Early risk assessment and prediction model for osteoporosis based on traditional Chinese medicine syndromes

基于中医证候的骨质疏松症早期风险评估和预测模型

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Abstract

OBJECTIVE: To evaluate the risk factors of osteoporosis and establish a risk prediction model based on routine clinical information and traditional Chinese medicine (TCM) syndromes. METHODS: Adults aged 30-82 who lived in 12 grass-roots communities or rural towns in Shanghai, Jilin Province, and Jiangsu Province from December 2019 to January 2022 through a multi-stage sampling method were included in this study. The risk factors and risk prediction of osteoporosis in women and men were explored and established by univariate analysis and multivariate logistic regression model. ROC curve and Hosmer-Lemeshow goodness-of-fit test were used to evaluate the prediction model. RESULTS: A total of 3000 subjects including 2243 females (75 %) and 757 males (25 %) were included in this study. The logistic prediction model of osteoporosis in women was Logit (P) = -2.946 + 0.960 (age ≥50 years old) + 0.633 (BMI ≥24 kg/m(2)) - 0.545 (daily exposure to sunlight >30 min) + 0.519 (no intake of dairy products) + 0.827 (coronary heart disease) + 0.383 (lumbar disc herniation) + 0.654 (no intake of calcium tablets and vitamin D) - 0.509 (insomnia) + 0.580 (flushed face and congested eyes) + 1.194 (thready and rapid pulse) + 1.309 (sunken and slow pulse). The logistic prediction model of osteoporosis in men was Logit (P) = -1.152-0.644 (daily exposure to sunlight >30 min) + 0.975 (no intake of calcium tablets and vitamin D) - 0.488 (insomnia). The area under the ROC curve (AUC) of female and male osteoporosis prediction models was 0.743 and 0.679, respectively. The Hosmer-Lemeshow goodness-of-fit test was >0.5. CONCLUSIONS: There are some significant differences in risk factors between female and male patients with osteoporosis. The risk of osteoporosis are found to be associated with TCM syndromes, and osteoporosis risk prediction models based on routine clinical information and TCM syndrome is effective.

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