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Modeling and Analysis of Monitored vs. Self-reported Postsurgical Acute Pain in a Clinical Trial ?

机译:在临床试验中进行监测和自我报告的后勤急性疼痛的建模与分析

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摘要

This work aims to study postsurgical trauma modeling to characterize the physiological process in postoperative pain assessment in an observational trial. The skin impedance data is proposed to be fitted by derived-Cole models, i.e., single and double dispersion models and a distributed model with an inductive term related to sweat glands. These models are motivated by the biological characteristics of the skin, its physiological stratification and the current intra-and extra-cellular pathways. The correlation between the identified parameters with the patient’s pain reported using the numerical rating scale (NRS) is analyzed for one patient for all three models. Following the trial, a statistically significant positive linear relationship was observed between the Anspec-Pro index and NRS (r2= 0.16, p=0.00), driving the further study of the relationship between the estimated dielectric parameters. The paper focuses to analyze the changes of the coefficients related to the particular clinical data, successfully identified using the non-linear least square procedure. The clinical significance of the results may be related to the individual model parameters for postoperative pain detection, validated on patients.
机译:这项工作旨在研究后勤创伤模型,以表征在观察试验中术后疼痛评估的生理过程。提出皮肤阻抗数据通过衍生 - COLE模型,即单个和双分散模型和分布式模型装配,具有与汗腺有关的感应术语。这些模型的激励是皮肤的生物学特征,其生理分层和当前内部和外细胞途径。对所有三种模型的一个患者分析了使用数值额定级(NRS)的患者疼痛的鉴定参数之间的相关性。在试验之后,在ANSPEC-PRO指数和NRS(R2 = 0.16,P = 0.00)之间观察到统计上显着的正线性关系,驱动了估计介电参数之间的关系的进一步研究。本文侧重于分析与特定临床数据相关的系数的变化,使用非线性最小二乘过程成功识别。结果的临床意义可能与术后疼痛检测的个体模型参数有关,验证患者。

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