VP47.03: Can fetal abdominal wall thickness predict intrapartum complications amongst mothers with pre‐gestational type 2 diabetes? A cohort study
Bibliographic record
Abstract
To evaluate the utility of fetal abdominal wall thickness (AWT) for predicting intrapartum complications amongst mothers with diabetes. This was a historical cohort study of pregnant mothers with pre-gestational type 2 diabetes delivering at a tertiary-centre between 2015-2019. Maternal and neonatal hospital records were reviewed to collect information about demographics, pregnancy complications, intrapartum events and early neonatal outcomes. Stored fetal ultrasound images were reviewed to collect biometry, and post-processing measurement of the fetal AWT at 36 weeks GA was also performed in a standardised fashion by 2 blinded and independent observers. The relationship between fetal AWT was then correlated with risk of intrapartum complications including emergency Caesarean section (CS) and shoulder dystocia. 216 pregnant women with type 2 diabetes had planned vaginal deliveries and were eligible for inclusion. Overall, the incidence of shoulder dystocia and emergency intrapartum CS were 7.3% and 17.8% respectively. There was no difference in mean fetal AWT between those that had a spontaneous vaginal delivery (8.2 mm (SD 1.6)) and those that were complicated by emergency intrapartum CS (8.1 mm (SD 1.5); p = 0.71) or shoulder dystocia (8.7mm (SD 1.4); p = 0.23). The strongest relationship between presence of intrapartum complications was birth weight (p = 0.003): with birth weights >4000 grams, the relative risk of shoulder dystocia or CS is 2.75 (95% CI 1.74-4.36; p < 0.001). There was no obvious benefit of AWT measurement at 36 weeks' in predicting shoulder dystocia and intrapartum CS amongst women at high-risk for intrapartum complications, although we were underpowered to examine this definitively. The strongest predictor of intrapartum complication remained birth weight, and so studies evaluating the use of ultrasound for predicting risk of intrapartum complications are still needed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".