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Record W7035858982

Association between cardiometabolic pregnancy complications and cardiovascular diseases

2017· dissertation· en· W7035858982 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2017
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Systems and Practices
Canadian institutionsnot available
FundersCanadian Vascular NetworkHeart and Stroke Foundation of Canada
KeywordsPregnancyGestational diabetesDiseaseDiabetes mellitusEndothelial dysfunctionVascular diseaseAcute coronary syndromeNatural historyProspective cohort study
DOInot available

Abstract

fetched live from OpenAlex

Background: Cardiometabolic pregnancy complications including hypertensive disorders of pregnancy (HDP) and gestational diabetes (GDM) each double the risk of cardiovascular disease (CVD) later in life. Two hypotheses have been posited to explain this increase in risk: shared burden of atherosclerotic risk factors, and persistent vascular impairment after the affected pregnancy. Thus, the aim of this work is to explore the biological mechanism underlying the association between pregnancy complications and CVD as well as the clinical outcomes at the time of an ischemic event. Methods: 1. Through a systematic review and meta-analysis, we summarized and updated evidence for sustained vascular dysfunction at least three months after HDP, as measured by imaging modalities and serum biomarkers. We pooled results of modalities reported in more than three studies using a random effects model. 2. Using data from the GENESIS-PRAXY prospective cohort, we studied 251 parous women (≤ 55 years old) hospitalized with an acute coronary syndrome (ACS) in whom detailed medical and obstetric history as well as biological data were available. We compared clinical presentation, traditional risk factors and biomarkers of endothelial dysfunction at ACS diagnosis in women with versus without a prior history of complicated pregnancy (HDP and/or GDM). Major adverse cardiac events (MACE) were captured at 12 months.Results: 1. By summarizing more than 70 studies, we found evidence of sustained vascular dysfunction after pregnancies complicated with HDP. There was evidence of vascular dysfunction in women post HDP compared to women with prior normal pregnancy when measured by carotid-femoral pulse-wave velocity (0.64m/s [0.17 to 1.11]), carotid intima-media thickness (0.025mm [0.004 to 0.045]) and augmentation index (5.48% [1.58 to 9.37]), as well as mean levels of soluble fms-like tyrosine kinase (6.12pg/ml [1.91 to 10.33]). Vascular dysfunction was more pronounced in younger women (< 40 years) and closer to the index pregnancy. 2. At the time of the ACS, women with previous pregnancy complications were younger (47.4 ± 6.2 vs. 49.1 ± 5.6 years, p=0.002), and had a greater burden of traditional atherosclerotic risk factors compared with women with prior normal pregnancy. Of note, women with prior preeclampsia were more likely to have chronic hypertension and to present with ST-elevation myocardial infarction as compared to women with prior unaffected pregnancy (adjusted OR 2.76 [1.04, 7.29]). At 12 months, there was a trend for increased risk of MACE in women with prior pregnancy complications, mostly driven by an increased risk of recurrent ACS in women with prior preeclampsia.Conclusion: Pooled data from studies evaluating vascular imaging suggest that some vascular dysfunction persists in women with prior HDP as compared to women with prior normal pregnancy. Women with prior pregnancy complications also present with ACS at a younger age, and with a high burden of atherosclerotic risk factors. In particular, preeclampsia was associated with more severe ACS at presentation and a higher likelihood of recurrence. Further studies are needed to understand the precise trajectory between cardiometabolic pregnancy complications and development of CVD, and the development and testing of tailored interventions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.242
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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