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Record W4281643487 · doi:10.4244/eij-d-21-00846

Delayed hospitalisation for heart failure after transcatheter repair or medical treatment for secondary mitral regurgitation: a landmark analysis of the MITRA-FR trial

2022· article· en· W4281643487 on OpenAlexaff
Guillaume Leurent, Vincent Auffret, Erwan Donal, Hervè Corbineau, Daniel Grinberg, Guillaume Bonnet, Pierre-Yves Leroux, Patrice Guérin, Fabrice Wautot, Thierry Lefèvre, David Messika–Zeitoun, Bernard Iung, Xavier Armoiry, Jean‐Noël Trochu, Florent Boutitie, Jean-François Obadia

Bibliographic record

VenueEuroIntervention · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsWilfrid Laurier UniversityUniversity of Ottawa
Fundersnot available
KeywordsMedicineHazard ratioClinical endpointMitraClipConfidence intervalMitral regurgitationSurgeryRandomized controlled trialConcordanceHeart failureEjection fractionInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In the MITRA-FR trial, transcatheter mitral valve repair (TMVR) was not associated with a 2-year clinical benefit in patients with secondary mitral regurgitation (SMR). AIMS: This landmark analysis aimed at investigating a potential reduction of the hospitalisation rate for heart failure (HF) between 12 and 24 months after inclusion in the MITRA-FR trial in patients randomised to the intervention group (TMVR with the MitraClip device), as compared with patients randomised to the control group (guideline-directed medical therapy [GDMT]). METHODS: The MITRA-FR trial randomised 307 patients with SMR for TMVR on top of GDMT (TMVR group; n=152) or for GDMT alone (control group; n=155). We conducted a 12-month landmark analysis in surviving patients who were not hospitalised for HF within the first 12 months of follow-up. The primary endpoint was the 1-year cumulative number of HF hospitalisations. RESULTS: A total of 140 patients (TMVR group: 67; GDMT group: 73) were selected for this landmark analysis with similar characteristics at inclusion in the trial. The primary endpoint was 28 events per 100 patient-years in the TMVR group, as compared with 60 events per 100 patient-years in the GDMT group (hazard ratio [HR] 0.46, 95% confidence interval [CI]: 0.20-1.02; p=0.057). CONCLUSIONS: In this landmark analysis of the MITRA-FR trial, the cumulative rate of HF hospitalisation between 12 and 24 months among patients treated with TMVR on top of GDMT was approximately half as many as those of patients treated with GDMT alone, a difference which did not reach statistical significance in the setting of a low number of events.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.010
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 head0.020
GPT teacher head0.342
Teacher spread0.323 · 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.

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

Citations4
Published2022
Admission routes1
Has abstractyes

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