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Record W3048327657 · doi:10.1177/1556984520938897

Oversizing Increases Pacemaker Implantation Rate After Sutureless Minimally Invasive Aortic Valve Replacement

2020· article· en· W3048327657 on OpenAlexaff
Borut Geršak, Mattia Glauber, Denis Bouchard, Jure Jug, Marco Solinas

Bibliographic record

VenueInnovations Technology and Techniques in Cardiothoracic and Vascular Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineAortic valve replacementCardiologySurgeryPermanent pacemakerAortic valveInternal medicineStenosis

Abstract

fetched live from OpenAlex

Objective Cardiac conduction system disturbances potentially leading to permanent pacemaker implantation are significant postoperative complications after aortic valve replacement. The aim of this study was to assess the impact of sutureless prosthetic valve oversizing on permanent pacemaker implantation rate. Methods This multicenter retrospective study included 306 patients who underwent minimally invasive aortic valve replacement with the Perceval sutureless valve. Oversizing was determined by the implanted valve size indexed to body surface area. Data were analyzed with a multivariable logistic regression model. Results This study confirmed excellent postoperative results for minimally invasive aortic valve replacement with right anterior minithoracotomy approach and rapid deployment sutureless valves. Mortality rate was 1%. Eighteen (5.9%) patients received a new permanent pacemaker. Multivariable logistic regression model ( P = 0.05) found oversizing as significant risk factor ( P = 0.017) for permanent postoperative pacemaker implantation independent of patient age. There was a significant negative correlation between the indexed implanted valve size and the mean and peak postoperative transvalvular gradients ( P < 0.001). Conclusions Oversizing of sutureless prosthetic aortic valves is a risk factor for postoperative permanent pacemaker implantation. Proper sizing of Perceval is important to avoid complications and ensure optimal valve performance.

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 score0.013
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.308
Teacher spread0.294 · 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

Citations24
Published2020
Admission routes1
Has abstractyes

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