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Record W2063306599 · doi:10.5114/aoms.2013.35479

One-year hemodynamic comparison of Perimount Magna with St Jude Epic aortic bioprostheses

2013· article· en· W2063306599 on OpenAlexaff
Jerzy Bobiarski, Andrew Newcomb, Abdelsalam M. Elhenawy, Manjula Maganti, Joanne Bos, Suzanne Hemeon, Vivek Rao

Bibliographic record

VenueArchives of Medical Science · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineEPICHemodynamicsSurgeryCardiologyRetrospective cohort studyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Cardiac surgeons are using more bioprosthetic valves due to the ageing population as well as to improvements that have been made to these implants. We sought to compare the 1-year hemodynamics of two commercially available valves by echocardiographic parameters. MATERIAL AND METHODS: Retrospective review of our institutional database revealed 69 patients who received either Perimount Magna (n = 33) or St Jude Epic (n = 36) valves in the aortic position with no other valve surgery between June 2004 and March 2006. All patients received transthoracic echocardiography at 1 year. Comparisons between groups were made at baseline and at 1-year follow-up. In addition, a pairwise comparison was performed in each patient to determine the change in echocardiographic parameters between baseline and follow-up. RESULTS: Mean implanted valve size was similar (Magna 24.3 ±2.0 mm vs. Epic 24.1 ±2.2 mm). Pre- and intraoperative patient variables were similar between the two groups. There were lower peak and mean pressure gradients in the Magna group, both at discharge and one year after surgery. This correlated with a larger indexed effective orifice area (Magna 0.8 ±0.2 cm(2)/m(2) vs. Epic 0.67 ±0.2 cm(2)/m(2), p = 0.02). In spite of these findings, left ventricular mass regression was not different. CONCLUSIONS: These findings suggest that in a series with relatively low indexed effective orifice areas, the peak and mean gradients obtained were acceptable. More clinical follow-up of these patients is required to assess the true impact of prosthesis patient mismatch.

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 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)0.003
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
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.017
GPT teacher head0.351
Teacher spread0.334 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2013
Admission routes1
Has abstractyes

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