P63The effect of fetal neck position on nuchal translucency measurement
Bibliographic record
Abstract
Background The aim of this study was to determine whether the position of the fetal neck has a significant effect on nuchal translucency measurement (NT). Method A prospective cross‐sectional study was carried out. One hundred and ninety‐six women from an unselected population underwent transabdominal sonography. The nuchal translucency was measured in the mid‐sagittal plane, with the fetal neck in the flexed, neutral and extended positions. Measurement was taken to the nearest 0.1 mm. Statistical analysis using a paired t‐test for the differences in the extended and neutral position nuchal translucency [delta extended NT] and in the flexed and neutral position nuchal translucency [delta flexed NT] was performed. Results On average the extended NT was 0.62 mm greater than the neutral NT value [95% confidence interval 0.53–0.70, T = 14.33, P = < 0.00001]. The flexed NT was on average 0.40 mm less than the neutral NT value [95% confidence interval 0.34–0.47, T = 11.99, P = < 0.00001]. The repeatability coefficient was lower in the case of neutral NT measurement [0.48] and was higher in the other groups [extended = 1.04, flexed = 0.70]. Conclusion The effect of fetal neck position can make a significant difference on nuchal translucency measurement. Repeatability of measurements are more accurate with the fetal neck in the neutral position. These findings have important implications for clinicians using nuchal translucency to screen the general obstetric population.
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".