OC19.02: Colour Doppler and 3D ultrasound and implantation of the human embryos
Bibliographic record
Abstract
Embryo quality and endometrial receptivity (ER) are the two major contributors to a successful IVF/IVM cycle. The optimal method to assess ER should be non-invasive, easy to perform and yield immediate results. Transvaginal ultrasound meets these requirements. Endometrial thickness and appearance, sonohysterogram (SHG), color Doppler and 3D ultrasound have been used to assess ER. SHGs can diagnose polyps, submucous myomas, synechiae and congenital anomalies. 3D ultrasound visualizes the transverse plane of the pelvis and projects scans in coronal view, providing a more accurate evaluation of the uterine cavity, which can differentiate between bicornuate uterus and septate uterus. The septum can then be removed by an operative hysteroscopy. It can diagnose an arcuate uterus and save unnecessary procedures. Uterine synechiae and endometrial polyps that may interfere with implantation can be more accurately diagnosed and then treated. The size and extent of uterine myomas can be defined and treatment is then modified according to the scan. Color Doppler can be used to assess the uterine and endometrial blood flow, which can predict the success of the IVF/ET cycle. A high uterine artery pulsatility index (PI) > 3.0 and absence of pulsatile subendometrial blood flow have been found to be associated with lower implantation and pregnancy rates. If uterine artery PI > 3.0 and there is no pulsatile subendometrial blood flow, then hCG can be withheld until the blood flow improves. Low dose aspirin and vaginal Sildenafil may help to improve the blood flow. An exciting option would be to vitrify the oocytes and transfer the embryos in a subsequent cycle when the endometrium can be artificially prepared to improve uterine and endometrial blood flow.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.074 | 0.019 |
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".