title: Evaluation of the accuracy of diagnostic scales for a syndrome in Chinese medicine in the absence of a gold standard.
abstract: BACKGROUND
  The concept of syndromes (zhengs) is unique to Chinese medicine (CM) and difficult to measure. Expert consensus is used as a gold standard to identify zhengs and evaluate the accuracy of existing diagnostic scales for zhengs. But, the use of expert consensus as a gold standard is problematic because the diagnosis of zhengs by expert consensus is not 100 % accurate. This study aimed to evaluate the accuracy of standardized diagnostic scales for a syndrome zhengs in the absence of a gold standard, with application to internal wind (nei feng) syndrome in ischemic stroke patients.
  
  
  METHODS
  A total of 204 participants (age 41-84 years) with ischemic stroke were assessed by the stroke syndrome differentiation diagnostic criterion (SSDC), ischemic stroke TCM syndrome diagnostic scale (ISDS), and expert syndrome differentiation (ESD). The diagnostic tests and data collection process were conducted over a 10-month period (February 2008 to November 2008) in 10 hospitals across nine cities in China. The Bayesian method was used to estimate the accuracy of the SSDC, ISDS, and ESD.
  
  
  RESULTS
  For internal wind syndrome, the estimated sensitivities and specificities of the SSDC, ISDS, and ESD without use of a gold standard were respectively: [Formula: see text], [Formula: see text]; [Formula: see text], [Formula: see text]; and [Formula: see text], [Formula: see text].
  
  
  CONCLUSIONS
  After adjusting for imperfect gold standard bias, we found that both the sensitivity and specificity of the ISDS were higher than those of the SSDC for diagnosis of internal wind syndrome in ischemic stroke patients.
authors.affiliation: School of Statistics, Renmin University of China, Beijing, 100872 China.
authors.forename: Xiao Nan
authors.initials: XN
authors.lastname: Wang
authors.affiliation: UW Autism Center, University of Washington, Seattle, WA 98105 USA.
authors.forename: Vanessa
authors.initials: V
authors.lastname: Zhou
authors.affiliation: TCM International Cooperation Center of China, Beijing, 100101 China.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Liu
authors.affiliation: Department of Neurology, Dongzhimen Hospital of Beijing University of Chinese Medicine, Beijing, 100700 China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Gao
authors.affiliation: School of Statistics, Renmin University of China, Beijing, 100872 China ; Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA 98195 USA.
authors.forename: Xiao-Hua
authors.initials: XH
authors.lastname: Zhou
keywords: Bayesian method; CM; Diagnostic scale; Sensitivity; Specificity; Syndrome; Without a gold standard