Extraction of Clinical Indicators That Are Associated with the Heat/Nonheat and Excess/Deficiency Patterns in Pattern Identifications for Stroke

The aim of this study is to extract indicators that are associated with the heat/nonheat and excess/deficiency patterns in stroke pattern identification through the large-scale analysis of clinical data. Two experts, who had more than three years of clinical experience with stroke, independently per...

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Main Authors: Ju Ah Lee, Mi Mi Ko, Jungsup Lee, Byoung-Kab Kang, Terje Alraek, Stephen Birch, Myeong Soo Lee
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Evidence-Based Complementary and Alternative Medicine
Online Access:http://dx.doi.org/10.1155/2015/869894
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spelling doaj-ce5f5e4d8a6c45b4b44d8b98ef090c382020-11-24T23:03:41ZengHindawi LimitedEvidence-Based Complementary and Alternative Medicine1741-427X1741-42882015-01-01201510.1155/2015/869894869894Extraction of Clinical Indicators That Are Associated with the Heat/Nonheat and Excess/Deficiency Patterns in Pattern Identifications for StrokeJu Ah Lee0Mi Mi Ko1Jungsup Lee2Byoung-Kab Kang3Terje Alraek4Stephen Birch5Myeong Soo Lee6Medical Research Division, Brain Disease Research Center, Korea Institute of Oriental Medicine, 1672 Yuseongdae-ro, Yuseong-gu, Daejeon 305-811, Republic of KoreaMedical Research Division, Brain Disease Research Center, Korea Institute of Oriental Medicine, 1672 Yuseongdae-ro, Yuseong-gu, Daejeon 305-811, Republic of KoreaKorean National Rehabilitation Center, Seoul, Republic of KoreaMedical Research Division, Brain Disease Research Center, Korea Institute of Oriental Medicine, 1672 Yuseongdae-ro, Yuseong-gu, Daejeon 305-811, Republic of KoreaUniversity College of Health Sciences, Institute of Acupuncture, 0855 Oslo, NorwayUniversity College of Health Sciences, Institute of Acupuncture, 0855 Oslo, NorwayMedical Research Division, Brain Disease Research Center, Korea Institute of Oriental Medicine, 1672 Yuseongdae-ro, Yuseong-gu, Daejeon 305-811, Republic of KoreaThe aim of this study is to extract indicators that are associated with the heat/nonheat and excess/deficiency patterns in stroke pattern identification through the large-scale analysis of clinical data. Two experts, who had more than three years of clinical experience with stroke, independently performed the pattern identification. We analyzed indicators of clinical data with two doctors’ concurrent diagnoses on the patient’s pattern identification. To verify heat/nonheat and excess/deficiency patterns, which are the basic elements of pattern identification, we grouped 960 patients diagnosed as the fire-heat pattern, the Yin deficiency pattern, and the Qi deficiency pattern in to two groups, the heat/nonheat group and the excess/deficiency group. We then extracted significant indicators using univariate and multivariate analysis. As a result of the comparison of 65 indicators, we were able to extract 10 indicators for the heat pattern, 6 for the nonheat pattern, 9 for the excess pattern, and 10 for the deficiency pattern. Extracted indicators in this study can be used for pattern identification in the context of stroke. These are positive indicators from large-scale clinical studies and are greatly expected to be crucial discriminant indicators in individual pattern identification henceforth.http://dx.doi.org/10.1155/2015/869894
collection DOAJ
language English
format Article
sources DOAJ
author Ju Ah Lee
Mi Mi Ko
Jungsup Lee
Byoung-Kab Kang
Terje Alraek
Stephen Birch
Myeong Soo Lee
spellingShingle Ju Ah Lee
Mi Mi Ko
Jungsup Lee
Byoung-Kab Kang
Terje Alraek
Stephen Birch
Myeong Soo Lee
Extraction of Clinical Indicators That Are Associated with the Heat/Nonheat and Excess/Deficiency Patterns in Pattern Identifications for Stroke
Evidence-Based Complementary and Alternative Medicine
author_facet Ju Ah Lee
Mi Mi Ko
Jungsup Lee
Byoung-Kab Kang
Terje Alraek
Stephen Birch
Myeong Soo Lee
author_sort Ju Ah Lee
title Extraction of Clinical Indicators That Are Associated with the Heat/Nonheat and Excess/Deficiency Patterns in Pattern Identifications for Stroke
title_short Extraction of Clinical Indicators That Are Associated with the Heat/Nonheat and Excess/Deficiency Patterns in Pattern Identifications for Stroke
title_full Extraction of Clinical Indicators That Are Associated with the Heat/Nonheat and Excess/Deficiency Patterns in Pattern Identifications for Stroke
title_fullStr Extraction of Clinical Indicators That Are Associated with the Heat/Nonheat and Excess/Deficiency Patterns in Pattern Identifications for Stroke
title_full_unstemmed Extraction of Clinical Indicators That Are Associated with the Heat/Nonheat and Excess/Deficiency Patterns in Pattern Identifications for Stroke
title_sort extraction of clinical indicators that are associated with the heat/nonheat and excess/deficiency patterns in pattern identifications for stroke
publisher Hindawi Limited
series Evidence-Based Complementary and Alternative Medicine
issn 1741-427X
1741-4288
publishDate 2015-01-01
description The aim of this study is to extract indicators that are associated with the heat/nonheat and excess/deficiency patterns in stroke pattern identification through the large-scale analysis of clinical data. Two experts, who had more than three years of clinical experience with stroke, independently performed the pattern identification. We analyzed indicators of clinical data with two doctors’ concurrent diagnoses on the patient’s pattern identification. To verify heat/nonheat and excess/deficiency patterns, which are the basic elements of pattern identification, we grouped 960 patients diagnosed as the fire-heat pattern, the Yin deficiency pattern, and the Qi deficiency pattern in to two groups, the heat/nonheat group and the excess/deficiency group. We then extracted significant indicators using univariate and multivariate analysis. As a result of the comparison of 65 indicators, we were able to extract 10 indicators for the heat pattern, 6 for the nonheat pattern, 9 for the excess pattern, and 10 for the deficiency pattern. Extracted indicators in this study can be used for pattern identification in the context of stroke. These are positive indicators from large-scale clinical studies and are greatly expected to be crucial discriminant indicators in individual pattern identification henceforth.
url http://dx.doi.org/10.1155/2015/869894
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