MétaCan
Menu
Back to cohort
Record W2106671473 · doi:10.1016/j.euje.2006.12.009

Effects of surgery on ischaemic mitral regurgitation: A prospective multicenter registry (SIMRAM registry)

2007· article· en· W2106671473 on OpenAlexaff
Patrizio Lancellotti, Erwan Donal, Bernard Cosyns, Jean‐Luc Monin, Éric Brochet, Alain Berrebi, Philippe Pîbarot, Christophe Chauvel, Christian Hassager

Bibliographic record

VenueEuropean Journal of Echocardiography · 2007
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsHôpital Saint-François d'Assise
Fundersnot available
KeywordsMedicineCardiologyInternal medicineMitral regurgitationCoronary artery bypass surgeryIschaemic heart diseaseSurgeryArtery

Abstract

fetched live from OpenAlex

AIMS: Functional ischaemic mitral regurgitation (IMR) is common in patients with ischaemic left ventricular dysfunction undergoing coronary artery bypass surgery. Although the presence of IMR negatively affects prognosis, the additional benefit of valve repair is debated, particularly with mild IMR at rest. Exercise echocardiography may help identify a subset of patients at higher risk of cardiovascular events by revealing the dynamic component of IMR. METHODS: A large prospective, multicentre, non-randomized registry is designed to evaluate the effects of surgery on IMR at rest and on its dynamic component at exercise (z). SIMRAM will enrol approximately 550 patients with IMR in up to 17 centres with clinical and exercise follow-up for 1 year. Three sets of outcomes will be prospectively assessed and several hypotheses will be tested including determinants of adverse outcome and progressive left ventricular remodeling, efficacy of treatment and role of ischaemia on the dynamic consequences of IMR. Enrolment began in November 2006 and is expected to end by early 2008.

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)0.000
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 score0.018
Threshold uncertainty score0.794

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.005
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 head0.011
GPT teacher head0.285
Teacher spread0.274 · 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

Citations17
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of EchocardiographySame topicCardiac Valve Diseases and TreatmentsFrench-language works237,207