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Record W2572579748 · doi:10.4244/eij-d-16-00299

Transcatheter aortic valve replacement with the Portico valve: one-year results of the early Canadian experience

2017· article· en· W2572579748 on OpenAlexaffabout
Gidon Perlman, Anson Cheung, Éric Dumont, Dion Stub, Danny Dvir, María Del Trigo, Marc Pelletier, Sami Alnasser, Jian Ye, David Wood, Christopher Thompson, Philipp Blanke, Jonathon Leipsic, Michael A. Seidman, Heather LeBlanc, Christopher E. Buller, Josep Rodés‐Cabau, John G. Webb

Bibliographic record

VenueEuroIntervention · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Michael's HospitalSt. Paul's Hospital
Fundersnot available
KeywordsMedicineValve replacementRegurgitation (circulation)CardiologyAortic valveInternal medicineSurgeryStenosis

Abstract

fetched live from OpenAlex

AIMS: The aim of this study was to examine the short- and medium-term outcomes of transcatheter aortic valve replacement (TAVR) with the self-expanding and repositionable Portico valve (St. Jude Medical, St. Paul, MN, USA). METHODS AND RESULTS: A total of 57 patients underwent TAVR with the Portico valve between March 2012 and August 2014, representing the first-in-human experience and the entire early experience in Canada. Patients were followed up at 30 days and one year with repeat echocardiography and clinical review. Patients were 80.8±7.3 years of age, and the Society of Thoracic Surgeons predicted risk of mortality was 7.7±5.7%. All patients had a valve implanted and four patients (7%) required a second valve. At 30 days, there were two deaths (3.5%), three disabling strokes (5.3%), and new pacemakers in five (8.8%) patients. Echocardiography revealed moderate/severe aortic regurgitation in two patients (3.6%). At one year, survival was 84.2% and echocardiographic findings were unchanged. CONCLUSIONS: Transcatheter aortic valve replacement with the repositionable Portico valve provides satisfactory short- and medium-term haemodynamic and clinical results.

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 score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.002
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 head0.025
GPT teacher head0.321
Teacher spread0.296 · 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

Citations23
Published2017
Admission routes2
Has abstractyes

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