Is there a relationship between fetal sex and placental pathological characteristics in twin gestations?
Bibliographic record
Abstract
BACKGROUND: Placenta plays a central role in mediating growth and development of fetuses. Sex-specific placentas may complicate this role. METHODS: The study aimed at investigating the association between fetal sex and placental pathological findings in twin gestations using generalized estimating equation modeling. We used a large population-based clinical data born in British Columbia (BC) and linked the fetal-maternal data to hand-searched pathology reports of 1493 twin placentas from twins born in BC Women hospital. We analyzed the data using generalized estimating equations taking the cluster nature of twins into consideration. RESULTS: About 26.5% of twins were monochorionic and 73.5% were dizygotic. Most twins were male (51.3%). About 2/3 of twins were sex concordant (66.6%). Of the sex concordant twins, similar percentages were male-male (34.7%) and female-female (31.2%). Of the sex discordant twins, the male-female (33.3%) group constituted about 1/3 of the whole population. Adjusted for chorionicity, birth weight discordance ≥30% and gestational age, the odds of chorionitis (1.38, 95% CI = 1.04-1.84), anastomosis (1.63, 95% CI = 1.22-2.19), unequal sharing of placenta (1.72, 95% CI = 1.11-2.64), placental inflammation (1.30, 95% CI = 1.05-1.62) and lesions (1.83, 95% CI = 1.02-3.31) were higher in male twins compared with females. Twins of either sex from sex-discordant pairs were less likely to have placental anastomosis compared to the reference category. Males from male-male pairs had higher odds of unequal placental sharing (74% higher) and composite inflammation (52% higher) compared with the reference twins. CONCLUSION: Our findings suggest a relationship between sex and placental pathological results.
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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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".