Incorporating intra-operative medication information for prediction of post-operative atrial fibrillation

Ethan M.I. Johnson, Jingzhi Yu, Yu Deng, David S. Melnick, Sukhveer S. Sandhu, Farhad Ghamsari, Mozziyar Etemadi, Abel N. Kho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study aimed to construct and evaluate a novel prediction model for postoperative atrial fibrillation (PoAF) with the addition of intraoperative medications. The study patient population included 4731 patients who underwent CABG surgery, of which 1363 developed PoAF, and the prediction methods included three logistic regression models. Multivariate logistic regression was performed with traditional clinical variables only for the first model, intraoperative medications added in the second model, and a subset of all variables chosen by the Least Absolute Shrinkage and Selection Operator (LASSO) in the third model. Age and prior AF diagnosis were consistently the strongest predictors for PoAF across all three models. The specific intra-operative medications moderately improved predictive accuracy as compared to the clinical feature-only model.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Healthcare Informatics, ICHI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538691380
DOIs
StatePublished - Jun 2019
Event7th IEEE International Conference on Healthcare Informatics, ICHI 2019 - Xi'an, China
Duration: Jun 10 2019Jun 13 2019

Publication series

Name2019 IEEE International Conference on Healthcare Informatics, ICHI 2019

Conference

Conference7th IEEE International Conference on Healthcare Informatics, ICHI 2019
Country/TerritoryChina
CityXi'an
Period6/10/196/13/19

Keywords

  • Atrial fibrillation
  • Cardiac artery bypass graft surgery
  • Postoperative complication arrhythmia
  • Prediction model

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Health Informatics
  • Biomedical Engineering

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