挖掘武汉新冠肺炎康复患者的内在信息。
Mining intrinsic information of convalescent patients after suffering coronavirus disease 2019 in Wuhan.
机构信息
Department of TCM Data Intelligence, Shanghai Daosh Medical Technology Co., Ltd., Shanghai 201200, China.
Electronical Medical Records and Information Management Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai 200437, China.
出版信息
J Tradit Chin Med. 2022 Apr;42(2):279-288. doi: 10.19852/j.cnki.jtcm.20220225.001.
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 ( < 0.05). Thirdly, the average value of gray-level co-occurrence 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.
目的
基于新兴的临床舌诊数据，总结中国新冠肺炎（COVID-19）恢复期患者的潜在特征，并从中医舌诊的角度指导 COVID-19 患者的治疗和康复。
方法
本研究通过分析不同特征，开发和验证了基于放射组学和实验室的方法，为个体化预处理评估提供了新方法，挖掘恢复期患者舌诊数据背后的有序性。此外，本研究还从临床舌象定性值，包括厚、薄、苔、剥落、肥瘦、齿痕和裂纹、油腻腐苔等方面分析了恢复期患者的舌象特征。
结果
共纳入 2164 例恢复期患者的舌象图像（0 天 34%，14 天 35.4%，28 天 30.6%）。显著性结果如下：首先，随着恢复时间的延长，舌和苔的 L 平均值从 60.21 降至 57.18，从 60.06 降至 57.03。其次，舌苔异常率的降低，包括腻苔、腐苔、齿痕、厚苔、薄苔，具有显著的统计学差异（<0.05）。第三，灰度共生矩阵的平均值从 0.173 增加到 0.194，熵的平均值从 0.606 增加到 0.665，倒数差异归一化的平均值从 0.981 减少到 0.979，差异的平均值从 0.1576 增加到 0.1828。其他放射组学特征的详细信息在结果部分描述。
结论
本实验表明，不同恢复期的患者与舌象图像的定量值之间存在一定的关系，包括舌和苔的 L 颜色空间以及放射组学特征分析。这种关系可以帮助临床医生尽快掌握患者的康复和健康状况，提高他们对 COVID-19 动态变化和潜在机制的认识。
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