Chinese and contemporary Western medical practices evolved on different cultures and historical contexts and, therefore, their medical knowledge represents this cultural divergence. Computerization of traditional Chinese medicine (TCM) is being used to promote the integrative medicine to manage, process and integrate the knowledge related to TCM anatomy, physiology, semiology, pathophysiology, and therapy.

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.

Chinese medicine practitioners apply the differentiation reasoning for decision-making. The wide scope of Chinese medicine intervention provides coverage of methods and techniques with applications to primary, secondary and tertiary levels of prevention. The rapid evolution of mathematical and computational techniques allowed the implementation of several models for pattern differentiation that were tested for several physiologic systems. Concurrently, it is argued that pattern differentiation might improve the efficacy of either traditional or conventional medical interventions. This article reviewed the influence of pattern differentiation into clinical practice organized by medical field: general pattern differentiation; genitourinary (recurrent cystitis); cardiovascular (coronary heart disease; arterial hypertension; angina pectoris); neurology (stroke); surgery; metabolic (diabetes mellitus); hepatic (cirrhosis); gastrointestinal (chronic superficial gastritis); orthopedic (low back pain; rheumatoid arthritis; cervical spondylosis; elbow arthritis); oncology (gastric mucosal dysplasia; lung cancer); gynecologic and obstetric manifestations (nausea and vomiting). The reviewed studies presented achievements that have contributed to the integration of Chinese medicine and evidence-based medicine in the treatment of many mild and severe diseases. Target diseases considered as major public health problems were also investigated and the results are promising regarding the possibility to treat guided by pattern differentiation.
Disease ; Humans ; Medicine, Chinese Traditional ; methods ; Practice Patterns, Physicians'

BACKGROUNDChinese and contemporary Western medical practices evolved on different cultures and historical contexts and, therefore, their medical knowledge represents this cultural divergence. Computerization of traditional Chinese medicine (TCM) is being used to promote the integrative medicine to manage, process and integrate the knowledge related to TCM anatomy, physiology, semiology, pathophysiology, and therapy.

METHODSWe proposed the development of the SuiteTCM software, a collection of integrated computational models mainly derived from epidemiology and statistical sciences for computerization of Chinese medicine scientific research and clinical practice in all levels of prevention. The software includes components for data management (DataTCM), simulation of cases (SimTCM), analyses and validation of datasets (SciTCM), clinical examination and pattern differentiation (DiagTCM, TongueTCM, and PulseTCM), intervention selection (AcuTCM, HerbsTCM, and DietTCM), management of medical records (ProntTCM), epidemiologic investigation of sampled data (ResearchTCM), and medical education, training, and assessment (StudentTCM).

DISCUSSIONThe SuiteTCM project is expected to contribute to the ongoing development of integrative medicine and the applicability of TCM in worldwide scientific research and health care. The SuiteTCM 1.0 runs on Windows XP or later and is freely available for download as an executable application.

Biomedical Research ; Decision Making, Computer-Assisted ; Humans ; Integrative Medicine ; Medicine, Chinese Traditional

OBJECTIVEThe 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.

METHODSSimTCM 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.

RESULTSSimulations 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.

CONCLUSIONThis 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.

Computer Simulation ; Diagnosis ; Evidence-Based Medicine ; Humans ; Medicine, Chinese Traditional ; Patient Simulation

BACKGROUNDPulse wave analysis (PWA) quantifies the phenomenon of pulse waveform propagation in patients with cardiovascular diseases, whereas pulse image analysis (PIA) is a subjective examination in traditional Chinese medicine.

OBJECTIVEThis study evaluated the association of PIA with PWA and hemodynamics in patients with hypertension.

DESIGN, SETTING, PARTICIPANTS AND INTERVENTIONSThis observational, cross-sectional study enrolled 45 patients (26 men, (55.2 ± 10.3) years, systolic blood pressure (155 ± 28) mmHg, diastolic blood pressure (93 ± 17) mmHg) for assessment of clinical and laboratorial data.

MAIN OUTCOME MEASURESPrimary outcomes comprised: pattern differentiation based on an automated method; PIA at the radial artery using the 'simultaneous pressing' method for identification of factors such as strength (strong/weak), depth (superficial/deep), and speed (fast/moderate/slow); and PWA at the same artery using a noninvasive system.

RESULTSSignificant multivariate main effects were observed for depth (λ=0.648, F5,29 =3.149, P=0.022, η(2) =0.352), strength (λ=0.608, F5,29 =3.736, P=0.010, η(2) =0.392), and speed (λ=0.535, F5,29 =5.302, P=0.002, η(2) =0.465). General effects comprised high values of PWA and blood pressure for superficial, strong, and fast pulse images. A strong pulse was found for pulse pressure ≥ 62.5 mmHg and systolic blood pressure ≥ 149.5 mmHg, whereas a superficial pulse was found for heart rate ≥ 58.25 beats/min; a fast pulse was found for heart rate ≥ 69.6 beats/min and pulse wave velocity ≥ 9.185 m/s.

CONCLUSIONAssociations were explained by LaPlace's law, arterial remodeling in hypertension, alongside the traditional criterion for classifying speed in pulse images. PIA is associated with PWA and hemodynamics in patients with hypertension. Systolic and pulse pressures, heart rate, and pulse wave velocity are quantitative variables that have information to describe the qualitative pulse images such as strength, depth and speed.

Adult ; Aged ; Cross-Sectional Studies ; Female ; Heart Rate ; Hemodynamics ; Humans ; Hypertension ; physiopathology ; Male ; Medicine, Chinese Traditional ; Middle Aged ; Pulse Wave Analysis ; Wrist