A Novel Approach to Describing Traditional Chinese Medical Patterns: The "traditional Chinese Medical Diagnostic Descriptor"

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Journal Article
Journal of Alternative and Complementary Medicine, 2019, 25 (11), pp. 1121 - 1129
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© Copyright 2019, Mary Ann Liebert, Inc. Objectives: In the first of a series of three articles by the present authors, diagnostic agreement between Traditional Chinese Medicine (TCM) practitioners was found to be low. This was the first time that TCM diagnoses had been evaluated with an open population of patients and this result is a cause of concern. In the second article, incorrect statistics were shown to have often been used to calculate chance-removed inter-rater agreement, and appropriate statistics such as Gwet's Agreement Coefficient 2 (AC2) was recommended for future studies. In this, the third article, a novel approach to recording TCM diagnostic patterns, the Traditional Chinese Medical Diagnostic Descriptor (TCMDD), is presented that allows chance-removed agreement calculation. An example of mapping TCM diagnostic patterns to the TCMDD format is given and diagnostic agreement is evaluated. Design, Settings, Subjects: The same 35 subjects used to report agreement in our first article were also diagnosed by additional practitioners using the TCMDD format during the same experimental sessions at the University of Technology, Sydney Clinic. TCM diagnoses from the first article were also mapped to the TCMDD format. Outcome measures: Linearly weighted simple agreement and the AC2 statistic were utilized and all results compared. Results: Linearly weighted simple agreement using the TCMDD and TCM mapped to TCMDD format averaged 0.80 ± 0.02 compared with 0.19 for TCM. TCMDD and TCM mapped to TCMDD chance-removed agreement, as calculated with AC2, ranged between 0.67 and 0.73 ± 0.03. Conclusions: The TCMDD allows the essence of diagnoses expressed by TCM practitioners to be appropriately compared. This was confirmed by the TCM mapped to TCMDD results. In both cases, simple agreement was significantly greater than that obtained with the TCM format. Chance-removed statistics and error estimates can be reliably calculated with the AC2 and the TCMDD in open populations.
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