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Record W3092768436 · doi:10.1016/j.jcin.2020.08.037

Transcatheter Mitral Valve Repair in Cardiogenic Shock and Mitral Regurgitation

2020· article· en· W3092768436 on OpenAlexafffund
Richard G. Jung, Trevor Simard, Christopher P. Kovach, Kelsey M. Flint, Creighton W. Don, Pietro Di Santo, Marianna Adamo, Luca Branca, Francesca Valentini, Tomás Benito‐González, Felipe Fernández‐Vázquez, Rodrigo Estévez‐Loureiro, Alessandra Berardini, Nicolina Conti, Claudio Rapezzi, Elena Biagini, Simon Parlow, Risa Shorr, Amos Levi, Ana Manovel, Rosa Cardenal-Piris, José Díaz Fernández, Mony Shuvy, Dan Haberman, Alessandra Sala, Mohamad Alkhouli, Claudia Marini, Marta Bargagna, Davide Schiavi, Paolo Denti, Sinisa Markovic, Nicola Buzzatti, Vincent Chan, Mark Hynes, Thierry Mesana, Marino Labinaz, Federico Pappalardo, Maurizio Taramasso, Benjamin Hibbert

Bibliographic record

VenueJACC: Cardiovascular Interventions · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health ResearchAbbott Vascular
KeywordsCardiogenic shockInterquartile rangeMedicineHazard ratioMitral regurgitationCardiologyInternal medicineHeart failureShock (circulatory)Confidence intervalMortality rateSurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

OBJECTIVES: The aim of this study was to evaluate the outcome of transcatheter mitral valve repair (TMVr) in patients with cardiogenic shock and significant mitral regurgitation (MR). BACKGROUND: Patients in cardiogenic shock with severe MR have a poor prognosis in the setting of conventional medical therapy. Because of its favorable safety profile, TMVr is being increasingly used as an acute therapy in this population, though its efficacy remains unknown. METHODS: A multicenter, collaborative, patient-level analysis was conducted. Patients with cardiogenic shock and moderate to severe (3+) or severe (4+) MR who were not surgical candidates were treated with TMVr. The primary outcome was in-hospital mortality. Secondary outcomes included 90-day mortality, heart failure (HF) hospitalization, and the combined event rate of 90-day mortality and HF hospitalization following dichotomization by TMVr device success. RESULTS: Between January 2011 and February 2019, 141 patients across 14 institutions met the inclusion criteria. In-hospital mortality occurred in 22 patients (15.6%), at 90 days in 38 patients (29.5%), and at one year in 55 patients (42.6%). Median length of hospital stay following TMVr was 10 days (interquartile range: 6 to 20 days). HF hospitalization occurred in 26 patients (18.4%) at a median of 73 days (interquartile range: 26 to 546 days). When stratified by TMVr procedural results, successful TMVr reduced rates of in-hospital mortality (hazard ratio [HR]: 0.36; 95% confidence interval [CI]: 0.13 to 0.98; p = 0.04), 90-day mortality (HR: 0.36; 95% CI: 0.16 to 0.78; p = 0.01), and the composite of 90-day mortality and HF hospitalization (HR: 0.41; 95% CI: 0.19 to 0.90; p = 0.03). CONCLUSIONS: TMVr may improve short- and intermediate-term mortality in high-risk patients with cardiogenic shock and moderate to severe MR. Randomized studies are needed to definitively establish MR as a therapeutic target in patients with cardiogenic shock.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.035
GPT teacher head0.323
Teacher spread0.288 · 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

Citations97
Published2020
Admission routes2
Has abstractyes

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