Does pregnancy complication history improve cardiovascular disease risk prediction? Findings from the HUNT study in Norway.

Autor:	Markovitz AR; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.; Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Boston, MA, USA.; Mathematica Policy Research, 955 Massachusetts Avenue, Cambridge, MA, USA., Stuart JJ; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.; 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; Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Postboks, N-7491 Trondheim, Norway.; Department of Obstetrics and Gynecology, Levanger Hospital, Nord-Trøndelag Hospital Trust, Kirkegata 2, Levanger, Norway., Williams PL; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.; Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA., Rimm EB; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.; Department of Nutrition, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA, USA., Missmer SA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA, USA.; Division of Adolescent and Young Adult Medicine, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, 333 Longwood Ave, Boston, MA, USA.; Department of Obstetrics, Gynecology, and Reproductive Biology, College of Human Medicine, Michigan State University, 400 Monroe Ave. NW, Grand Rapids, MI, USA., Tanz LJ; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.; Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Boston, MA, USA., Haug EB; Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Postboks, N-7491 Trondheim, Norway., Fraser A; Population Health Sciences, Bristol Medical School and MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, UK., Timpka S; Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Boston, MA, USA.; Harvard Medical School, 25 Shattuck St., Boston, MA, USA.; Lund University Diabetes Center, Department of Clinical Sciences, Malmö, Lund University, Jan Waldenströms gata 35, Malmö, Sweden., Klykken B; Department of Medicine, Levanger Hospital, Nord-Trøndelag Hospital Trust, Kirkegata 2, Levanger, Norway., Dalen H; Department of Medicine, Levanger Hospital, Nord-Trøndelag Hospital Trust, Kirkegata 2, Levanger, Norway.; Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Postboks 8905, Trondheim, Norway.; Department of Cardiology, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim, Norway., Romundstad PR; Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Postboks, N-7491 Trondheim, Norway., Rich-Edwards JW; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA.; Division of Women's Health, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Boston, MA, USA.; 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; K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Postboks 8905, Trondheim, Norway.; Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Prinsesse Kristinas gate 3, Trondheim, Norway.
Jazyk:	angličtina
Zdroj:	European heart journal [Eur Heart J] 2019 Apr 07; Vol. 40 (14), pp. 1113-1120.
DOI:	10.1093/eurheartj/ehy863
Abstrakt:	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. (© The Author(s) 2018. Published by Oxford University Press on behalf of the European Society of Cardiology.)
Databáze:	MEDLINE
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