Cargando…

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

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 Jia...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Dan, Hu, Zhijun, Tang, Zhanying, Li, Pan, Yuan, Weina, Li, Fangfang, Chen, Qian, Min, Wen, Zhao, Changwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10663826/
https://www.ncbi.nlm.nih.gov/pubmed/38027808
http://dx.doi.org/10.1016/j.heliyon.2023.e21501
_version_ 1785138485517090816
author Liu, Dan
Hu, Zhijun
Tang, Zhanying
Li, Pan
Yuan, Weina
Li, Fangfang
Chen, Qian
Min, Wen
Zhao, Changwei
author_facet Liu, Dan
Hu, Zhijun
Tang, Zhanying
Li, Pan
Yuan, Weina
Li, Fangfang
Chen, Qian
Min, Wen
Zhao, Changwei
author_sort Liu, Dan
collection PubMed
description 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.
format Online
Article
Text
id pubmed-10663826
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-106638262023-10-27 Early risk assessment and prediction model for osteoporosis based on traditional Chinese medicine syndromes Liu, Dan Hu, Zhijun Tang, Zhanying Li, Pan Yuan, Weina Li, Fangfang Chen, Qian Min, Wen Zhao, Changwei Heliyon Research Article 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. Elsevier 2023-10-27 /pmc/articles/PMC10663826/ /pubmed/38027808 http://dx.doi.org/10.1016/j.heliyon.2023.e21501 Text en © 2023 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Liu, Dan
Hu, Zhijun
Tang, Zhanying
Li, Pan
Yuan, Weina
Li, Fangfang
Chen, Qian
Min, Wen
Zhao, Changwei
Early risk assessment and prediction model for osteoporosis based on traditional Chinese medicine syndromes
title Early risk assessment and prediction model for osteoporosis based on traditional Chinese medicine syndromes
title_full Early risk assessment and prediction model for osteoporosis based on traditional Chinese medicine syndromes
title_fullStr Early risk assessment and prediction model for osteoporosis based on traditional Chinese medicine syndromes
title_full_unstemmed Early risk assessment and prediction model for osteoporosis based on traditional Chinese medicine syndromes
title_short Early risk assessment and prediction model for osteoporosis based on traditional Chinese medicine syndromes
title_sort early risk assessment and prediction model for osteoporosis based on traditional chinese medicine syndromes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10663826/
https://www.ncbi.nlm.nih.gov/pubmed/38027808
http://dx.doi.org/10.1016/j.heliyon.2023.e21501
work_keys_str_mv AT liudan earlyriskassessmentandpredictionmodelforosteoporosisbasedontraditionalchinesemedicinesyndromes
AT huzhijun earlyriskassessmentandpredictionmodelforosteoporosisbasedontraditionalchinesemedicinesyndromes
AT tangzhanying earlyriskassessmentandpredictionmodelforosteoporosisbasedontraditionalchinesemedicinesyndromes
AT lipan earlyriskassessmentandpredictionmodelforosteoporosisbasedontraditionalchinesemedicinesyndromes
AT yuanweina earlyriskassessmentandpredictionmodelforosteoporosisbasedontraditionalchinesemedicinesyndromes
AT lifangfang earlyriskassessmentandpredictionmodelforosteoporosisbasedontraditionalchinesemedicinesyndromes
AT chenqian earlyriskassessmentandpredictionmodelforosteoporosisbasedontraditionalchinesemedicinesyndromes
AT minwen earlyriskassessmentandpredictionmodelforosteoporosisbasedontraditionalchinesemedicinesyndromes
AT zhaochangwei earlyriskassessmentandpredictionmodelforosteoporosisbasedontraditionalchinesemedicinesyndromes