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Record W4221135473 · doi:10.1016/j.radcr.2022.02.057

Twin reversed arterial perfusion (TRAP) sequence: A case report and a brief literature review

2022· article· en· W4221135473 on OpenAlexaff
Gurinder Dhanju, Alli Breddam

Bibliographic record

VenueRadiology Case Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsUniversity of SaskatchewanSt. Boniface Hospital
Fundersnot available
KeywordsMedicineSonographerTrap (plumbing)Sequence (biology)Monochorionic twinsObstetricsRadiofrequency ablationPregnancyRadiologyUltrasoundFetusCardiologyAblation

Abstract

fetched live from OpenAlex

Twin reversed arterial perfusion (TRAP) sequence is rare in monochorionic twin pregnancies. TRAP sequence is distinct from other multifetal pregnancies in that one of the twins has normal anatomy while the other twin has a varied amount of characteristic abnormal features. In the literature, mortality is reported 100% in the abnormal twin. We report 1 case of TRAP sequence at our institution in which the diagnosis of TRAP sequence was missed in the first trimester at another hospital. The patient, a 33-year-old G1P0A0, did not have any follow-up after her first scan until the routine second-trimester ultrasound at our institution. Both the radiologist and the sonographer did not appreciate the differential diagnosis of TRAP sequence in their clinical decision-making. The TRAP diagnosis was established after the ultrasound performed at the fetal assessment unit in our hospital. Radiofrequency ablation (RFA) procedure was performed to give the normal twin a chance to survive, but unfortunately, the prognosis was poor in this case. We conclude that diagnosing a TRAP sequence is very important early in the pregnancy for a positive outcome in the normal twin. A robust collaboration among radiologists and obstetricians is vital for the best outcome of the normal twin.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.286
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2022
Admission routes1
Has abstractyes

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