ArticleInnovations (Philadelphia, Pa.)
Learning Curve Analysis of Minimally Invasive Mitral Valve Repair.
Article in Innovations (Philadelphia, Pa.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Commentary: The End of the Learning Curve Is the Beginning of Good Judgment.Innovations (Philadelphia, Pa.)Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivePrevious learning curve analyses of minimally invasive mitral valve (MV) repair have focused largely on early safety outcomes without including detailed mitral repair quality outcomes. This study investigates the learning curve of minimally invasive MV repair over a 15-year experience, focused on clinical outcomes and evidence-based technical failure endpoints.
methodsAll MV repair operations were performed by a single surgeon between May 2008 and February 2023. Patient data were stratified into 3 groups of tertiles. Failure endpoints were defined as postrepair residual mitral regurgitation ≥ mild and a 30-day composite outcome. Cumulative log-likelihood curves were constructed for minimally invasive MV repair using the primary outcomes as technical failure endpoints. Control limits were determined using previous analyses of the Society of Thoracic Surgeons database.
resultsA total of 362 consecutive patients across 15 years were included. Across tertiles, there was a significant trend toward shorter cross-clamp time (
conclusionsThe estimated number of operations to achieve optimal repair outcomes and durability is ~60 to 85 patients. These data can improve the design of surgical training competencies, beyond avoidance of complications, and instead focus the learning curve on what is necessary to achieve optimal mitral repair outcomes.
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