Outcomes of Postpartum Preeclampsia: A Retrospective Cohort Study of 1.3 Million Pregnancies
Bibliographic record
Abstract
OBJECTIVE: We assessed the association between postpartum preeclampsia and the risk of adverse maternal and neonatal outcomes. Evidence suggests that postpartum preeclampsia is initiated antenatally, but the impact on birth outcomes is unclear. DESIGN: Retrospective cohort study. SETTING: All deliveries in hospitals of Quebec, Canada. POPULATION: 1 317 181 pregnancies between 2006 and 2022. METHODS: We identified patients who developed preeclampsia in the postpartum period. Using log-binomial regression models, we estimated adjusted risk ratios (RR) and 95% confidence intervals (CI) for the association of postpartum or antepartum preeclampsia with adverse pregnancy outcomes relative to no preeclampsia. MAIN OUTCOME MEASURES: Preterm birth, placental abruption, severe maternal morbidity and recurrent preeclampsia. RESULTS: Postpartum preeclampsia was less frequent than antepartum preeclampsia (n = 4123 [0.3%] vs. 51 269 [3.9%]). Postpartum preeclampsia was associated with preterm birth (RR 1.45, 95% CI 1.34-1.57), placental abruption (RR 1.36, 95% CI 1.16-1.59) and severe maternal morbidity (RR 6.48, 95% CI 5.87-7.16) compared with no preeclampsia. Antepartum preeclampsia was also associated with these outcomes. Moreover, patients with postpartum preeclampsia in a first pregnancy were at risk of adverse outcomes in a subsequent pregnancy, particularly recurrent preeclampsia (RR 7.77, 95% CI 6.54-9.23). CONCLUSIONS: Postpartum preeclampsia is associated with adverse outcomes at delivery, despite being detected only postnatally. Our findings suggest that patients with adverse birth outcomes may benefit from blood pressure measurements up to 6 weeks following delivery.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".