Uterine artery and umbilical vein blood flow are unaffected by moderate habitual physical activity during pregnancy
Bibliographic record
Abstract
Abstract Objective This study aims to noninvasively quantify blood flow in the uterine arteries (UTAs) and umbilical vein (UV) using phase‐contrast magnetic resonance imaging (PC‐MRI) and test whether these correlate with maternal fitness parameters. Method Resting UTA and UV flows were measured in 23 healthy 30 ± 3‐year‐old women who engaged in moderate‐intensity physical activity during pregnancy. Participant fitness was characterized in the second and third trimesters using the submaximal oxygen uptake (VO2) test measuring heart rate (HR), VO2, ventilation (ventilatory equivalent [VE]/VO2), and the Borg rating of perceived exertion (respiratory quotient [RQ]). Linear regression models were used to determine the associations between blood flow and maternal fitness measures. Results Blood flows in the UTA (957 ± 241 mL/min) and UV (132 ± 38 mL/min/kg) were successfully measured in 20 (87%) participants. Neither was associated with any physical fitness parameters (HR, VO2, VE/VO2, and RQ) nor with any second‐to‐third trimester change in these parameters. Conclusion PC‐MRI can be used to noninvasively measure blood flow in the UTA and UV. Neither resting UTA nor UV flow is associated with maternal fitness parameters. This is the first MRI–based study to provide novel hemodynamic data suggesting decoupling between maternal moderate fitness level and the maternal‐placental‐fetal hemodynamic system in healthy, normal body mass index (BMI) pregnancies.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".