Severe Maternal Morbidity and Long-Term Risk of Cardiovascular Hospitalization
Bibliographic record
Abstract
BACKGROUND: Severe maternal morbidity is rising, yet the association with cardiovascular disease is not clear. We examined the risk of cardiovascular hospitalization up to 3 decades after having a pregnancy complicated by severe maternal morbidity. METHODS: We analyzed a longitudinal cohort of 1 336 846 women who were pregnant between 1989 and 2019 in Quebec, Canada. The main exposure measure was severe maternal morbidity in any pregnancy, including severe preeclampsia, acute renal failure, sepsis, and other life-threatening conditions. Using time-varying Cox regression models, we compared the adjusted risk of hospitalization for cardiovascular disease up to 3 decades after pregnancy for women with severe maternal morbidity relative to women without severe morbidity. RESULTS: Five percent of women had severe maternal morbidity. Overall, there were 68 287 cardiovascular hospitalizations during 21 725 672 person-years of follow-up in the cohort. Compared with no morbidity, women with any severe morbidity had a greater risk of cardiovascular hospitalization (hazard ratio [HR], 1.77 [95% CI, 1.72-1.82]). The association was the greatest within the first year of delivery (HR, 4.42 [95% CI, 3.77-5.19]) but persisted beyond 15 years (HR, 1.44 [95% CI, 1.37-1.51]). Having a cardiac complication (HR, 5.37 [95% CI, 4.65-6.20]), cerebrovascular accident (HR, 3.82 [95% CI, 2.94-4.96]), or acute renal failure (HR, 2.60 [95% CI, 2.15-3.14]) during pregnancy was strongly associated with future cardiovascular hospitalization. CONCLUSIONS: Women with severe maternal morbidity have a greater risk of cardiovascular disease after pregnancy, both in the short and long term. These women may benefit from active surveillance for cardiovascular disease.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".