Impact of the New American Hypertension Guidelines on the Prevalence of Postpartum Hypertension
Bibliographic record
Abstract
Cardiovascular disease (CVD) is the leading cause of death and disability among women, with more than half occurring in individuals with hypertension. New blood pressure criteria for the diagnosis of hypertension from the American College of Cardiology/American Heart Association recognize that there is no specific blood pressure threshold that is associated with vascular disease. We performed a secondary analysis of two published postpartum databases (the Pre-Eclampsia New Emerging Team [PE-NET] cohort and the Maternal Health Clinic [MHC] cohort) to determine the impact of the change in blood pressure criteria on the diagnosis of hypertension. The prevalence of hypertension in women with uncomplicated pregnancies (PE-NET control) was 22% compared with 56.4% in those who have had a pregnancy complicated by preeclampsia (PE, PE-NET patient) and 67.2% in those referred to the MHC due to a pregnancy complicated by any of the hypertensive disorders of pregnancy. It is well established that certain complications in pregnancy can reliably identify women with risk factors for future CVD. Thus, pregnancy and the postpartum afford a new opportunity for cardiovascular risk screening that could lead to lifestyle modification and therapeutic intervention. Applying the new guideline criteria at least doubles the prevalence of women with hypertension postpartum.
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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 | 0.019 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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".