Objective
This study is developed for clinical research to evaluate reliability and validity of Pattern Identifications Tool for Cognitive Disorders(PIT-C ver 2.1) and verify the correlation with other related scales.

Method
This study is a single group, prospective, observational one. The subjects selected was men and women between 45 and 85 years old, diagnosed with neurocognitive disorders by Diagnostic and Statistical Manual of Mental Disorder(5th edition)’s criteria (n=60, Clinical Dementia Rating(CDR)=0.5 or 1, Korean Version of Montreal Cognitive Assessment(MoCA-K)≤22). The reliability of PIT-C(ver 2.1) was evaluated as inter-rater and test-retest reliability. And correlation between PIT-C(ver 2.1) and other related scales are also assessed.

Results

1. We had moderate to substantial internal consistency and test-retest reliability on classifying pattern identification of PIT-C(ver 2.1) through Kappa analysis.
2. We had good to excellent internal consistency and test-retest reliability on scoring pattern identification of PIT-C(ver 2.1) through Kappa Pearson coefficient analysis.
3. Evaluating internal consistency measured by Cronbach-α, we had good or acceptable on Qi-dificiency and Phlegm-retained fluid Pattern, unacceptable on Yin-deficiency, poor or unacceptable on Fire-heat Pattern.
4. Evaluating the relevance of PIT-C(ver 2.1) and Korean diagnostic tool of dementia through ANOVA analysis, the Qi-deficiency pattern score had a highest score within the type of ‘Liver-kidney yin deficiency’, ‘Blood stasis due to qi stagnation’, ‘Deficiency of the spleen and kidney pattern’, ‘Dual deficiency of qi and blood’. Phlegm-retained fluid Pattern score was the highest within ‘Phlegm turbidity obstructing the path’, and the Fire-heat pattern score was the highest within type of ‘Fire toxin pattern’. In the Pearson correlation analysis, the PIT-C(ver 2.1) score of Qi defiency shows clear correlation with ‘Blood stasis due to qi stagnation’, ‘Dual deficiency of qi and blood’ and clear correlation between Yin-deficiency pattern score and ‘Liver-kidney yin deficiency’, ‘Dual deficiency of qi and blood’ and between Phlegm-retained fluid Pattern with ‘Phlegm turbidity obstructing the path’, ‘Dual deficiency of qi and blood’, Fire-heat score between ‘Dual deficiency of qi and blood’ and ‘Fire toxin pattern’. In the partial correlation analysis, PIT-C(ver 2.1) score of Qi deficency shows highest correlation with ‘Blood stasis due to qi stagnation’, ‘Dual deficiency of qi and blood’, and shows highest correlation between Yin-deficiency pattern score and 간신음허, Phlegm-retained fluid Pattern score and ‘Phlegm turbidity obstructing the path’, Fire-heat score and ‘Fire toxin pattern’
5. Evaluating the relevance of PIT-C(ver 2.1) and Pattern identification inventory of Cold-Heat, Deficiency-Excess in the categorical analysis, there was a significant difference between the Phlegm-retained fluid Pattern, Qi deficiency, Yin deficiency, Fire-heat groups for cold score. And Phlegm-retained fluid Pattern showed a significantly higher score compared to Yin deficiency and Fire-heat score in Kruskal-Wallis(Post analysis). In Pearson''s correlation analysis, significant positive correlation was showed between heat score and Fire-heat pattern, and showed borderline-level significant correlation between deficiency score and Qi-deficiency pattern.
6. Looking at the correlations with MMSE-DS, MoCA, KIADL, NPI, and CDR, KIADL and CDR sum of box showed a clear positive correlation with Qi deficiency scores.

Conclusion
Based on this study, its data could be used to categorize neurocognitive disorders as Korean medicine and PIT-C(ver 2.1) will be helpful tool for primary health care.