Severe maternal morbidity and risk of cardiovascular disease: Recent advances
Bibliographic record
Abstract
Pregnancy complications including severe maternal morbidity have been linked with an increased risk of cardiovascular disease, and provide opportunities to identify women who would benefit from prevention. Severe maternal morbidity comprises life-endangering complications around the time of pregnancy and delivery. Literature on the relationship between severe maternal morbidity and cardiovascular disease is increasing at a rapid pace. Studies have shown that severe preeclampsia or eclampsia and severe hemorrhage are associated with cardiovascular disease later in life. Proposed pathways include endothelial damage, hypercoagulability, and impaired cardiac function that are induced or exacerbated by severe pregnancy complications that elevate cardiovascular risks. However, less is known about other types of severe maternal morbidity that may influence the risk of cardiovascular disease. Other research gaps include a need to better understand the pathways and mechanisms linking severe maternal morbidity with cardiovascular disease, the potential for cardiovascular recovery after severe cardiovascular events during pregnancy, and disparities in the occurrence of cardiovascular disease after severe maternal morbidity.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".