Chronic Histiocytic Intervillositis: A Proposed Algorithm for Management of Subsequent Pregnancies [18F]
Bibliographic record
Abstract
INTRODUCTION: Chronic histiocytic intervillositis (CHI) of the placenta is associated with serious adverse pregnancy outcomes not only in the index pregnancy but also in subsequent pregnancies. This study's aim was to propose an algorithm for the management of pregnancies following a histopathologic diagnosis of CHI. METHODS: We conducted a retrospective cohort study at a tertiary-level hospital that included CHI cases and controls matched by age, ethnicity, body mass index and pre-existing medical comorbidities, in a 1:2 ratio. We compared first- and second-trimester biomarkers for fetal aneuploidy, serum alkaline phosphatase (ALKP) and antenatal ultrasound findings, considering a p-value of <0.05 as statistically significant. RESULTS: We included 33 cases of CHI and 66 matched controls. The two groups were comparable except with regard to prior (92.6% vs. 43.3%, p<0.001) and current (87.9% vs. 42.2%, p<0.001) adverse obstetric outcomes. There were significant differences between groups in terms of abnormal first-trimester biomarkers in general (55.6% vs. 16.2%, p=0.003), and PAPP-A in particular (46.7% vs. 7.1%, p=0.005), second-trimester alpha-fetoprotein (25% vs. 0%, p=0.006), third-trimester ALKP levels (38.5% vs. 0%, p=0.045); second-trimester placental ultrasound findings (abnormal dimensions in 40% vs. 5.6%, p=0.02 and abnormal echotexture in 25% vs. 0%, p=0.047); third-trimester placental morphology (44% vs. 16.7%, p=0.009), umbilical artery Doppler studies (76% vs. 11.1%, p<0.001) and oligohydramnios (40% vs. 3.7%, p<0.001). CONCLUSION: The differences in biomarker and ultrasound findings between cases and controls was used to propose an algorithm for management of subsequent pregnancies, in terms of maternal and fetal surveillance, administration of antenatal corticosteroids and timing of 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".