, MA, USA.
Eur Heart J ; 40(14): 1113-1120, 2019 04 07.
Article en En | MEDLINE | ID: mdl-30596987
ABSTRACT

AIM:

To evaluate whether history of pregnancy complications [pre-eclampsia, gestational hypertension, preterm delivery, or small for gestational age (SGA)] improves risk prediction for cardiovascular disease (CVD). METHODS AND

RESULTS:

This population-based, prospective cohort study linked data from the HUNT Study, Medical Birth Registry of Norway, validated hospital records, and Norwegian Cause of Death Registry. Using an established CVD risk prediction model (NORRISK 2), we predicted 10-year risk of CVD (non-fatal myocardial infarction, fatal coronary heart disease, and non-fatal or fatal stroke) based on established risk factors (age, systolic blood pressure, total and HDL-cholesterol, smoking, anti-hypertensives, and family history of myocardial infarction). We evaluated whether adding pregnancy complication history improved model fit, calibration, discrimination, and reclassification. Among 18 231 women who were parous, ≥40 years of age, and CVD-free at start of follow-up, 39% had any pregnancy complication history and 5% experienced a CVD event during a median follow-up of 8.2 years. While pre-eclampsia and SGA were associated with CVD in unadjusted models (HR 1.96, 95% CI 1.44-2.65 for pre-eclampsia and HR 1.46, 95% CI 1.18-1.81 for SGA), only pre-eclampsia remained associated with CVD after adjusting for established risk factors (HR 1.60, 95% CI 1.16-2.17). Adding pregnancy complication history to the established prediction model led to small improvements in discrimination (C-index difference 0.004, 95% CI 0.002-0.006) and reclassification (net reclassification improvement 0.02, 95% CI 0.002-0.05).

CONCLUSION:

Pre-eclampsia independently predicted CVD after controlling for established risk factors; however, adding pre-eclampsia, gestational hypertension, preterm delivery, and SGA made only small improvements to CVD prediction among this representative sample of parous Norwegian women.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Preeclampsia / Medición de Riesgo / Enfermedad Coronaria / Accidente Cerebrovascular / Infarto del Miocardio Tipo de estudio: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Middle aged / Pregnancy País/Región como asunto: Europa Idioma: En Revista: Eur Heart J Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Preeclampsia / Medición de Riesgo / Enfermedad Coronaria / Accidente Cerebrovascular / Infarto del Miocardio Tipo de estudio: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Middle aged / Pregnancy País/Región como asunto: Europa Idioma: En Revista: Eur Heart J Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos