Association of Acute Histological Chorioamnionitis and Other Placental Lesions With Subsequent Pregnancy Outcomes After Spontaneous Preterm Birth
Bibliographic record
Abstract
Objectives Acute histological chorioamnionitis (HCA) is detected in over 50% of spontaneous preterm birth (PTB) and is associated with worse neonatal prognosis. We aim to investigate whether the presence of HCA impacts subsequent pregnancy outcomes. Methods This retrospective cohort study included deliveries at a tertiary centre from 2014 to 2020. Participants were individuals with a history of spontaneous PTB or pregnancy loss >16 0 weeks and available placental pathology (index pregnancy) with a subsequent pregnancy followed at the same institution. Placentas were classified according to the presence of HCA, other placental lesions, or no lesions. Subsequent pregnancy outcomes were analyzed. The primary outcome was the rate of overall and spontaneous PTB (<37 0 weeks) in the subsequent pregnancy. Results A total of 292 individuals met the study criteria, of which 133 had HCA, 61 had other placental lesions, and 98 had no lesions. Individuals with HCA in the index delivery had a higher risk of PTB <28 0 weeks in the subsequent pregnancy, compared to the no-lesion group (10.4% vs. 1.0%, P = 0.004). Rates of PTB >28 0 weeks did not significantly differ. The risk of neonatal adverse composite outcomes was higher in the HCA group (13.9% vs. 4.2%, P < 0.01). In a subanalysis of different placental lesions at the index PTB, only maternal vascular malperfusion was associated with recurrent PTB (adjusted odds ratio 2.57, P = 0.01). Conclusions PTB with HCA is associated with higher rates of extreme PTB and adverse neonatal outcomes in the subsequent pregnancy. The inclusion of placental pathology analysis may improve individualized risk assessment in future pregnancies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".