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Record W4406026161 · doi:10.3390/diagnostics15010097

Current Status of CT Imaging Before Common Transcatheter Interventions for Structural Heart Disease

2025· review· en· W4406026161 on OpenAlexaff
Rodrigo Salgado, Farah Cadour, Riccardo Cau, Luca Saba

Bibliographic record

VenueDiagnostics · 2025
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAtrial fibrillationPsychological interventionRadiologyStenosisMitral valveIntensive care medicineCardiology

Abstract

fetched live from OpenAlex

Background: Over the past decade, several trials and observational studies have validated the use of minimally invasive cardiac interventions as viable treatment options for various cardiac diseases. Transcatheter techniques for severe aortic valve stenosis have rapidly emerged as alternatives to surgical aortic valve replacement in certain patient populations. Additionally, non-surgical treatment options have expanded for conditions affecting other cardiac valves, such as the mitral valve. These emerging minimally invasive interventions complement already well-established endovascular techniques for, among others, atrial septal defect closure, left atrial appendage occlusion and pulmonary vein isolation in patients with atrial fibrillation. Given their non-surgical nature and lack of direct visualisation of the targeted anatomy, these procedures heavily rely on precise pre-procedural radiological imaging for optimal patient selection and procedural success. Method: This paper is based on the expert opinion of the authors and an exhaustive literature research. Results: This manuscript reviews the most commonly employed minimally invasive cardiac interventions, highlighting the essential pre-procedural imaging information and key aspects that must be included in radiological reports to mitigate potential complications. Conclusion: Accurate pre-procedural imaging is crucial for ensuring safe and effective minimally invasive cardiac interventions, underscoring the importance of the radiologist in the pre-procedural work-up of these patients.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.820
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.009
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 head0.042
GPT teacher head0.459
Teacher spread0.417 · 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 designOther design
Domainnot available
GenreReview

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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