Uterine Artery Pulsatility Index in Singleton Pregnancies Conceived via Assisted Reproductive Technology Versus Spontaneous Conception: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background/Objectives: Uterine artery pulsatility index (UtA-PI) is a key biomarker of placental function, but its clinical interpretation in assisted reproductive technology (ART) pregnancies is uncertain. This meta-analysis aimed to assess trimester- and method-specific UtA-PI differences between ART and spontaneous conceptions (SC) and to examine associated risks for preeclampsia (PE) and small-for-gestational-age (SGA) neonates to contextualize its findings. Methods: A systematic search of MEDLINE, Scopus, and the Cochrane Library was conducted through 25 June 2025. We included observational studies comparing UtA-PI and perinatal outcomes in singleton ART versus SC pregnancies. The primary outcome was the standardized mean difference (SMD) in first (until the 13+6 gestational week) and second trimester (14+0–23+6 gestational weeks) UtA-PI measurements; secondary outcomes were PE and SGA rates. Analyses were stratified by ART modalities. Random-effects models were used, and study quality was evaluated using the Newcastle–Ottawa Scale and risk of bias with QUIPS tool (INPLASY registration: INPLASY202560104). Results: Thirteen cohort studies were included. Overall, ART pregnancies had significantly lower UtA-PI values than SC in both the first (SMD = −0.28; 95% CI: −0.53 to −0.03) and second trimesters (SMD = −0.20; 95% CI: −0.36 to −0.04). These reductions were driven by oocyte donation (first-trimester SMD = −0.70; 95% CI: −1.21 to −0.18; second-trimester SMD = −0.46; 95% CI: −0.65 to −0.26) and artificial cycle frozen embryo transfers (ET) (first-trimester SMD = −0.69; 95% CI: −1.00 to −0.39). These lower UtA-PI values typically suggest better placental perfusion and a lower risk of placental related complications. However, ART pregnancies had an elevated overall risk for PE (risk ratio [RR] = 2.32; 95% CI: 1.72 to 3.12), with the highest risk in oocyte donation (RR = 6.11; 95% CI: 3.35 to 11.17) and artificial cycle frozen ET (RR = 3.45; 95% CI: 1.51 to 7.90). Conclusions: ART pregnancies, particularly from oocyte donation and artificial cycle frozen ET, show lower UtA-PI values despite a significantly elevated risk for PE. This finding suggests that mechanisms other than placental perfusion contribute to PE development. Clinically, the ART method is an independent risk factor for PE, and UtA-PI interpretation should be adjusted accordingly. Further research is crucial to elucidate the underlying pathophysiology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".