Maternal cardiovascular disease after twin pregnancies complicated by hypertensive disorders of pregnancy: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: People whose singleton pregnancy is affected by hypertensive disorders of pregnancy (HDP) are at risk of future cardiovascular disease. It is unclear, however, whether this association can be extrapolated to twin pregnancies. We aimed to compare the association between HDP and future cardiovascular disease after twin and singleton pregnancies. METHODS: We conducted a population-based retrospective cohort study that included nulliparous people in Ontario, Canada, 1992-2017. We compared the future risk of cardiovascular disease among pregnant people from the following 4 groups: those who delivered a singleton without HDP (referent) and with HDP, and those who delivered twins either with or without HDP. RESULTS: The populations of the 4 groups were as follows: 1 431 651 pregnant people in the singleton birth without HDP group; 98 631 singleton birth with HDP; 21 046 twin birth without HDP; and 4283 twin birth with HDP. The median duration of follow-up was 13 (interquartile range 7-20) years. The incidence rate of cardiovascular disease was lowest among those with a singleton or twin birth without HDP (0.72 and 0.74 per 1000 person-years, respectively). Compared with people with a singleton birth without HDP, the risk of cardiovascular disease was highest among those with a singleton birth and HDP (1.47 per 1000 person-years; adjusted hazard ratio [HR] 1.81 [95% confidence interval (CI) 1.72-1.90]), followed by people with a twin pregnancy and HDP (1.07 per 1000 person-years; adjusted HR 1.36 [95% CI 1.04-1.77]). The risk of the primary outcome after a twin pregnancy with HDP was lower than that after a singleton pregnancy with HDP (adjusted HR 0.74 [95% CI 0.57-0.97]), when compared directly. INTERPRETATION: In a twin pregnancy, HDP are weaker risk factors for postpartum cardiovascular disease than in a singleton pregnancy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".