Hypertensive disorders of pregnancy and long-term risk of maternal stroke - a systematic review
Bibliographic record
Abstract
Abstract Hypertensive disorders of pregnancy (HDP) are associated with a long-term risk for cardiovascular disease among parous patients later in life. However, relatively little is known about whether HDP are associated with an increased risk for ischaemic stroke (IS) or haemorrhagic stroke (HS) in later life. This systematic review aimed to synthesize the available literature on the association between HDP and the long-term risk for maternal stroke. PubMed, Web of Science, and CINAHL were searched from inception to December 19, 2022. Studies included were case-control or cohort studies, conducted with human participants, available in English, measuring the exposure of a history of HDP (preeclampsia (PE), gestational hypertension (GH), chronic hypertension (CH), or superimposed preeclampsia) and the outcome of maternal IS or HS. Three reviewers extracted the data and appraised the study quality following the Meta-analyses of Observational Studies in Epidemiology guidelines and using the Newcastle-Ottawa scale. The primary outcome was any undifferentiated stroke (AS) and secondary outcomes included IS and HS. The protocol for this systematic review was registered on PROSPERO (CRD42021254660). 24 studies were included (10,632,808 study participants). HDP were significantly associated with AS (aRR, 1.74; 95% CI, 1.45-2.10). PE was significantly associated with AS (aRR, 1.75; 95% CI, 1.56-1.97), IS (aRR, 1.74; 95% CI, 1.46-2.06), and HS (aRR, 2.77; 95% CI, 2.04-3.75). GH was significantly associated with AS (aRR, 1.23; 95% CI, 1.20-1.26), IS (aRR, 1.35; 95% CI, 1.19-1.53), and HS (aRR, 2.66; 95% CI, 1.02-6.98). CH was associated with IS (aRR, 1.49; 95% CI, 1.01-2.19). In conclusion, exposure to HDP, including PE and GH, seems to be associated with an increased risk for AS and IS among parous patients in later life. Preventive interventions may be warranted for patients who experience HDP to reduce their long-term risk for stroke. Key messages • Hypertensive disorders of pregnancy appear to be associated with an increased risk of maternal stroke in later life. • The strength of association between exposures and outcomes varies by hypertensive disorder of pregnancy subtype and stroke subtype.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".