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Record W2419660592 · doi:10.1097/rti.0000000000000169

Imaging in Minimally Invasive Mitral Valve Repair

2015· review· en· W2419660592 on OpenAlexaff
Stefanie Mangold, Mario Castillo-Sang, U. Joseph Schoepf, Jonathon Leipsic, Stephen R. Fuller, Julian L. Wichmann, Giuseppe Muscogiuri, Carlo N. De Cecco

Bibliographic record

VenueJournal of Thoracic Imaging · 2015
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of British ColumbiaSt. Paul's Hospital
Fundersnot available
KeywordsMedicinePerioperativeMagnetic resonance imagingRadiologyCardiac imaging

Abstract

fetched live from OpenAlex

Minimally invasive mitral valve (MV) repair and replacement techniques have evolved as increasingly used alternatives to open heart surgery especially in patients unsuitable for surgery or at high perioperative risk. The vast majority of these techniques are still under development, and only a limited number of devices are approved for clinical use; however, they do show promising results in terms of minimizing complications and improving clinical outcome. The complex anatomy of the MV and the annulus complicates not only the development of devices for minimally invasive MV repair or replacement but also complicates preprocedural planning, which is mandatory for minimization of postprocedural complications. Although echocardiography still plays a crucial clinical role, cross-sectional imaging modalities such as coronary computed tomography (CCT) and cardiac magnetic resonance imaging (CMR) are increasingly gaining importance for preprocedural planning. Specifically, CCT seems to be more practicable for preinterventional planning and device sizing, whereas CMR has been shown useful in detecting increased risk for adverse clinical outcomes through delayed gadolinium enhancement and the monitoring of cardiac morphology and function in the framework of follow-up examinations. This article describes recent techniques currently available or under development for minimally invasive repair or replacement of the MV and reviews the current state of CCT and CMR imaging for preinterventional and postinterventional diagnostic workup.

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), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.947
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.017
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.042
GPT teacher head0.443
Teacher spread0.401 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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