OC11.05: Accuracy of sonographic estimated fetal weight in postdates pregnancies: do weight estimates influence management?
Bibliographic record
Abstract
To compare sonographic estimated fetal weight (EFW) of postdates fetuses (≥41 + 0 weeks gestation) with actual birthweights (ABW). Secondary objectives were to compare EFW in macrosomic fetuses (≥4000/≥4500 g) with ABW and investigate relationship between EFW, delivery mode, and neonatal outcomes (NICU admission, APGARs). All singleton postdates gestations from 2009–2014 were identified in a clinical ultrasound database and linked to outcomes from the Alberta perinatal database (n = 3891). EFWs were determined using Hadlock method and compared with ABW using percent error (PE). PE for EFW ≥4000/4500 g vs. EFW < 4000/4500 g were compared using Mann–Whitney test. Sensitivity, specificity, PPV and NPVs were calculated. χ2 tests were used to assess association between EFW, delivery mode and neonatal outcomes. Ultrasound overestimated ABW in our postdates cohort (mean PE −6.8%) with increasing error with larger estimates (mean PE of −8.9% and −10.2% for EFW ≥ 4000 g and ≥4500 g respectively). Moreover, ABW of 57% of fetuses with EFW ≥4000 g and 63% with EFW ≥4500 g differed by >1 SD (p < 0.01). Sensitivity for detecting macrosomia was 47.6% when EFW ≥4000 g and 27.8% when ≥4500 g. Specificity was 95.9% for EFW ≥4000 g and 99.3% ≥4500 g. Overall rate of Caesarean Section (CS) was 24.8%, with 12% performed prior to labour onset. Of fetuses with EFW ≥ 4000 g and ≥4500 g, 32% and 41% were delivered by CS, respectively, which is higher than expected using χ2 test (p < 0.01). Rate of CS prior to labour was 52% when EFW was ≥4000 g, which was also higher than expected by χ2 test (p < 0.01). No statistical significance was observed for neonatal outcomes. In postdates pregnancies, ultrasound overestimated ABW and became more inaccurate with larger estimates. Fetuses with suspected macrosomia were more likely to have a CS, and more likely to have CS without labour. This suggests clinical decisions regarding mode of delivery may be influenced by a test with significant inaccuracy.
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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 | 0.011 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".