Matches in SemOpenAlex for { <https://semopenalex.org/work/W3206554013> ?p ?o ?g. }
- W3206554013 endingPage "28" @default.
- W3206554013 startingPage "18" @default.
- W3206554013 abstract "Current Society of Thoracic Surgeons (STS) risk models for predicting outcomes of mitral valve surgery (MVS) assume a linear and cumulative impact of variables. We evaluated postoperative MVS outcomes and designed mortality and morbidity risk calculators to supplement the STS risk score.Data from the STS Adult Cardiac Surgery Database for MVS was used from 2008 to 2017. The data included 383,550 procedures and 89 variables. Machine learning (ML) algorithms were employed to train models to predict postoperative outcomes for MVS patients. Each model's discrimination and calibration performance were validated using unseen data against the STS risk score.Comprehensive mortality and morbidity risk assessment scores were derived from a training set of 287,662 observations. The area under the curve (AUC) for mortality ranged from 0.77 to 0.83, leading to a 3% increase in predictive accuracy compared to the STS score. Logistic Regression and eXtreme Gradient Boosting achieved the highest AUC for prolonged ventilation (0.82) and deep sternal wound infection (0.78 and 0.77) respectively. EXtreme Gradient Boosting performed the best with an AUC of 0.815 for renal failure. For permanent stroke prediction all models performed similarly with an AUC around 0.67. The ML models led to improved calibration performance for mortality, prolonged ventilation, and renal failure, especially in cases of reconstruction/repair and replacement surgery.The proposed risk models complement existing STS models in predicting mortality, prolonged ventilation, and renal failure, allowing healthcare providers to more accurately assess a patient's risk of morbidity and mortality when undergoing MVS." @default.
- W3206554013 created "2021-10-25" @default.
- W3206554013 creator A5018456307 @default.
- W3206554013 creator A5025940525 @default.
- W3206554013 creator A5053607940 @default.
- W3206554013 creator A5060802442 @default.
- W3206554013 creator A5075944300 @default.
- W3206554013 date "2021-10-20" @default.
- W3206554013 modified "2023-09-24" @default.
- W3206554013 title "Machine learning models for mitral valve replacement: A comparative analysis with the Society of Thoracic Surgeons risk score" @default.
- W3206554013 cites W1563433584 @default.
- W3206554013 cites W2075227608 @default.
- W3206554013 cites W2092087236 @default.
- W3206554013 cites W2108349586 @default.
- W3206554013 cites W2115709314 @default.
- W3206554013 cites W2134843796 @default.
- W3206554013 cites W2525984666 @default.
- W3206554013 cites W2551345775 @default.
- W3206554013 cites W2560629614 @default.
- W3206554013 cites W2571536841 @default.
- W3206554013 cites W2604736517 @default.
- W3206554013 cites W2617110182 @default.
- W3206554013 cites W2727650337 @default.
- W3206554013 cites W2790553094 @default.
- W3206554013 cites W2790952035 @default.
- W3206554013 cites W2807444804 @default.
- W3206554013 cites W2888528836 @default.
- W3206554013 cites W2895999714 @default.
- W3206554013 cites W2899525417 @default.
- W3206554013 cites W2911964244 @default.
- W3206554013 cites W2934399013 @default.
- W3206554013 cites W2946711149 @default.
- W3206554013 cites W2986424528 @default.
- W3206554013 cites W3092494313 @default.
- W3206554013 cites W3102476541 @default.
- W3206554013 cites W4297957988 @default.
- W3206554013 doi "https://doi.org/10.1111/jocs.16072" @default.
- W3206554013 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34669218" @default.
- W3206554013 hasPublicationYear "2021" @default.
- W3206554013 type Work @default.
- W3206554013 sameAs 3206554013 @default.
- W3206554013 citedByCount "5" @default.
- W3206554013 countsByYear W32065540132022 @default.
- W3206554013 countsByYear W32065540132023 @default.
- W3206554013 crossrefType "journal-article" @default.
- W3206554013 hasAuthorship W3206554013A5018456307 @default.
- W3206554013 hasAuthorship W3206554013A5025940525 @default.
- W3206554013 hasAuthorship W3206554013A5053607940 @default.
- W3206554013 hasAuthorship W3206554013A5060802442 @default.
- W3206554013 hasAuthorship W3206554013A5075944300 @default.
- W3206554013 hasBestOaLocation W32065540131 @default.
- W3206554013 hasConcept C11783203 @default.
- W3206554013 hasConcept C119857082 @default.
- W3206554013 hasConcept C126322002 @default.
- W3206554013 hasConcept C127413603 @default.
- W3206554013 hasConcept C141071460 @default.
- W3206554013 hasConcept C151956035 @default.
- W3206554013 hasConcept C169258074 @default.
- W3206554013 hasConcept C177713679 @default.
- W3206554013 hasConcept C194828623 @default.
- W3206554013 hasConcept C2777080012 @default.
- W3206554013 hasConcept C2779134260 @default.
- W3206554013 hasConcept C2780645631 @default.
- W3206554013 hasConcept C41008148 @default.
- W3206554013 hasConcept C45804977 @default.
- W3206554013 hasConcept C58471807 @default.
- W3206554013 hasConcept C70153297 @default.
- W3206554013 hasConcept C71924100 @default.
- W3206554013 hasConcept C76318530 @default.
- W3206554013 hasConcept C78519656 @default.
- W3206554013 hasConceptScore W3206554013C11783203 @default.
- W3206554013 hasConceptScore W3206554013C119857082 @default.
- W3206554013 hasConceptScore W3206554013C126322002 @default.
- W3206554013 hasConceptScore W3206554013C127413603 @default.
- W3206554013 hasConceptScore W3206554013C141071460 @default.
- W3206554013 hasConceptScore W3206554013C151956035 @default.
- W3206554013 hasConceptScore W3206554013C169258074 @default.
- W3206554013 hasConceptScore W3206554013C177713679 @default.
- W3206554013 hasConceptScore W3206554013C194828623 @default.
- W3206554013 hasConceptScore W3206554013C2777080012 @default.
- W3206554013 hasConceptScore W3206554013C2779134260 @default.
- W3206554013 hasConceptScore W3206554013C2780645631 @default.
- W3206554013 hasConceptScore W3206554013C41008148 @default.
- W3206554013 hasConceptScore W3206554013C45804977 @default.
- W3206554013 hasConceptScore W3206554013C58471807 @default.
- W3206554013 hasConceptScore W3206554013C70153297 @default.
- W3206554013 hasConceptScore W3206554013C71924100 @default.
- W3206554013 hasConceptScore W3206554013C76318530 @default.
- W3206554013 hasConceptScore W3206554013C78519656 @default.
- W3206554013 hasIssue "1" @default.
- W3206554013 hasLocation W32065540131 @default.
- W3206554013 hasLocation W32065540132 @default.
- W3206554013 hasLocation W32065540133 @default.
- W3206554013 hasOpenAccess W3206554013 @default.
- W3206554013 hasPrimaryLocation W32065540131 @default.
- W3206554013 hasRelatedWork W2066363065 @default.
- W3206554013 hasRelatedWork W2364708368 @default.
- W3206554013 hasRelatedWork W2932411505 @default.