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Establishment of a Discriminant Model for 40 ~ 65 Years Old Postmenopausal Osteoporosis Women Based on Generalized Partial Linear Model
Author(s): 
Pages: 837-839
Year: Issue:  6
Journal: Chinese Journal of Health Statistics

Keyword:  绝经后骨质疏松症危险因素中医证候广义偏线性模型判别模型;
Abstract: 目的 建立基于广义偏线性模型(generalized partial linear model,GPLM)的,包括危险因素和中医证候要素内容的绝经后骨质疏松症(postmenopausal osteoporosis,PMOP)风险判别模型.方法 在获取1740例社区PMOP高危人群危险因素及证候问卷调查数据基础上,筛选出与PMOP发病相关的重要危险因素和中医症状为协变量,以骨密度定性诊断为结局变量,建立基于GPLM的PMOP判别模型.结果 GPLM模型线性部分参数估计提示:是否绝经、体重指数、下肢抽筋、下肢骨痛、绝经年限(线性效应)具有统计意义(P<0.05);模型非线性部分参数估计提示:绝经年限(非线性效应)具有统计意义(P<0.05).与logistic回归模型相比,拟合GPLM模型时加入了“绝经年限”的非线性效应,其A UC值为0.7971,具有统计学意义(x2=21.9162,P <0.001).结论 绝经年限与PMOP发病之间存在非线性效应.将西医危险因素和中医症状相结合,建立基于GPLM的PMOP判别模型,反映病证结合特点,与logistic回归模型相比,具有更好的判别准确性.
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