Progression to myocardial infarction short-term death based on interval sequential pattern mining

Yang Sheng Wu, David Taniar*, Kiki Adhinugraha, Chao Hung Wang, Tun Wen Pai*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

2 Scopus citations

Abstract

Background: Myocardial infarction (MI) is one of the significant cardiovascular diseases (CVDs). According to Taiwanese health record analysis, the hazard rate reaches a peak in the initial year after diagnosis of MI, drops to a relatively low value, and maintains stable for the following years. Therefore, identifying suspicious comorbidity patterns of short-term death before the diagnosis may help achieve prolonged survival for MI patients. Methods: Interval sequential pattern mining was applied with odds ratio to the hospitalization records from the Taiwan National Health Insurance Research Database to evaluate the disease progression and identify potential subjects at the earliest possible stage. Results: Our analysis resulted in five disease pathways, including “diabetes mellitus,” “other disorders of the urethra and urinary tract,” “essential hypertension,” “hypertensive heart disease,” and “other forms of chronic ischemic heart disease” that led to short-term death after MI diagnosis, and these pathways covered half of the cohort. Conclusion: We explored the possibility of establishing trajectory patterns to identify the high-risk population of early mortality after MI.

Original languageEnglish
Article number394
Pages (from-to)394
JournalBMC Cardiovascular Disorders
Volume23
Issue number1
DOIs
StatePublished - 10 08 2023

Bibliographical note

© 2023. BioMed Central Ltd., part of Springer Nature.

Keywords

  • Disease trajectory
  • Interval sequential pattern mining
  • Short-term death
  • myocardial infarction
  • Myocardial Infarction
  • Comorbidity
  • Humans
  • Risk Factors
  • Myocardial Ischemia/epidemiology
  • Hypertension/epidemiology

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