Predictive Value of Volumetric Measurements of Fetal Adrenal Glands for Preterm Birth: A Case-Control Study
Bibliographic record
Abstract
Background: To investigate whether fetal adrenal gland volume (AGV) and fetal zone volume (FZV), important components of the fetal adrenal gland, differ between women who have term and preterm births, and to determine whether these two parameters can be used to predict premature birth. Methods: A total of 238 pregnant women at 24–28 weeks of gestation were included in this case-control study. The fetal AGV and FZV were ultrasonographically evaluated, and corrected AGV (cAGV) and corrected FZV (cFZV) were assessed with adjustments for estimated birth weight. Receiver operating characteristic (ROC) curves were used to assess the ability of AGV, FZV, cAGV, and cFZV to predict preterm birth. Results: Ultrasound exams on 220 term fetuses and 18 preterm fetuses showed that preterm fetuses exhibited higher AGV (p = 0.039), FZV (p = 0.001), cAGV (p = 0.001), and cFVZ (p = 0.001) compared to term fetuses. Conclusions: These results demonstrated that term and preterm fetuses differ in their AGV and FZV within this study population. The data generated by 3D sonography between 24 and 28 weeks of gestation may be beneficial for predicting premature birth. However, larger prospective studies with a larger sample size of preterm births are needed to validate these findings.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".