Diagnosis of Knee Osteoarthritis Risk through Abnormal Musculo-postural Features
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Date
2018-01
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Publisher
Ibn Sina Academy of Medieval Medicine & Sciences
Abstract
Background: In several parts of the globe, knee osteoarthritis (KOA) occurs as a painful chronic disease. The aim of the study was to determine the risk factors for musculo-postural abnormalities by detecting abnormal anatomical leg parameters caused by knee-osteoarthritis (KOA). Methods: Baseline data were collected and evaluated from 207 patients aged between 40-65 years (58.94% females) with KOA and an equal number of subjects without-KOA. Anatomical measurements included the gap at the knee between the short head of the biceps femoris and the level of the bed (KGB), diameter of muscles at the thigh (DTM), the calf (DCM) and 4cm above and below the patella (DAP and DBP) and flexion supine, prone and standing (KFS, KFP and KFSt) and extension supine, prone and standing (KES, KEP and KESt) in different postural positions for both legs of both groups using appropriate instruments and Body Mass Index (BMI). The study was also correlated with radiological images. Results: Risk factors for KOA based on abnormal leg anatomical-features were observed with statistical significance (P<0.001) and R2 (97-100%). The present results were evaluated after analyses of anatomical and flexion and extension range of motion measurements in different postural positions for both legs with KOA along with radiological features. The BMI of the experimental group was higher than that of the control group with high statistical significance (P<0.001). Conclusions: Abnormal muscle morphology and musculo-postural-features of the legs may be a suitable diagnostic protocol for the detection of early progression and risk of KOA.
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Keywords
Knee osteoarthritis, Diagnostic protocol, Musculo-postural feature, Risk of KOA, Progression of KOA.
Citation
Ganguly Apurba. Diagnosis of Knee Osteoarthritis Risk through Abnormal Musculo-postural Features. International Archives of BioMedical and Clinical Research. 2018 Jan-Mar; 4(1): 39-46