Hypertensive disorders of pregnancy and long‐term cardiovascular health: <scp>FIGO</scp> Best Practice Advice
Bibliographic record
Abstract
Hypertensive disorders of pregnancy (HDP) are the most common causes of maternal and perinatal morbidity and mortality. They are responsible for 16% of maternal deaths in high-income countries and approximately 25% in low- and middle-income countries. The impact of HDP can be lifelong as they are a recognized risk factor for future cardiovascular disease. During pregnancy, the cardiovascular system undergoes significant adaptive changes that ensure adequate uteroplacental blood flow and exchange of oxygen and nutrients to nurture and accommodate the developing fetus. Failure to achieve normal cardiovascular adaptation is associated with the development of HDP. Hemodynamic alterations in women with a history of HDP can persist for years and predispose to long-term cardiovascular morbidity and mortality. Therefore, pregnancy and the postpartum period are an opportunity to identify women with underlying, often unrecognized, cardiovascular risk factors. It is important to develop strategies with lifestyle and therapeutic interventions to reduce the risk of future cardiovascular disease in those who have a history of HDP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.087 | 0.031 |
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".