Deep Vein Thrombosis Predisposing Factors Analysis Using Association Rules Mining

  • Muthanna D.R. AL-Assal Lecturer/Dept. of Surgery , college of Al-Kindy medical college-Baghdad University.
Keywords: DVT risk factors, analysis of DVT risk factors, Data mining and DVT

Abstract

Background: DVT is a very common problem with a very serious complications like pulmonary embolism (PE) which carries a high mortality,and many other chronic and annoying complications ( like chronic DVT, post-phlebitic syndrome, and chronic venous insufficiency) ,and it has many risk factors that affect its course, severity ,and response to treatment.
Objectives: Most of those risk factors are modifiable, and a better understanding of the relationships between them can be beneficial for better assessment for liable pfatients , prevention of disease, and the effectiveness of our treatment modalities. Male to female ratio was nearly equal , so we didn’t discuss the gender among other risk factors.
Type of the study:A cross- sectional study.
Methods: Data taken from 114 patients with DVT were analyzed by association rules mining.Immobility was the most important risk factor.
Results: Smoking add more risk to immobile, post operative patient. Age per se has no effect.100% of patients with long bone fracture, were immobile. Fever occurred in one third of post operative patients who develop DVT. Conclusions: Association rules mining allow better and faster analysis of more data with an interactive powerful system, which saves time and effort, and discovers the relations among many factors to one or more than one factors. So, we use this method for analysis in this study, and we get the above mentioned relations, which are important for the future management of DVT.

Published
2018-05-06