OC17.02: Assessment of fetal right ventricular systolic function: nomograms of fractional area change by 2D‐echocardiography
Bibliographic record
Abstract
Right ventricular (RV) fractional area change (FAC) is a 2D-echocardiographic parameter to assess RV global systolic function. Fetal reference ranges are not yet available. Our aims were: to study prenatal RV FAC feasibility and reproducibility and to construct nomograms for RV FAC and end-diastolic and end-systolic RV areas throughout gestation. Prospective cohort study including 602 low-risk singleton pregnancies undergoing a fetal echocardiography from 18-41 weeks of gestation. RV end-diastolic and end-systolic areas were measured following standard recommendations for ventricular dimensions and strict landmarks to identify the phases of the cardiac cycle. RV FAC was calculated as: [(ED area – ES area) / ED area] x 100. RV FAC intra- and inter-observer reproducibility was evaluated in 45 fetuses by calculating the interclass correlation coefficient (ICC). Parametric regressions were tested to model each parameter against gestational age (GA) and estimated fetal weight (EFW). RV areas and FAC were successfully obtained in ∼99% of fetuses with acceptable reproducibility [FAC ICC (95% confidence interval): 0.69 (0.44-0.83)]. Nomograms were constructed for RV end-diastolic and end-systolic areas and FAC. RV areas showed a quadratic and logarithmic increase with GA and EFW, respectively. In contrast, RV FAC showed a slight quadratic decrease throughout gestation (figure 1). The best models for RV areas and FAC were a second degree polynomial. Supporting information can be found in the online version of this abstract Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".