Delay of Fetal Anatomy Ultrasound Assessment Based on Maternal Body Mass Index Does Not Reduce the Rate of Inadequate Visualization
Bibliographic record
Abstract
Objectives To determine whether delay of initial anatomy ultrasound based on the maternal body mass index (BMI) reduces the rate of inadequate visualization compared to standard timing at 180/7 to 196/7 weeks. Methods A retrospective study of singleton anatomy assessments was conducted at a tertiary care center in the 2‐year period before (A, 2012–2014) and after (B, 2014–2016) protocol initiation. Assessments in period B were scheduled on the basis of the BMI in the first trimester: lower than 25 kg/m2, 180/7 to 196/7 weeks; 25 to 29.9 kg/m2, 190/7 to 206/7 weeks; 30 to 34.9 kg/m2, 200/7 to 216/7 weeks; 35 to 39.9 kg/m2, 210/7 to 226/7 weeks; and 40 kg/m2 or higher, 220/7 to 236/7 weeks. In period A, assessments were scheduled between 180/7 and 196/7 weeks. The rate of inadequate visualization and repeated assessments in periods A and B were compared. Multivariable logistic regression, per‐protocol, and BMI subgroup analyses were completed. Results In total, 3491 pregnancies in period A and 3672 in period B were included. In period B, 74% were scheduled per protocol; however, this rate decreased for higher‐BMI categories (52% for BMI ≥40 kg/m2). The inadequate visualization rate was slightly higher in period B versus A (16.9% versus 15.0%; P = .03) and exceeded 35% for a BMI of 40 kg/m2 or higher, with or without delay. After adjusting for maternal age and fetal presentation, period B had small increased odds of inadequate visualization versus period A (adjusted odds ratio, 1.2; 95% confidence interval, 1.02–1.38). Repeated assessment rates were similar in periods B and A (14.0% versus 13.1%; P = .25). Conclusions In pregnancies with obesity, a protocol delaying the initial assessment beyond 196/7 weeks based on the maternal BMI does not reduce the rate of inadequate visualization.
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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 | 0.004 | 0.025 |
| 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) | 0.001 | 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".