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Record W4414979031 · doi:10.1016/j.jaccas.2025.105295

Fetal Cardiac Magnetic Resonance Imaging in Left-Sided Diaphragmatic Hernia

2025· article· en· W4414979031 on OpenAlexaff
Gloria Biechele, Nicola Fink, Julien Dinkel, Ryoko Mehnert, Teresa Starrach, M. Schelling, Christoph Hübener, Sven� Mahner, Bernd J. Wintersperger, Jens Ricke, Sophia Stoecklein

Bibliographic record

VenueJACC Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicCongenital Diaphragmatic Hernia Studies
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsFetusMagnetic resonance imagingDiaphragmatic herniaCongenital diaphragmatic herniaDiaphragmatic breathingCardiac magnetic resonanceHerniaLung

Abstract

fetched live from OpenAlex

BACKGROUND: Magnetic resonance imaging (MRI) has become an essential complementary imaging tool during pregnancy. CASE SUMMARY: In this case of left-sided congenital diaphragmatic hernia (CDH), fetal cardiac MRI at 29 gestational weeks showed subtle septal bounce and reduced biventricular ejection fraction. On follow-up MRI at 37 gestational week, the right ventricle was significantly dilated (right-to-left ventricle index: 1.9:1.0), indicating increasing right ventricular strain and raising the suspicion of pulmonary hypertension (PH). Post delivery, the newborn required ventilation and circulatory support. Diagnosis of PH was confirmed by echocardiography. After surgical repair, the clinical course was unremarkable. DISCUSSION: This case illustrates that fetal cardiac MRI can provide a prenatal assessment of cardiovascular sequelae of CDH, thereby informing perinatal care. TAKE-HOME MESSAGES: Fetal MRI in CDH is used to accurately quantify fetal lung volume and to detect associated malformations. Additional cardiac assessment can indicate right ventricular strain and should raise suspicion of PH and prompt information of perinatal management.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.267
Teacher spread0.260 · 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.

Study designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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