Abstract
Abstract 15895: Machine Learning Algorithms to Predict Major Adverse Cardiovascular Events in Patients Undergoing Orthotopic Liver Transplantation: A Retrospective Cohort Study
Circulation (New York, N.Y.), Vol.142(Suppl_3), pp.A15895-A15895
11/17/2020
DOI: 10.1161/circ.142.suppl_3.15895
Abstract
Abstract only
Background:
Post-transplant major adverse cardiovascular events (MACE) are amongst the leading cause of death amongst orthotopic liver transplant(OLT) recipients. Despite years of guideline directed therapy, there are limited data on predictors of post-OLT MACE. We assessed if machine learning algorithms (MLA) can predict MACE and all-cause mortality in patients undergoing OLT.
Methods:
We tested three MLA: support vector machine, extreme gradient boosting(XG-Boost) and random forest with traditional logistic regression for prediction of MACE and all-cause mortality on a cohort of consecutive patients undergoing OLT at our center between 2008-2019. The cohort was randomly split into a training (80%) and testing (20%) cohort. Model performance was assessed using c-statistic or AUC.
Results:
We included 1,459 consecutive patients with mean ± SD age 54.2 ± 13.8 years, 32% female who underwent OLT. There were 199 (13.6%) MACE and 289 (20%) deaths at a mean follow up of 4.56 ± 3.3 years. The random forest MLA was the best performing model for predicting MACE [AUC:0.78, 95% CI: 0.70-0.85] as well as mortality [AUC:0.69, 95% CI: 0.61-0.76], with all models performing better when predicting MACE vs mortality. See Table and Figure.
Conclusion:
Random forest machine learning algorithms were more predictive and discriminative than traditional regression models for predicting major adverse cardiovascular events and all-cause mortality in patients undergoing OLT. Validation and subsequent incorporation of MLA in clinical decision making for OLT candidacy could help risk stratify patients for post-transplant adverse cardiovascular events.
Details
- Title: Subtitle
- Abstract 15895: Machine Learning Algorithms to Predict Major Adverse Cardiovascular Events in Patients Undergoing Orthotopic Liver Transplantation: A Retrospective Cohort Study
- Creators
- vardhmaan jain - Cleveland ClinicVikram Sharma - Cleveland ClinicAgam Bansal - Cleveland ClinicCerise Kleb - Cleveland, OHChirag Sheth - Cleveland ClinicCristiano Quintini - Cleveland ClinicJacek Cywinski - Cleveland, OHMaan Fares - Cleveland Clinic
- Resource Type
- Abstract
- Publication Details
- Circulation (New York, N.Y.), Vol.142(Suppl_3), pp.A15895-A15895
- Publisher
- LIPPINCOTT WILLIAMS & WILKINS; PHILADELPHIA
- DOI
- 10.1161/circ.142.suppl_3.15895
- ISSN
- 0009-7322
- eISSN
- 1524-4539
- Language
- English
- Date published
- 11/17/2020
- Academic Unit
- Internal Medicine
- Record Identifier
- 9984808211802771
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