Pathologic Basis for the Definition of Discordant Growth in Dichorionic Twins
Bibliographic record
Abstract
OBJECTIVE: The aim of the current study was to identify the optimal cutoff that should define discordance in dichorionic twin gestations through correlation with abnormal placental pathology as a specific measure of fetal growth restriction of the smaller twin. METHODS: We performed a retrospective cohort study of all women with dichorionic twin pregnancies who gave birth in a single center between 2002 and 2015. We investigated the association between the level of growth discordance and maternal vascular malperfusion (MVM) pathology in the placenta of the smaller twin, with and without adjustment for whether the smaller twin is small for gestational age (SGA). RESULTS: A total of 1,198 women with dichorionic twin gestation met the study criteria. The rate of MVM pathology in the placenta of the smaller twin increased with the level of discordance and was most obvious for discordance ≥25% (rate of MVM 12.0% compared with 2.8% in cases with discordance <10%, adjusted relative risk [aRR] 3.71, 95% confidence interval [CI] 1.97-6.99). When the analysis was adjusted for SGA of the smaller twin, discordance was independently associated with MVM pathology only when growth discordance was ≥25% (aRR 2.18, 95%-CI 1.01-4.93), while SGA was strongly associated with MVM pathology irrespective of the level of discordance. CONCLUSION: Our findings suggest that discordant growth in dichorionic twins should raise the concern of fetal growth restriction of the smaller twin, irrespective of whether the smaller twin is SGA, only when the discordance s ≥25%. The association of lower levels of discordance with abnormal placental pathology is mainly driven by the confounding effect of SGA of the smaller twin.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 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) | 0.001 | 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".