842Prevention of severe preeclampsia at term gestation among women with chronic hypertension
Bibliographic record
Abstract
Abstract Background Chronic hypertension is a strong risk factor for severe preeclampsia/eclampsia (SPE), and timely obstetric intervention can prevent SPE and reduce perinatal complications. We quantified gestational age-specific rates of SPE and estimated the benefits of preventive interventions among women with chronic hypertension at term gestation (≥37 weeks). Methods Women with chronic hypertension and a term, singleton, hospital delivery in Washington State, 2003-2013, were included in the study (N = 9697) with data obtained from birth certificates and hospital records. Adverse outcomes included SPE and composite severe neonatal morbidity (e.g., seizures, intracranial hemorrhage) and perinatal death (SNMM). Preventive interventions included labour induction and pre-labour cesarean delivery. Results There were 1026 cases of SPE (10.6 per 100 women with chronic hypertension). Gestational age-specific SPE rates ranged between 2.8 and 4.1 per 100 ongoing pregnancies; the frequency of preventive intervention at each gestational week ranged between 58% and 66%. Gestational age-specific SPE and SNMM rates were lower following preventive intervention: such intervention reduced the frequency of SPE/SNMM by 28 per 100 additional interventions at 37 weeks, 22 per 100 at 38 weeks, 17 per 100 at 39 weeks, 13 at 40 weeks and 6 per 100 additional interventions at 41 weeks’ gestation. Conclusions Labour induction and pre-labour cesarean delivery at term gestation can prevent a substantial proportion of severe preeclampsia/eclampsia and perinatal death/severe neonatal morbidity among women with chronic hypertension. Key messages SPE occurs in approximately 11% of women with chronic hypertension at term gestation. Obstetric interventions can prevent SPE and improve adverse pregnancy outcomes.
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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 | 0.000 |
| 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".