Guidelines on Fetal Growth Restriction: A Comparison of Recent National Publications
Bibliographic record
Abstract
OBJECTIVE: This study aims to compare recommendations from recently published national clinical guidelines for pregnancies complicated by fetal growth restriction (FGR). MATERIALS AND METHODS: Clinical guidelines informing best practice management of pregnancies with FGR issued by the American Congress of Obstetricians and Gynecologists, the Society of Obstetricians and Gynaecologists of Canada and the Royal College of Obstetricians and Gynaecologists in the United Kingdom are reviewed together with the published literature on this topic. RESULTS: Each of the guidelines uses different terminology to describe pregnancies affected by suboptimal fetal growth; all of them agree that an estimated fetal weight < 10th centile should alert clinicians to small fetal size. All guidelines describe risk factor screening for improved detection of FGR and acknowledge the limited accuracy achieved with fundal height measurement. No agreement is reached over the value of fetal weight customization. All colleges have varied opinions regarding methods of Doppler surveillance, however agree that umbilical artery Doppler is beneficial as primary surveillance tool. CONCLUSIONS: The results of this review relay significant inconsistencies and call for an urgent and practical international consensus on this important and common clinical topic. Current data were used to develop a clinical practice guideline for Ireland, which will be presented in context with this review.
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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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".