The Management of Acardiac Twinning: Twin Reverse Arterial Perfusion Sequence – An International Survey
Bibliographic record
Abstract
INTRODUCTION: The optimal approach and therapy method for the acardiac twin with a reverse arterial perfusion sequence has not yet been established. The aim of this study was to determine the clinical practice patterns among international fetal therapy units in their management of these cases. METHODS: A survey was sent to fetal centers across the world via email between December 2020 and December 2021. RESULTS: Responses were obtained from 77% contacted centers. The most frequent ultrasound variables used in the evaluation of twin reverse arterial perfusion sequence include echocardiographic assessment of the pump twin and umbilical artery Doppler waveforms in the acardiac and pump twins, in 90% and 80% of the centers, respectively. Most centers in Europe and Latin America propose an in utero intervention in all cases. Most centers in Europe and Latin America prefer interstitial laser ablation, whereas radiofrequency ablation (RFA) is preferred in North America. The earliest gestational age for an intervention is on mean 13 weeks in Europe, which is earlier than the other geographic areas (p = 0.001). CONCLUSIONS: Most centers agreed that antenatal evaluation should include echocardiography along with the UA Doppler waveform measurements, and the most frequently used interventions were interstitial laser ablation or RFA at a median between 14 and 26 weeks.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".