MétaCan
Menu
Back to cohort

Contemporary Trends in Aortic Valve Surgery:. A Single Centre 10-Year Clinical Experience*

2004· article· en· W2111334005 on OpenAlexaff
Naoji Hanayama, Shafie Fazel, Bernard S. Goldman, Peter R. Mitoff, Jeri Sever, Stephen E. Fremes

Bibliographic record

VenueJournal of Cardiac Surgery · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineAortic valveSurgeryGeneral surgeryCardiology

Abstract

fetched live from OpenAlex

The purpose of this study is to present a comprehensive profile of the trends in aortic valve replacement at a single institution over the past decade. Prospectively collected data concerning 873 patients undergoing aortic valve replacement (AVR), with and without coronary artery bypass grafting (CABG), were analysed. The patients were divided into three time periods: period I, (1990 to 1993); period II, (1994 to 1996); and period III, (1997 to 2000). Actuarial survival of AVR patients with and without CABG at 7 years was 82.9 +/- 2.4% and 79.1 +/- 3.3% (p = 0.17), respectively. Actuarial survival at 7 years for stentless, mechanical, and stented valve patients were 89.5 +/- 2.7%, 85.5 +/- 2.8%, and 76.0 +/- 3.2%, respectively. There was a significant difference in survival between the stentless and stented valve groups (p = 0.014). Age (63.8 +/- 12.9 yrs, 66.2 +/- 11.0 yrs, 67.9 +/- 10.3 yrs; p = 0.01), the incidence of peripheral vascular disease (5.1%, 10.8%, 16.6%; p = 0.001), and the extent of coronary artery disease necessitating CABG (34.0%, 38.8%, 41.0%; p = 0.05) have increased significantly in the later time period. However, operative mortality has remained constant (4.7%, 4.8%, 4.5%; p = 0.9). Moreover, perioperative complications have decreased significantly (27.4%, 18.0, 16.0%; p = 0.001). Multivariate analysis identified more recent time period as independent protective factor for early mortality and morbidity (period I, RR 1.00; period II, RR 0.47; period III, RR 0.40).

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)0.001
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 score0.046
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.009
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 head0.062
GPT teacher head0.375
Teacher spread0.312 · 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

Citations11
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cardiac SurgerySame topicCardiac Valve Diseases and TreatmentsFrench-language works237,207