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Abstract 13429: Echocardiographic Predictors of Mitral Transvalvular Gradients After Mitraclip Insertion

2020· article· en· W3163619468 on OpenAlexaff
Sandra Hadjadj, Afonso B. Freitas‐Ferraz, Amélie Paquin, Mathieu Bernier, Kim O’Connor, Erwan Salaün, Philippe Pîbarot, Marie‐Annick Clavel, Josep Rodés‐Cabau, Jean‐Michel Paradis, Jonathan Beaudoin

Bibliographic record

VenueCirculation · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversité du QuébecInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineMitraClipCardiologyInternal medicineMitral regurgitationMitral valveVentricular outflow tractStroke volumeNuclear medicineEjection fractionHeart failure

Abstract

fetched live from OpenAlex

Introduction: The MitraClip procedure is a non-surgical alternative for patients with severe mitral regurgitation and high surgical risk. However, the MitraClip may lead to a reduction in the mitral valve orifice area (MVOA) and elevated transmitral mean gradients (TMG). The objectives of this study are to assess the value of baseline MVOA by different imaging methods and explore the value of MVOA indexed for left ventricular (LV) forward stroke volume (SV) to predict postprocedural TMG. Methods: Preprocedural echo images were retrospectively reviewed in 76 consecutive patients. MVOA from 2D transthoracic (MVOA TTE ), 2D transgastric (MVOA TG ) and 3D transesophageal (MVOA 3D ) echocardiography were measured and then indexed by the SV measured by Doppler in the LV outflow tract (MVOA/SV) . Postprocedural TMG was measured at one month and survival rate at one year. Results: Patients with postprocedural TMG >5 mmHg (18/76, 24%) had significantly smaller preprocedural MVOA 3D (3.9±0.9 vs 5.2±1.3 cm 2 , p<0.01) and MVOA TTE (4.9±1.1 vs 5.9±1.5 cm 2 , p=0.02). No significant difference was found for MVOA TG (5.5±1.4 vs 5.9±1.4 cm 2 , p=0.2). Best threshold values for MVOA 3D and MVOA TTE to predict postprocedural TMG >5 mmHg were respectively 3.9 cm 2 (AUC=0.80, IC95%: 0.67-0.94, p<0.01; sensitivity (Se) 62%, specificity (Sp) 87%) and 4,6 cm 2 (AUC=0.69, IC95%: 0.54-0.83, p=0.02; Se 50%, Sp 84%). MVOA/SV from each echocardiographic modality were smaller in patients with postprocedural TMG >5 mmHg (3D: 80 [62-95] vs 113 [99-129] cm 2 /L; TTE: 92 [81-105] vs 130 [100-166] cm 2 /L; TG: 104 [83-123] vs 135 [104-166] cm 2 /L; p<0.01 for all). MVOA/SV 3D was overall the best predictor of postprocedural TMG >5 mmHg, with an optimal threshold of 96 cm 2 /L (AUC=0.86, IC95%: 0.76-0.97, p<0.001; Se 84%, Sp 81%). Patients with MVOA 3D <3.9 cm 2 and MVOA/SV 3D <96 cm 2 /L tend to be at higher risk for mortality at one-year follow-up (69% vs 84%, p=0.14 and 67% vs 87%, p=0.11 respectively). Conclusion: Unlike preprocedural MVOAs assessed by 3D echocardiography, preprocedural MVOAs measured by 2D echocardiographic modalities were poor predictors of high TMG after MitraClip. Preprocedural MVOA 3D <3.9 cm 2 and MVOA/SV 3D <96 cm 2 /L were found to be the best cut-off values to predict postprocedural TMG >5 mmHg.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.000

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 head0.014
GPT teacher head0.272
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations2
Published2020
Admission routes1
Has abstractyes

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