The Prevalence of Pathologies Causing Low Back Pain Using Magnetic Resonance Imaging for Categorization
Received Date: Mar 22, 2021 / Accepted Date: Apr 05, 2021 / Published Date: Apr 12, 2021
Abstract
Objective: Low back pain (LBP) is one of the top ten causes of visits to hospitals. Literature review shows that 84% of people have low back pain at some stages of their lives. Therefor the present research study was conducted to find out the prevalence of pathologies causing low back pain using Magnetic Resonance Imaging.
Methods: This was a cross-sectional study conducted in a private tertiary care hospital Peshawar. The sample size was 142, calculated by Rao Soft calculator. The study was conducted during May-August 2020. Data were collected from patients coming to the radiology department for lumber scan MRI and analysed by SPSS version 22.
Results: A total of 142 patients having low back pain including 73 male and 69 females were examined. Degenerative disc diseases (82.3%) were the commonest pathologies. There were a total of 117(82.3%) cases of degenerative disc disease, 09 (6.33%) cases of the traumatic lesion, 08 (5.63%) cases of the congenital lesion, and 5 (3.5%) patients with neoplastic lesions. In this study, there were 44 cases of spinal stenosis, 68 cases of nerve compression. The commonest type of herniation was disc bulge (81.30%) and the most affected lumbar vertebral level by disc bulge was LV4/LV5.
Conclusions: This population-based study shows the prevalence of pathologies causing low back. Males were more affected as compared to females and people with Middle Ages were at increased risk of experiencing low back pain. Degenerative disc diseases (82.3%) were the commonest pathologies, followed by traumatic lesion (6.33%), congenital lesions (5.63%), and neoplastic lesions (3.52%). Future studies with long-term follow-up for determining the benefits of treatments are warranted.
Citation: Yousof M, Din RU, Ahmad M, Khattak S, Ali S (2021) The Prevalence of Pathologies Causing Low Back Pain Using Magnetic Resonance Imaging for Categorization. OMICS J Radiol 10: 323. Doi: 10.4172/2167-7964.1000323
Copyright: © 2021 Yousof M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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