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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 and Timpka, Simon LU , et al. (2019) In European Heart Journal 40(14). p.1113-1120
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... (More)

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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published
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European Heart Journal
volume
40
issue
14
pages
1113 - 1120
publisher
Oxford University Press
external identifiers
  • scopus:85064163006
ISSN
1522-9645
DOI
10.1093/eurheartj/ehy863
language
English
LU publication?
yes
id
012a4050-c682-4d23-8ec6-88c45da46131
date added to LUP
2019-01-11 07:18:40
date last changed
2019-10-23 06:06:27
@article{012a4050-c682-4d23-8ec6-88c45da46131,
  abstract     = {<p>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).</p><p>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).</p><p>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.</p>},
  author       = {Markovitz, Amanda R and Stuart, Jennifer J and Horn, Julie and Williams, Paige L and Rimm, Eric B and Missmer, Stacey A and Tanz, Lauren J and Haug, Eirin B and Fraser, Abigail and Timpka, Simon and Klykken, Bjørnar and Dalen, Håvard and Romundstad, Pål R and Rich-Edwards, Janet W and Åsvold, Bjørn Olav},
  issn         = {1522-9645},
  language     = {eng},
  number       = {14},
  pages        = {1113--1120},
  publisher    = {Oxford University Press},
  series       = {European Heart Journal},
  title        = {Does pregnancy complication history improve cardiovascular disease risk prediction? : Findings from the HUNT study in Norway},
  url          = {http://dx.doi.org/10.1093/eurheartj/ehy863},
  volume       = {40},
  year         = {2019},
}