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Record W4292794428 · doi:10.1111/jocs.16839

A survey of cardiac surgeons to evaluate the use of sutureless aortic valve replacement in Canada

2022· article· en· W4292794428 on OpenAlexaffabout
Ahmad Makhdoum, Kevin Kim, Alex Koziarz, Seleman Reza, Ali Alsagheir, Arjun Pandey, Kevin Teoh, Waleed Alhazzani, André Lamy, Bobby Yanagawa, Emilie P. Belley‐Côté, Richard Whitlock

Bibliographic record

VenueJournal of Cardiac Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsHealth Sciences CentreSouthlake Regional Health CenterImpactMcMaster UniversityPopulation Health Research InstituteUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineRespondentAortic valve replacementCardiac surgeryCardiothoracic surgeryRandomized controlled trialStenosisLimitingSurgeryEmergency medicineCardiology

Abstract

fetched live from OpenAlex

BACKGROUND: Sutureless aortic valve replacement (SuAVR) is gaining popularity for the treatment of aortic stenosis. We aimed to describe Canadian cardiac surgeons' practice patterns and perceptions regarding SuAVR. METHODS: Content experts (clinicians and methodologists) developed the survey. Domains in the questionnaire include: respondent characteristics, factors influencing the decision to implant a SuAVR, barriers to SuAVR use, and interest in participating in a trial. RESULTS: A total of 66 cardiac surgeons (median duration of practice: 15 years; range 8-20 years) from 18 hospitals across Canada responded to the survey for a response rate of 84%. Surgeons reported that the following patient characteristics increased the likelihood they would choose SuAVR: hostile root (73%), small annular size (55%), high Society of Thoracic Surgery risk score (42%), older age (40%), to support minimally invasive surgery (25%) and redo-operation (23%). The following patient characteristics made surgeons less likely to pursue SuAVR: young age (73%), low STS score (40%), and large annular size (30%). Reported barriers to SuAVR use included: cost (33%), permanent pacemaker risk (27%) and uncertain durability (12%). Of respondents, 73% were interested in participating in a randomized controlled trial comparing SuAVR with transcatheter aortic valve replacement. CONCLUSIONS: The primary reasons for surgeons selecting SuAVR were high surgical risk and anatomical challenges. Cost is a primary factor limiting SuAVR use.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.528
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.001
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 head0.047
GPT teacher head0.319
Teacher spread0.273 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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