Maternal Vascular Malperfusion and Adverse Perinatal Outcomes in Low-Risk Nulliparous Women
Bibliographic record
Abstract
OBJECTIVE: To evaluate the disease burden of placental maternal vascular malperfusion pathology in a low-risk nulliparous population and test the hypothesis that a multiparameter model in the second trimester can predict maternal vascular malperfusion with high precision. METHODS: A single-center, prospective cohort study was conducted in healthy nulliparous women. Maternal vascular malperfusion disease burden was estimated by incidence, relative risk (RR), and population-attributable risk percent. Maternal risk factors, serum biomarkers, Doppler, and placental morphologic ultrasonography were examined in isolation and in combination for prediction of this placental pathology. RESULTS: The incidence of maternal vascular malperfusion pathology was 8.4% (72/856). Women with pathology had higher risk of preeclampsia (8.33% compared with 1.79%; RR 4.67, 95% CI 1.85-11.77%; population-attributable risk 23.6%, 95% CI 16.9-31.6%), small for gestational age (SGA) (47.22% compared with 9.45%; RR 5.00, 95% CI 3.6-6.93%; population-attributable risk 25.2%, 95% CI 22.1-28.5%), and the composite of adverse outcomes (defined as SGA or preeclampsia) (47.22% compared with 10.59%; RR 4.46, 95% CI 3.25-6.13; population-attributable risk 22.5%, 95% CI 19.8-25.5%). The combination of parameters was superior to individual modalities alone in predicting maternal vascular malperfusion, but achieved only moderate precision (area under the curve 0.77, 95% CI 0.71-0.84). CONCLUSION: One in 12 healthy nulliparous women develop maternal vascular malperfusion placental pathology, and these pregnancies had a 4.5 times higher risk of developing preeclampsia or delivering a SGA neonate compared with those without this pathology. A multiparameter model achieved modest precision to predict placental maternal vascular malperfusion. Importantly, in low-risk pregnancies, maternal vascular malperfusion accounts for one fourth of pregnancy outcomes with SGA or preeclampsia. The low population-attributable risk of this placental pathology for SGA and preeclampsia illustrates the importance of discovering novel associations to reduce the disease burden of these pregnancy complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".