Association of Pre-Implantation Uterine Artery Doppler with Clinical Pregnancy in Assisted Reproductive Technology: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background and Objectives: This meta-analysis aimed to determine whether pre-implantation uterine artery (UtA) Doppler measurements are associated with clinical pregnancy in women undergoing assisted reproductive technologies (ART). Materials and Methods: A systematic search of MEDLINE, Scopus, and the Cochrane Library from inception until 25 March 2025 was conducted to identify relevant studies. Additional records were retrieved through grey literature searching and manual reference checks. Eligible publications were observational studies or clinical trials that evaluated UtA Doppler indices prior to embryo transfer in adult women undergoing ART. Studies were required to report on clinical pregnancy rates, while those enrolling participants under 18 years of age, lacking Doppler data, or providing no pregnancy endpoints were excluded. Three reviewers independently assessed study quality using the Newcastle–Ottawa Scale and the Quality in Prognosis Studies tool. Meta-analyses were performed using a random-effects model to calculate mean differences (MDs) with 95% confidence intervals (CIs). Heterogeneity was examined via Cochran’s Q and the I2 statistic. Sensitivity analyses excluded studies at high risk of bias. Results: In total, 12 studies met the inclusion criteria, including a population of 3317 women. Women who achieved clinical pregnancy had a lower mean UtA pulsatility index (PI) (MD, −0.26; 95% CI, −0.46 to −0.06) and a higher peak systolic velocity (PSV) (MD, 8.59; 95% CI, 2.31 to 14.87) than those who did not conceive. Subgroup analyses showed that UtA PI measured during the menstrual cycle was lower in clinical pregnancy cases (MD, −0.38; 95% CI, −0.66 to −0.10). Measurements on the day of hCG administration or the day before showed a non-significant difference in UtA PI (MD, −0.43; 95% CI, −1.03 to 0.17), while assessments on the day of embryo transfer showed no significant difference between groups (MD, −0.02; 95% CI, −0.28 to 0.24). Conclusions: This meta-analysis suggests that lower UtA PI and higher PSV prior to embryo transfer are associated with higher clinical pregnancy rates in ART, particularly when measurements are taken during the menstrual cycle. Although these findings highlight a potential role for uterine hemodynamics in successful clinical pregnancy, UtA Doppler alone may not be a reliable predictor. Future studies should focus on earlier-cycle Doppler measurements and their integration into multifactorial models to improve prognostic accuracy.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 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 | 0.001 | 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".