Ferreira Arthur de Sá, Pacheco Antonio Guilherme
Postgraduation Program in Rehabilitation Science, Augusto Motta University Center, Rio de Janeiro, Brazil; E-mail:
Program of Scientific Computing, Fiocruz, Rio de Janeiro, Brazil.
J Integr Med. 2015 Jan;13(1):9-19. doi: 10.1016/S2095-4964(15)60151-0.
The aim of this work is to develop and implement the SimTCM, an advanced computational model that incorporates relevant aspects from traditional Chinese medicine (TCM) theory as well as advanced statistical and epidemiological techniques for simulation and analysis of human patients.
SimTCM presents five major attributes for simulation: representation of true and false profiles for any single pattern; variable count of manifestations for each manifestation profile; empirical distributions of patterns and manifestations in a disease-specific population; incorporation of uncertainty in clinical data; and the combination of the four examinations. The proposed model is strengthened by following international standards for reporting diagnostic accuracy studies, and incorporates these standards in its treatment of study population, sample size calculation, data collection of manifestation profiles, exclusion criteria and missing data handling, reference standards, randomization and blinding, and test reproducibility.
Simulations using data from patients diagnosed with hypertension and post-stroke sensory-motor impairments yielded no significant differences between expected and simulated frequencies of patterns (P=0.22 or higher). Time for convergence of simulations varied from 9.90 s (9.80, 10.27) to 28.31 s (26.33, 29.52). The ratio iteration profile necessary for convergence varied between 1:1 and 5:1.
This model is directly connected to forthcoming models in a large project to design and implement the SuiteTCM: ProntTCM, SciTCM, DiagTCM, StudentTCM, ResearchTCM, HerbsTCM, AcuTCM, and DataTCM. It is expected that the continuity of the SuiteTCM project enhances the evidence-based practice of Chinese medicine. The software is freely available for download at: http://suitetcm.unisuam.edu.br.
本研究旨在开发并实施中医模拟系统（SimTCM），这是一种先进的计算模型，它融合了中医理论的相关方面以及先进的统计和流行病学技术，用于对人类患者进行模拟和分析。
SimTCM具有五个主要模拟属性：任何单一证型的虚实特征表示；每个症状特征的症状数量可变；特定疾病人群中证型和症状的经验分布；临床数据中不确定性的纳入；以及四诊合参。通过遵循国际诊断准确性研究报告标准来强化所提出的模型，并将这些标准纳入其对研究人群、样本量计算、症状特征数据收集、排除标准和缺失数据处理、参考标准、随机化和盲法以及测试可重复性的处理中。
使用诊断为高血压和中风后感觉运动障碍患者的数据进行模拟，证型的预期频率与模拟频率之间无显著差异（P = 0.22或更高）。模拟收敛时间从9.90秒（9.80，10.27）到28.31秒（26.33，29.52）不等。收敛所需的比率迭代次数在1:1到5:1之间变化。
该模型与一个大型项目中即将推出的模型直接相关，该项目旨在设计和实施中医套件（SuiteTCM）：ProntTCM、SciTCM、DiagTCM、StudentTCM、ResearchTCM、HerbsTCM、AcuTCM和DataTCM。预计SuiteTCM项目的连续性将增强中医的循证实践。该软件可在以下网址免费下载：http://suitetcm.unisuam.edu.br 。
