P14.85: Uterine arteriovenous malformation in pregnancy—a case series
Bibliographic record
Abstract
Case 1: A 34 year old G2A1 was referred at 20 weeks' gestation for unusual ultrasound findings at the time of routine second trimester examination. Ultrasound was performed with 3D, colour and Power Doppler which demonstrated an arteriovenous malformation (AVM) encompassing the entire lower uterine segment with very thin myometrium overlying it. Cesarean section was arranged at 27 weeks' gestation. Femoral sheaths were placed by interventional radiology prior to induction of anaesthesia and the uterine arteries were successfully embolized immediately post-op. Follow up ultrasound demonstrated residual venous flow, and repeat embolization was performed successfully. Case 2: A 19 year old G2A1 woman was transferred in at 24 and 6 weeks' gestation with preterm labour. Despite reportedly normal antenatal ultrasounds, she returned three weeks postpartum with a massive hemorrhage. CT scan confirmed AVM of the uterus. The patient was resuscitated and underwent successful embolization of the uterine arteries. Case 3: A 30 year old G1 referred after an abnormal maternal serum screen and 18 week ultrasound consistent with trisomy 21. The patient had an elective termination of pregnancy after confirmation with amniocentesis. She presented 4 weeks postpartum with a hemorrhage. Ultrasound identified a fundal AVM, which was confirmed by MRI. The uterine arteries required two embolization procedures. Following a thorough work-up the patient has subsequently been diagnosed with hereditary hemorrhagic telangiectasia. She is currently pregnant without experiencing difficulties with fertility. Ultrasound is important in the identification of uterine AVM. This is a rare condition which can be life threatening in conjunction with pregnancy. It can effectively be treated with uterine artery embolization. Thorough work up for the etiology of AVM is important for long term patient care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".