Preterm Birth Prevention: Effects of Vaginal Progesterone Administration on Blood Flow Impedance in Uterine-Fetal Circulation by Doppler Sonography
Bibliographic record
Abstract
OBJECTIVE: The present study aimed to evaluate the effect of vaginal progesterone administration on maternal and fetal circulation to prevent preterm birth. METHODS: The present prospective study was conducted on 35 women with singleton pregnancy at 18-33 weeks of gestation, who presented with at least one episode of preterm labor or asymptomatic short cervix, or past medical history of preterm birth. Doppler flow and Pulsatility Index (PI) assessment of the umbilical artery, fetal middle cerebral artery, uterine arteries, and ductusvenosus were performed before and 72 h after vaginal progesterone administration. RESULTS: Results showed a significant reduction in the PI of the uterine artery following progesterone administration. Nevertheless, no significant changes were observed in the PI of other vessels. No significant difference was found in Doppler flow parameters in any of the examined vessels before or after progesterone treatment in women with Preterm Labor Pain (PLP). Yet, a statistically significant association was observed between short cervix complication in the current pregnancy and medical history of PLP in the previous pregnancy. CONCLUSION: Treatment with vaginal progesterone reduced the PI in the uterine arteries in the second and third trimesters of pregnancy. Thus, this medication may have useful vasodilatory effects on uterine-fetal vessels.
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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 | 0.001 |
| 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".