Pregnancy Outcomes and Blood Pressure Visit-to-Visit Variability and Level in Three Less-Developed Countries
Bibliographic record
Abstract
In pregnancy in well-resourced settings, limited data suggest that higher blood pressure (BP) visit-to-visit variability may be associated with adverse pregnancy outcomes. Included were pregnant women in 22 intervention clusters of the CLIP (Community-Level Interventions for Preeclampsia) cluster randomized trials, who had received at least 2 prenatal contacts from a community health worker, including standardized BP measurement. Mixed-effects adjusted logistic regression assessed relationships between pregnancy outcomes and both BP level (median [interquartile range]) and visit-to-visit variability (SD and average real variability [ARV], adjusted for BP level), among all women and those who became hypertensive. The primary outcome was the CLIP composite of maternal and perinatal mortality and morbidity. Among 17 770 pregnancies, higher systolic and diastolic BP levels were associated with increased odds of the composite outcome per 5 mm Hg increase in BP (odds ratio [OR], 1.05 [95% CI, 1.03–1.07] and OR, 1.08 [1.06–1.11], respectively). Higher BP visit-to-visit variability was associated with increased odds, per a SD increase in BP variability measure, of (1) hypertension (systolic: OR, 2.09 [1.98–2.21] for SD and 1.52 [1.45–1.60] for ARV; diastolic: OR, 2.70 [2.54–2.87] for SD and 1.86 [1.76–1.96] for ARV); and (2) the composite outcome (systolic: OR, 1.10 [1.06–1.14] for SD and 1.06 [1.02–1.10] for ARV; diastolic: OR, 1.07 [1.03–1.11] for SD and 1.06 [1.02–1.09] for ARV). In 3 less-developed countries, higher BP level and visit-to-visit variability predicted adverse pregnancy outcomes, providing an opportunity for high-definition medicine.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".