Blood pressure measurement and adverse pregnancy outcomes: A cohort study testing blood pressure variability and alternatives to 140/90 mmHg
Bibliographic record
Abstract
OBJECTIVE: To examine the association with adverse pregnancy outcomes of: (1) American College of Cardiology/American Heart Association blood pressure (BP) thresholds, and (2) visit-to-visit BP variability (BPV), adjusted for BP level. DESIGN: An observational study. SETTING: Analysis of data from the population-based UK Southampton Women's Survey (SWS). POPULATION OR SAMPLE: 3003 SWS participants. METHODS: Generalised estimating equations were used to estimate crude and adjusted relative risks (RRs) of adverse pregnancy outcomes by BP thresholds, and by BPV (as standard deviation [SD], average real variability [ARV] and variability independent of the mean [VIM]). Likelihood ratios (LRs) were calculated to evaluate diagnostic test properties, for BP at or above a threshold, compared with those below. MAIN OUTCOME MEASURES: Gestational hypertension, severe hypertension, pre-eclampsia, preterm birth (PTB), small-for-gestational-age (SGA) infants, neonatal intensive care unit (NICU) admission. RESULTS: A median of 11 BP measurements were included per participant. For BP at ≥20 weeks' gestation, higher BP was associated with more adverse pregnancy outcomes; however, only BP <140/90 mmHg was a good rule-out test (negative LR <0.20) for pre-eclampsia and BP ≥140/90 mmHg a good rule-in test (positive LR >8.00) for the condition. BP ≥160/110 mmHg could rule-in PTB, SGA infants and NICU admission (positive LR >5.0). Higher BPV (by SD, ARV, or VIM) was associated with gestational hypertension, severe hypertension, pre-eclampsia, PTB, SGA and NICU admission (adjusted RRs 1.05-1.39). CONCLUSIONS: While our findings do not support lowering the BP threshold for pregnancy hypertension, they suggest BPV could be useful to identify elevated risk of adverse 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".