Predicting risk factors for postoperative coronary artery bypass grafting using logistic regression and CHAID

A. Nabilah, D. Lestari, S. Mardiyati, S. Devila

Research output: Contribution to journalConference articlepeer-review

Abstract

Non-fatal postoperative complications are postoperative morbidity that can affect the patient's functional status and quality of life. Evaluation of postoperative morbidity is the step needed to assess and improve the quality of patient care. Therefore, a method is required in order to predict risk factors in evaluating a patient's postoperative morbidity. After this the results will be used to determine the insurance premiums. In this research, the Logistic Regression are used to know the risk factors that would occur in patients who had undergone Coronary Artery Bypass Grafting (CABG) surgery. Then we use the CHAID method to classify readmission based on patient characteristics. Based on the two analyzes, it can be concluded that the CHAID analysis supports the Logistics analysis, there are two risk factors significantly influence the complications of patients after Coronary Artery Bypass Graft (CABG), namely Sex and Ejection Fraction.

Original languageEnglish
Article number012025
JournalJournal of Physics: Conference Series
Volume1725
Issue number1
DOIs
Publication statusPublished - 12 Jan 2021
Event2nd Basic and Applied Sciences Interdisciplinary Conference 2018, BASIC 2018 - Depok, Indonesia
Duration: 3 Aug 20184 Aug 2018

Keywords

  • Maximum likelihood method
  • Morbidity
  • Risk factors

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