Cardiovascular Disease-Related Morbidity and Mortality in Women With a History of Pregnancy Complications
Bibliographic record
Abstract
BACKGROUND: Women with a history of certain pregnancy complications are at higher risk for cardiovascular (CVD) disease. However, most clinical guidelines only recommend postpartum follow-up of those with a history of preeclampsia, gestational diabetes mellitus, or preterm birth. This systematic review was undertaken to determine if there is an association between a broader array of pregnancy complications and the future risk of CVD. METHODS: We systematically searched PubMed, MEDLINE and EMBASE (via Ovid), CINAHL, and the Cochrane Library from inception to September 22, 2017, for observational studies of the association between the hypertensive disorders of pregnancy, placental abruption, preterm birth, gestational diabetes mellitus, low birth weight, small-for-gestational-age birth, stillbirth, and miscarriage and subsequent CVD. Likelihood ratio meta-analyses were performed to generate pooled odds ratios (OR) and 95% intrinsic confidence intervals (ICI). RESULTS: Our systematic review included 84 studies (28 993 438 patients). Sample sizes varied from 250 to 2 000 000, with a median follow-up of 7.5 years postpartum. The risk of CVD was highest in women with gestational hypertension (OR 1.7; 95% ICI, 1.3-2.2), preeclampsia (OR 2.7; 95% ICI, 2.5-3.0), placental abruption (OR 1.8; 95% ICI, 1.4-2.3), preterm birth (OR 1.6; 95% ICI, 1.4-1.9), gestational diabetes mellitus (OR 1.7; 95% ICI, 1.1-2.5), and stillbirth (OR 1.5; 95% ICI, 1.1-2.1). A consistent trend was seen for low birth weight and small-for-gestational-age birth weight but not for miscarriage. CONCLUSIONS: Women with a broader array of pregnancy complications, including placental abruption and stillbirth, are at increased risk of future CVD. The findings support the need for assessment and risk factor management beyond the postpartum period.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".