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Record W2416812555

Hemodynamic performance on exercise: comparison of a stentless and stented biological aortic valve replacement.

2004· article· en· W2416812555 on OpenAlexaboutno aff
John B. Chambers, Helen Rimington, Ronak Rajani, Fiona Hodson, Christopher Blauth

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHemodynamicsCardiologyInternal medicineAortic valve replacementAortic valveRest (music)Stenosis
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND AND AIM OF THE STUDY: Although stentless valves are expected to be hemodynamically superior to stented valves, the results of comparative trials have been inconsistent. The study aim was to compare hemodynamic function at rest and on exercise in 50 stentless and stented biological replacement aortic valves METHODS: Twenty-one patients with a Toronto stentless porcine valve and 29 with a Perimount stented bovine pericardial valve were exercised using a bicycle ergometer. Echocardiography was performed before, and during exercise testing. RESULTS: Patients with either valve type were exercised to a similar degree. Transaortic resistance was slightly lower in the Perimount compared with the Toronto at rest (p = 0.03) and at peak exercise (p = 0.04), and flow was higher in the Perimount at rest (p = 0.007), but not at peak exercise. There were no significant differences between the valve types in peak velocity, mean pressure difference or effective orifice area either at rest or on peak exercise. CONCLUSION: There were no clinically significant differences in hemodynamic function between the stented and stentless biological valves chosen for comparison either at rest or during bicycle exercise.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.030
GPT teacher head0.311
Teacher spread0.281 · 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

Citations24
Published2004
Admission routes1
Has abstractyes

Explore more

Same venuePubMed→Same topicCardiac Valve Diseases and Treatments→French-language works237,207→