Official publication of Rawalpindi Medical University
Frequency of branching pattern variation of the renal artery in a subset of Karachi population: A Study on Multi-Detector Computed Tomography

Supplementary Files

PDF

How to Cite

1.
Mohiuddin M, Khan RN, Ahmed SB, Lakhani M, Sughra A, Hassan N. Frequency of branching pattern variation of the renal artery in a subset of Karachi population: A Study on Multi-Detector Computed Tomography . JRMC [Internet]. 2024 Jun. 29 [cited 2024 Jul. 21];28(2). Available from: http://www.journalrmc.com/index.php/JRMC/article/view/2174

Abstract

Abstract

Objective: This study was conducted to determine the frequency of early branching patterns of renal arteries in a subset of Karachi.

Method: This was a cross-sectional study, conducted in  Ziauddin University Hospital, Clifton campus, Karachi.  This was a prospective study conducted from June 2017 to July 2018. The sample size was calculated by using a 95 % confidence interval and study participants were included through consecutive sampling. A total of 250 participants (500 kidneys) aged 21 to 60 years and serum creatinine of ≤ 1.3 mg /dl were included in the study. All CT examinations were performed on an MDCT scanner (Alexion 16 slicer, Japan) in the arterial phase.

Results: In this study, among a total of 250 study participants, 52 % (129 out of 250) were males and 48 % (121 out of 250) were females. Out of a total of 250 study participants, renal artery variation of pre-hilar early branching was found to be 9.2% (23) in individuals. On the right side early was found to be 4% and 5.2%. The length of the main renal artery in early branching measured was 11.0 ± 2.05 mm.

Conclusion: This study concluded that the frequency of early branching of renal arteries was 9.2% in a subset of the Karachi population.

https://doi.org/10.37939/jrmc.v28i2.2174
Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Copyright (c) 2024 Maria Mohiuddin, Rosheena Nabeel Khan, Syeda Bushra Ahmed, Mubina Lakhani, Amatul Sughra, Nuzhat Hassan