The Added Value of Uterine Artery Doppler in the Evaluation of The Second and Third Trimester Fetal Distress: A Systematic Review
Bibliographic record
Abstract
Background: The uterine artery plays a critical role in fetal oxygenation and nutrient delivery during pregnancy. Abnormal uterine artery Doppler (UAD) indices, such as elevated pulsatility index (PI) and diastolic notching, are associated with adverse outcomes like fetal distress (FD), preeclampsia, and fetal growth restriction (FGR). Despite its clinical utility, the predictive accuracy of UAD in the second and third trimesters remains variable. Objective: This systematic review aimed to evaluate the diagnostic performance of UAD indices in predicting FD and related perinatal complications during the second and third trimesters of pregnancy. Methods: Following PRISMA 2020 guidelines, a comprehensive search of PubMed, Scopus, and Web of Science was conducted (January 2015–May 2025). Studies assessing UAD indices in singleton pregnancies ≥18 weeks were included. Two reviewers independently screened records, extracted data, and appraised study quality using the Newcastle-Ottawa Scale. Results: Of 204 records, 23 studies met inclusion criteria. In the second trimester, elevated PI (>95th percentile multiples of the median) showed moderate sensitivity and high specificity for FD. Bilateral notching improved specificity but not sensitivity. Third-trimester PI (>1.5 multiples of the median) had similar specificity but lower sensitivity for predicting emergency cesarean delivery due to FD. Bilateral notching in late gestation correlated strongly with adverse neonatal outcomes. Conclusion: UAD indices, particularly in the second trimester, offer high specificity for identifying pregnancies at risk of FD and adverse outcomes. However, sensitivity limitations highlight the need for multimodal screening. Standardized protocols and integrated risk models are essential for optimizing clinical utility
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".