Volume 28, Issue 1 (1-2014)                   Med J Islam Repub Iran 2014 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Rezapour M, Khavaninzadeh M. Association between non-matured arterio-venus fistula and blood pressure in hemodialysis patients. Med J Islam Repub Iran 2014; 28 (1) :966-974
URL: http://mjiri.iums.ac.ir/article-1-2569-en.html
Rasoul Akram Hospital, Iran University of Medical Sciences (IUMS), Tehran, Iran. , khavaninzadeh.m@iums.ac.ir
Abstract:   (8270 Views)

  Background : Chronic Kidney Disease (CKD) is a complicated kidney problem causing permanent renal failure in progressive stages. The final stage of CKD is called ESRD in which most accepted management is Hemodialysis (HD). Arterio-Venus Fistula (AVF) is the most practical way of making proper access to the blood circulatory system however, maturation of the AVF is a challenge, since there are number of variables interfering with the whole process. The purpose of this study was to evaluate potentially modifiable factors associated with Maturation Time (MT) after creation of a Vascular Access (VA).

  Methods : In this cross-sectional study, a total of 87 patients referred to the Hasheminejad Kidney Center for AVF creation in 2010 were evaluated. Patients were evaluated before and after the AVF creation and risk factors such as history of blood pressure abnormalities, diabetes and congestive heart failure, as well as the successive development of AVF was studied and finally processed using ‘data mining’ technology.

  Results : The “Decision Trees” indicated the significant impact of the systolic blood pressure (SBP) in the delay of the patient’s AVF maturation. Also, prediction of AVF maturation was made with 70.59% of precision in regard to their BP condition.

  Conclusion : This study demonstrated that monitoring the SBP is one of the important steps in management of the cardiovascular variables producing any delay in the process of the patient’s HD. Also the data mining method can discover the hidden relationship between the patient’s medical conditions in order to predict the potential disorders.

Full-Text [PDF 1162 kb]   (2181 Downloads)    
Type of Study: Original Research | Subject: Nephrology

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.