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Estimation of low bone mass using forearm and calcaneum bone mineral density in young Indian population

机译:印度年轻人中使用前臂和跟骨骨矿物质密度估算低骨量

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“Osteoporosis” is the state of an individual having low bone mineral density (BMD) and in this way it get to be distinctly weaker and inclined to break with no significant injury. In India, many individuals are experiencing this condition. Aim and objectives: The Main aim of this study to predict the future low bone mass in younger adults using Peripheral dual x-ray absorptiometry and also to find the co-relational aspect of both genders with forearm and calcaneum bone mineral density measurements. Materials and methods: In this study 72, younger adults aged ranged from 18-25 years were incorporated. A grown-up matured over 25 years were avoided. In every subject, BMD of Forearm and calcaneum were measured by (pDXA). The back propagation neural network classifier is used in the diagnosing of low bone mass and Statistical tool was used to find the co-relational aspect of various BMD measurements. Results: The both calcaneum BMD were strongly correlated (p<;0.05) with weight and body mass index of men, whereas in women group the left calcaneum BMD was correlated with body height at the level of p<;0.05. The accuracy of the classifier was found to be 88.3 % and 97.6% with left forearm and right calcaneum BMD in both genders. Conclusion: The result suggest calcaneum BMD measured by pDXA shows statistically high significant correlation with demographic features of both genders and it will help in the evaluation of low bone mass.
机译:“骨质疏松症”是一种具有低骨矿物质密度(BMD)的人的状态,因此,其骨质明显变弱,容易骨折而无明显伤害。在印度,许多人都遇到这种情况。目的和目的:本研究的主要目的是使用周边双X线吸收法预测年轻成年人的未来低骨量,并通过前臂和跟骨骨矿物质密度测量来发现两性之间的相互关系。材料和方法:在这项研究中,纳入了年龄介于18至25岁之间的年轻成年人。避免在25年以上长大的成年人。在每个受试者中,通过(pDXA)测量前臂和跟骨的BMD。反向传播神经网络分类器用于诊断低骨量,而统计工具则用于查找各种BMD测量值的相互关系。结果:两个跟骨的BMD与男性的体重和体重指数密切相关(p <; 0.05),而在女性组,左跟骨的BMD与身高相关,p <; 0.05。男女左前臂骨和右跟骨骨密度的分类器的准确度分别为88.3%和97.6%。结论:结果表明,pDXA测量的跟骨骨密度与性别特征在统计学上高度相关,这将有助于评估低骨量。

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