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Record W2160191160 · doi:10.1056/nejmoa1410490

Surgical Treatment of Moderate Ischemic Mitral Regurgitation

2014· article· en· W2160191160 on OpenAlexafffundabout
Peter K. Smith, John D. Puskas, Deborah D. Ascheim, Pierre Voisine, Annetine C. Gelijns, Alan J. Moskowitz, Judy Hung, Michael K. Parides, Gorav Ailawadi, Louis P. Perrault, Michael A. Acker, Michael Argenziano, Vinod H. Thourani, James S. Gammie, Marissa A. Miller, Pierre Pagé, Jessica Overbey, Emilia Bagiella, François Dagenais, Eugene H. Blackstone, Irving L. Kron, Daniel J. Goldstein, Eric A. Rose, Ellen Moquete, Neal Jeffries, Timothy J. Gardner, Patrick T. O’Gara, John H. Alexander, Robert E. Michler

Bibliographic record

VenueNew England Journal of Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsHôpital du Sacré-Cœur de MontréalUniversité de MontréalMontreal Heart InstituteColumbia CollegeInstitut universitaire de cardiologie et de pneumologie de Québec
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood InstituteCanadian Institutes of Health Research
KeywordsMedicineMitral regurgitationBypass graftingCardiologyInternal medicineArteryMitral valve repairRegurgitation (circulation)Mitral valveMitral valve regurgitation

Abstract

fetched live from OpenAlex

BACKGROUND: Ischemic mitral regurgitation is associated with increased mortality and morbidity. For surgical patients with moderate regurgitation, the benefits of adding mitral-valve repair to coronary-artery bypass grafting (CABG) are uncertain. METHODS: We randomly assigned 301 patients with moderate ischemic mitral regurgitation to CABG alone or CABG plus mitral-valve repair (combined procedure). The primary end point was the left ventricular end-systolic volume index (LVESVI), a measure of left ventricular remodeling, at 1 year. This end point was assessed with the use of a Wilcoxon rank-sum test in which deaths were categorized as the lowest LVESVI rank. RESULTS: At 1 year, the mean LVESVI among surviving patients was 46.1±22.4 ml per square meter of body-surface area in the CABG-alone group and 49.6±31.5 ml per square meter in the combined-procedure group (mean change from baseline, -9.4 and -9.3 ml per square meter, respectively). The rate of death was 6.7% in the combined-procedure group and 7.3% in the CABG-alone group (hazard ratio with mitral-valve repair, 0.90; 95% confidence interval, 0.38 to 2.12; P=0.81). The rank-based assessment of LVESVI at 1 year (incorporating deaths) showed no significant between-group difference (z score, 0.50; P=0.61). The addition of mitral-valve repair was associated with a longer bypass time (P<0.001), a longer hospital stay after surgery (P=0.002), and more neurologic events (P=0.03). Moderate or severe mitral regurgitation was less common in the combined-procedure group than in the CABG-alone group (11.2% vs. 31.0%, P<0.001). There were no significant between-group differences in major adverse cardiac or cerebrovascular events, deaths, readmissions, functional status, or quality of life at 1 year. CONCLUSIONS: In patients with moderate ischemic mitral regurgitation, the addition of mitral-valve repair to CABG did not result in a higher degree of left ventricular reverse remodeling. Mitral-valve repair was associated with a reduced prevalence of moderate or severe mitral regurgitation but an increased number of untoward events. Thus, at 1 year, this trial did not show a clinically meaningful advantage of adding mitral-valve repair to CABG. Longer-term follow-up may determine whether the lower prevalence of mitral regurgitation translates into a net clinical benefit. (Funded by the National Institutes of Health and the Canadian Institutes of Health Research; ClinicalTrials.gov number, NCT00806988.).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0000.000

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 head0.018
GPT teacher head0.334
Teacher spread0.316 · 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 designOther design
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

Citations416
Published2014
Admission routes3
Has abstractyes

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