Nonpresenting Dichorionic Twins and Placental Vascular Malperfusion
Bibliographic record
Abstract
OBJECTIVE: To explore the hypothesis that selective placental pathology affecting the nonpresenting twin is a significant contributory factor mediating the smaller size at birth of nonpresenting dichorionic twins. METHODS: We conducted a retrospective cohort study of all dichorionic twin deliveries in a single tertiary center between 2002 and 2015 where by departmental policy, all placentas from multifetal gestations are routinely sent for pathologic examination. Maternal charts, neonatal charts, and pathology reports were reviewed. Placental abnormalities were classified into lesions associated with maternal vascular malperfusion, fetal vascular malperfusion, placental hemorrhage, and chronic villitis. Comparison of neonatal outcomes and placental abnormalities was made between all nonpresenting and all presenting twins as well as within twin pairs. RESULTS: A total of 1,322 women with dichorionic twins were studied. Nonpresenting twins were smaller at birth compared with the presenting cotwin starting at 32 weeks of gestation (birth weight [±standard deviation] 2,224±666 g compared with 2,278±675 g, P=.036). Nonpresenting twins had smaller placentas (361±108 g compared with 492±129 g, P<.001) as early as 24 weeks of gestation. Nonpresenting twins had higher odds for any placental abnormality (adjusted odds ratio [OR] 1.91, 95% confidence interval [95% CI] 1.63-2.23), small placenta (adjusted OR 4.69, 95% CI 3.75-5.88), and maternal vascular malperfusion (OR 2.75, 95% CI 2.32-3.27) compared with their presenting cotwins. In nonpresenting twins, the presence of maternal vascular malperfusion pathology was associated with lower birth weight compared with their presenting cotwin during the third trimester. CONCLUSION: The lower birth weight of nonpresenting fetuses in dichorionic twin pregnancies is correlated with a higher rate of placental maternal vascular malperfusion pathology.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".