作为疾病风险评估的量化工具,疾病预测模型有助于识别高危人群,为健康管理提供参考依据,而非酒精性脂肪性肝病(NAFLD)预测模型研究尚未引起中国肝病健康管理领域研究者的充分关注。本文针对性地在PubMed、Web of Science、中国知网等数...作为疾病风险评估的量化工具,疾病预测模型有助于识别高危人群,为健康管理提供参考依据,而非酒精性脂肪性肝病(NAFLD)预测模型研究尚未引起中国肝病健康管理领域研究者的充分关注。本文针对性地在PubMed、Web of Science、中国知网等数据库进行了文献查阅,得到8种NAFLD预测模型,分别是脂肪肝指数(FLI)、肝脂肪变性指数(HSI)、肝脂肪百分比、Framingham脂肪变性指数(FSI)、ZJU指数、NAFLD筛查评分(NSS)、Young Jin Park模型、Mika Aizawa模型。通过归纳上述8种NAFLD预测模型的建模方法、模型的质量表现、模型的表达及应用现状发现,Logistic回归分析是主要的建模方法,模型区分度较好,模型多采取内部验证,NAFLD预测模型的研究还存在较大的开发空间。展开更多
OBJECTIVE:To summarize the potential characteristics of convalescent patients with coronavirus disease 2019(COVID-19)in China based on emerging clinical tongue data and guide the treatment and recovery of COVID-19 pat...OBJECTIVE:To summarize the potential characteristics of convalescent patients with coronavirus disease 2019(COVID-19)in China based on emerging clinical tongue data and guide the treatment and recovery of COVID-19 patients from the perspective of Traditional Chinese Medicine tongue diagnosis.METHODS:In this study,we developed and validated radiomics-based and lab-based methods as a novel approach to provide individualized pretreatment evaluation by analyzing different features to mine the orderliness behind tongue data of convalescent patients.In addition,this study analyzed the tongue features of convalescent patients from clinical tongue qualitative values,including thick and thin,fur,peeling,fat and lean,tooth marks and cracked,and greasy and putrid fur.RESULTS:We included 2164 tongue images in total(34%from day 0,35.4%from day 14 and 30.6%from day 28)from convalescent patients.The significance results are shown as follows.Firstly,as the recovery time prolongs,the L average values of tongue and coat decrease from 60.21 to 57.18 and from 60.06 to 57.03 respectively.Secondly,the decrease of abnormality rate of tongue coat,included greasy tongue fur,putrid fur,teeth-mark,thick-thin fur,are of significant statistical difference(P<0.05).Thirdly,the average value of gray-level cooccurrence matrices increases from 0.173 to 0.194,the average value of entropy increases from 0.606 to 0.665,the average value of inverse difference normalized decrease from 0.981 to 0.979,and the average value of dissimilarity decrease from 0.1576 to 0.1828.The details of other radiomics features are describe in results section.CONCLUSIONS:Our experiment shows that patients in different recovery periods have a relationship with quantitative values of tongue images,including L color space of the tongue and coat radiomics features analysis.This relationship can help clinical doctors master the recovery and health of patients as soon as possible and improve their understanding of the potential mechanisms underlying the dynamic changes and mechanisms underlying COVID-19.展开更多
文摘作为疾病风险评估的量化工具,疾病预测模型有助于识别高危人群,为健康管理提供参考依据,而非酒精性脂肪性肝病(NAFLD)预测模型研究尚未引起中国肝病健康管理领域研究者的充分关注。本文针对性地在PubMed、Web of Science、中国知网等数据库进行了文献查阅,得到8种NAFLD预测模型,分别是脂肪肝指数(FLI)、肝脂肪变性指数(HSI)、肝脂肪百分比、Framingham脂肪变性指数(FSI)、ZJU指数、NAFLD筛查评分(NSS)、Young Jin Park模型、Mika Aizawa模型。通过归纳上述8种NAFLD预测模型的建模方法、模型的质量表现、模型的表达及应用现状发现,Logistic回归分析是主要的建模方法,模型区分度较好,模型多采取内部验证,NAFLD预测模型的研究还存在较大的开发空间。
基金Supported by National key research and development plan-Clinical Evaluation of TCM Intervention in COVID-19 Recovery(No.2020YFC0845000)Clinical study on the prevention and treatment of COVID-19 with integrated Chinese and Western Medicine(No.2020YFC0841600)National Administration of Traditional Chinese Medicine-TCM Emergency Response Project for COVID-19(No.2020ZYLCYJ04)。
文摘OBJECTIVE:To summarize the potential characteristics of convalescent patients with coronavirus disease 2019(COVID-19)in China based on emerging clinical tongue data and guide the treatment and recovery of COVID-19 patients from the perspective of Traditional Chinese Medicine tongue diagnosis.METHODS:In this study,we developed and validated radiomics-based and lab-based methods as a novel approach to provide individualized pretreatment evaluation by analyzing different features to mine the orderliness behind tongue data of convalescent patients.In addition,this study analyzed the tongue features of convalescent patients from clinical tongue qualitative values,including thick and thin,fur,peeling,fat and lean,tooth marks and cracked,and greasy and putrid fur.RESULTS:We included 2164 tongue images in total(34%from day 0,35.4%from day 14 and 30.6%from day 28)from convalescent patients.The significance results are shown as follows.Firstly,as the recovery time prolongs,the L average values of tongue and coat decrease from 60.21 to 57.18 and from 60.06 to 57.03 respectively.Secondly,the decrease of abnormality rate of tongue coat,included greasy tongue fur,putrid fur,teeth-mark,thick-thin fur,are of significant statistical difference(P<0.05).Thirdly,the average value of gray-level cooccurrence matrices increases from 0.173 to 0.194,the average value of entropy increases from 0.606 to 0.665,the average value of inverse difference normalized decrease from 0.981 to 0.979,and the average value of dissimilarity decrease from 0.1576 to 0.1828.The details of other radiomics features are describe in results section.CONCLUSIONS:Our experiment shows that patients in different recovery periods have a relationship with quantitative values of tongue images,including L color space of the tongue and coat radiomics features analysis.This relationship can help clinical doctors master the recovery and health of patients as soon as possible and improve their understanding of the potential mechanisms underlying the dynamic changes and mechanisms underlying COVID-19.
