Medical Journal of the Islamic Republic Of Iran
مجله پزشکی جمهوری اسلامی ایران
Med J Islam Repub Iran
Medical Sciences
http://mjiri.iums.ac.ir
2
journal2
1016-1430
2251-6840
8
10.18869/mjiri
14
8888
13
en
jalali
1392
10
1
gregorian
2014
1
1
28
1
online
1
fulltext
en
Association between non-matured arterio-venus fistula and blood pressure in hemodialysis patients
Nephrology
Nephrology
Original Research
Original Research
<p> <strong> Background </strong>: 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). </p><p> <strong> Methods </strong>: 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. </p><p> <strong> Results </strong>: 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. </p><p> <strong> Conclusion </strong>: 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. </p>
Data Mining, ArterioVenus fistula, Blood pressure, Hypertension.
966
974
http://mjiri.iums.ac.ir/browse.php?a_code=A-10-1-747&slc_lang=en&sid=1
Mohammad
Rezapour
mrezapour@srbiau.ac.ir
200319475328460014156
200319475328460014156
No
Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Morteza
Khavaninzadeh
khavaninzadeh.m@iums.ac.ir
200319475328460014157
200319475328460014157
Yes
Rasoul Akram Hospital, Iran University of Medical Sciences (IUMS), Tehran, Iran.