P15.10: Accuracy of antenatal sonographic identification of discordant birthweight in twins
Bibliographic record
Abstract
The aim of the study was to assess the accuracy of 12 formulae commonly used for estimation of fetal weight (EFW) to predict birthweight discordance in twins. This is a retrospective study including both di-chorionic (DC – 227 pairs) and mono-chorionic di-amniotic (MCDA −31 pairs) twins, delivered within one week of an EFW assessment, over a six-year period, at a tertiary care centre. Differences between 12 EFW formulae were assessed using Wilcoxon's Rank Sum test and concordance correlation coefficients (CCC) to evaluate how the EFW discordance corresponded with birthweight discordance. The accuracy of predicting a 20% intertwin discordance was evaluated with ROC curves. In DC twins 11 formulae demonstrated concordance, however there were significant differences between weight discordances calculated by the Warsof equation and 5 of the other formulae. In MC twins the Warsof and Combs formulae showed significant differences from all but one other formula. CCC for the 12 equations showed similar performance in evaluating intertwin discordance in DC twins (CCC 0.91–0.93), with the exception of the Warsof equation (CCC = 0.81, 95% CI: 0.80, 0.82), whose correlation was significantly lower than all other formulae. In MC twins the Combs, Ong and all Hadlock equations (excluding “2” 1984) performed equally (CCC 0.57–0.62) whereas the Warsof equation performed poorly (CCC = 0.33, 95% CI: 0.32, 0.35). In identifying a 20% discordance, the ROC curves were similar for all formulae, with similar results observed when discordances of 15% or 25% were evaluated. The ability to predict the inter twin discordance appears better in DC twins than in MC twins. For DC twins all formulae perform equally excepting Warsof's. In MC twins the prediction was least accurate with the Warsof, Merz, Shepard and Hadlock “2” (1984) formulae – none of which incorporate femur length. In MC twins using formulae that include femur length appears crucial in obtaining an accurate inter twin discordance.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".