Uterine artery Doppler pulsatility index at 11–38 weeks in ICSI pregnancies with egg donation
Bibliographic record
Abstract
BACKGROUND: Uterine artery Doppler pulsatility index (UtA-PI) may be different in pregnancies with egg donation (ICSI-ED) as compared to conceptions with autologous intra-cytoplasmatic sperm injection (autologous ICSI) and to spontaneous conceptions (SC). METHODS: One hundred and ninety-four pregnant women with different modes of conception (MC) were prospectively evaluated: 53 ICSI-ED, 36 autologous ICSI and 105 SC. To evaluate the effects of different MC on PI, multivariable linear regression (MLR) models predicting UtA-PI were fitted after adjustment for maternal age, body mass index, race, parity, smoking status and gestational age. RESULTS: In the first trimester, at MLR, autologous ICSI was not associated with a significantly different UtA-PI [estimate (EST) 0.01; 95% confidence interval (CI) -0.19, 0.2; P=0.9] when compared to SC. Conversely, MC by ICSI-ED was associated with lower first trimester UtA-PI (EST -0.32; CI -0.55, -0.08; P=0.01) when compared to SC. At MLR, MC by autologous ICSI and by ICSI-ED were not associated with significant differences in the second and third trimester UtA-PI when compared to SC. CONCLUSION: ICSI-ED conception presented lower UtA-PI when compared to SC at 11+0-13+6 weeks but not at later assessments. Correction of UtA-PI measurement specifying the origin of oocyte may be useful in first trimester screening.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".