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Record W2898581089 · doi:10.1093/eurheartj/ehy590

Outcomes of transcatheter mitral valve replacement for degenerated bioprostheses, failed annuloplasty rings, and mitral annular calcification

2018· article· en· W2898581089 on OpenAlexaff
Sung-Han Yoon, Brian Whisenant, Sabine Bleiziffer, Victoria Delgado, Abhijeet Dhoble, Niklas Schofer, Lena Eschenbach, Eric Bansal, D. Murdoch, Marco Ancona, Tobias Schmidt, Ermela Yzeiraj, Flavien Vincent, Hiroki Niikura, Masahiko Asami, Axel Unbehaun, Sameer Hirji, Buntaro Fujita, Miriam Silaschi, Gilbert H L Tang, Shingo Kuwata, S. Chiu Wong, Antonio H. Frangieh, Colin M. Barker, James E. Davies, Alexander Lauten, Florian Deuschl, Luis Nombela‐Franco, Rajiv Rampat, Pedro Felipe Gomes Nicz, Jean‐Bernard Masson, Harindra C. Wijeysundera, Horst Sievert, Daniel J. Blackman, Enrique Gutiérrez, Daisuke Sugiyama, Tarun Chakravarty, David Hildick‐Smith, Fábio Sândoli de Brito, Christoph Jensen, Christian Jung, Richard W. Smalling, Martin Arnold, Simon Redwood, Albert Markus Kasel, Francesco Maisano, Hendrik Treede, Stephan Ensminger, Saibal Kar, Tsuyoshi Kaneko, Thomas Pilgrim, Paul Sorajja, Éric Van Belle, Bernard Prendergast, Vinayak Bapat, Thomas Modine, Joachim Schöfer, Christian Frerker, Jörg Kempfert, Guilherme F. Attizzani, Azeem Latib, Ulrich Schäfer, John G. Webb, Jeroen J. Bax, Raj Makkar

Bibliographic record

VenueEuropean Heart Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSunnybrook Health Science CentreSt. Paul's HospitalCentre Hospitalier de l’Université de MontréalUniversity of British Columbia
Fundersnot available
KeywordsMedicineMitral valve replacementCardiologyMitral valveCalcificationInternal medicineMitral regurgitationVentricular outflow tract obstructionVentricular outflow tractSurgery

Abstract

fetched live from OpenAlex

Aims: We sought to evaluate the outcomes of transcatheter mitral valve replacement (TMVR) for patients with degenerated bioprostheses [valve-in-valve (ViV)], failed annuloplasty rings [valve-in-ring (ViR)], and severe mitral annular calcification [valve-in-mitral annular calcification (ViMAC)]. Methods and results: From the TMVR multicentre registry, procedural and clinical outcomes of ViV, ViR, and ViMAC were compared according to Mitral Valve Academic Research Consortium (MVARC) criteria. A total of 521 patients with mean Society of Thoracic Surgeons score of 9.0 ± 7.0% underwent TMVR (322 patients with ViV, 141 with ViR, and 58 with ViMAC). Trans-septal access and the Sapien valves were used in 39.5% and 90.0%, respectively. Overall technical success was excellent at 87.1%. However, left ventricular outflow tract obstruction occurred more frequently after ViMAC compared with ViR and ViV (39.7% vs. 5.0% vs. 2.2%; P < 0.001), whereas second valve implantation was more frequent in ViR compared with ViMAC and ViV (12.1% vs. 5.2% vs. 2.5%; P < 0.001). Accordingly, technical success rate was higher after ViV compared with ViR and ViMAC (94.4% vs. 80.9% vs. 62.1%; P < 0.001). Compared with ViMAC and ViV groups, ViR group had more frequent post-procedural mitral regurgitation ≥moderate (18.4% vs. 13.8% vs. 5.6%; P < 0.001) and subsequent paravalvular leak closure (7.8% vs. 0.0% vs. 2.2%; P = 0.006). All-cause mortality was higher after ViMAC compared with ViR and ViV at 30 days (34.5% vs. 9.9% vs. 6.2%; log-rank P < 0.001) and 1 year (62.8% vs. 30.6% vs. 14.0%; log-rank P < 0.001). On multivariable analysis, patients with failed annuloplasty rings and severe MAC were at increased risk of mortality after TMVR [ViR vs. ViV, hazard ratio (HR) 1.99, 95% confidence interval (CI) 1.27-3.12; P = 0.003; ViMAC vs. ViV, HR 5.29, 95% CI 3.29-8.51; P < 0.001]. Conclusion: The TMVR provided excellent outcomes for patients with degenerated bioprostheses despite high surgical risk. However, ViR and ViMAC were associated with higher rates of adverse events and mid-term mortality compared with ViV.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.349
Teacher spread0.313 · 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

Labeled directly by 2 models reading the full record.

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".

Quick stats

Citations374
Published2018
Admission routes1
Has abstractyes

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