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Record W4390796553 · doi:10.4244/eij-d-23-00722

Impact of transcatheter heart valve type on outcomes of surgical explantation after failed transcatheter aortic valve replacement: the EXPLANT-TAVR international registry

2024· article· en· W4390796553 on OpenAlexafffund
Syed Zaid, Neal S. Kleiman, Sachin S. Goel, Molly Szerlip, Michael J. Mack, Mateo Marin‐Cuartas, Siamak Mohammadi, Tamim Nazif, Axel Unbehaun, Martin Andreas, Derek R. Brinster, N. Bryce Robinson, Lin Wang, Basel Ramlawi, Lenard Conradi, Nimesh D. Desai, John K. Forrest, Rodrigo Bagur, Tom C. Nguyen, Ron Waksman, Lionel Leroux, Eric Van Belle, Kendra J. Grubb, Hasan Ahmad, Paolo Denti, Thomas Modine, Vinayak Bapat, Tsuyoshi Kaneko, Michael J. Reardon, Gilbert H.L. Tang, On Behalf Of The Explant-Tavr Registry Investigators

Bibliographic record

VenueEuroIntervention · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsLondon Health Sciences CentreWestern UniversityUniversité Laval
FundersDaiichi Sankyo EuropeNational Center for Advancing Translational SciencesAbbott VascularUniversità di PisaUniversità degli Studi di PadovaJenaValveCryoLifeMedizinische Universität WienUniversity of OttawaUniversity of Texas Health Science Center at HoustonNorthwell HealthLivaNovaInstitut de Cardiologie de MontréalInstitut universitaire de cardiologie et de pneumologie de Québec, Université LavalBoston Scientific CorporationUniversität WienUniversità degli Studi di MilanoUniversity of PennsylvaniaCook MedicalAstraZenecaAtriCureYale UniversityVanderbilt UniversityUniversitätsspital ZürichEdwards LifesciencesUniversité LavalAmgen
KeywordsMedicineValve replacementHeart valveCardiologySurgeryInternal medicineHeart failureStenosis

Abstract

fetched live from OpenAlex

BACKGROUND: There are limited data on the impact of transcatheter heart valve (THV) type on the outcomes of surgical explantation after THV failure. AIMS: We sought to determine the outcomes of transcatheter aortic valve replacement (TAVR) explantation for failed balloon-expandable valves (BEV) versus self-expanding valves (SEV). METHODS: From November 2009 to February 2022, 401 patients across 42 centres in the EXPLANT-TAVR registry underwent TAVR explantation during a separate admission from the initial TAVR. Mechanically expandable valves (N=10, 2.5%) were excluded. The outcomes of TAVR explantation were compared for 202 (51.7%) failed BEV and 189 (48.3%) failed SEV. RESULTS: Among 391 patients analysed (mean age: 73.0±9.8 years; 33.8% female), the median time from index TAVR to TAVR explantation was 13.3 months (interquartile range 5.1-34.8), with no differences between groups. Indications for TAVR explantation included endocarditis (36.0% failed SEV vs 55.4% failed BEV; p<0.001), paravalvular leak (21.2% vs 11.9%; p=0.014), structural valve deterioration (30.2% vs 21.8%; p=0.065) and prosthesis-patient mismatch (8.5% vs 10.4%; p=0.61). The SEV group trended fewer urgent/emergency surgeries (52.0% vs 62.3%; p=0.057) and more root replacement (15.3% vs 7.4%; p=0.016). Concomitant cardiac procedures were performed in 57.8% of patients, including coronary artery bypass graft (24.8%), and mitral (38.9%) and tricuspid (14.6%) valve surgery, with no differences between groups. In-hospital, 30-day, and 1-year mortality and stroke rates were similar between groups (allp>0.05), with no differences in cumulative mortality at 3 years (log-rank p=0.95). On multivariable analysis, concomitant mitral surgery was an independent predictor of 1-year mortality after BEV explant (hazard ratio [HR] 2.00, 95% confidence interval [CI]: 1.07-3.72) and SEV explant (HR 2.00, 95% CI: 1.08-3.69). CONCLUSIONS: In the EXPLANT-TAVR global registry, BEV and SEV groups had different indications for surgical explantation, with more root replacements in SEV failure, but no differences in midterm mortality and morbidities. Further refinement of TAVR explantation techniques are important to improving outcomes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.007
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)0.0010.000

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 head0.022
GPT teacher head0.367
Teacher spread0.345 · 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.

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

Citations15
Published2024
Admission routes2
Has abstractyes

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