How does maternal obesity affect the routine fetal anatomic ultrasound?
Bibliographic record
Abstract
OBJECTIVE: To determine the completion rate for the routine anatomic survey in obese pregnant women with body mass index (BMI)≥30 as compared to normal weight controls (BMI: 20-25). METHODS: A retrospective analysis of the routine anatomic survey was performed in 100 consecutive women with a BMI≥30. Each subject was matched to two normal weight controls, controlling for gestational age. Exclusion criteria such as anatomic abnormalities or multiple gestations were known. The degree of visibility (satisfactory, moderate or unsatisfactory), indication for repeat examination and placental location were assessed. RESULTS: Average BMI in the index cases was 35.7 (range: 30-64.8). Twenty-six (26%) of index cases were considered incomplete as compared to 5 (2.5%) of the 200 controls. The anatomic survey was completed in 74 (74%) of index cases compared with 195 (97.5%) of controls. Visibility was satisfactory in 28 (28%) of index cases, moderate in 46 (46%) and unsatisfactory in 26 (26%). In comparison, 177 (88.5%) were satisfactory, 17 (8.5%) moderate and 6 (3%) were poor in controls. CONCLUSIONS: The completion rate for the routine anatomic survey in obese (BMI≥30) pregnant women was significantly lower as compared to normal weight pregnant women.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".