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Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing

OBJECTIVES: The aim of this study is to interpret a quantitative diagnosis model of traditional Chinese medicine (TCM) syndromes based on computer adaptive testing (CAT), from the perspective of both patients and clinicians. METHODS: In this cross-sectional study, patients with postprandial distress...

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Autores principales: Yao, Simeng, Huang, Zhongyu, Liu, Xianhua, Yan, Qiaofeng, Tang, Jing, Liu, Fengbin, Hou, Zhengkun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9262526/
https://www.ncbi.nlm.nih.gov/pubmed/35815272
http://dx.doi.org/10.1155/2022/3203158
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author Yao, Simeng
Huang, Zhongyu
Liu, Xianhua
Yan, Qiaofeng
Tang, Jing
Liu, Fengbin
Hou, Zhengkun
author_facet Yao, Simeng
Huang, Zhongyu
Liu, Xianhua
Yan, Qiaofeng
Tang, Jing
Liu, Fengbin
Hou, Zhengkun
author_sort Yao, Simeng
collection PubMed
description OBJECTIVES: The aim of this study is to interpret a quantitative diagnosis model of traditional Chinese medicine (TCM) syndromes based on computer adaptive testing (CAT), from the perspective of both patients and clinicians. METHODS: In this cross-sectional study, patients with postprandial distress syndrome completed the CAT model of TCM syndromes and the Chinese version of the Quality of Life Questionnaire for Functional Digestive Disorders (Chin-FDDQL); the clinicians' diagnosis was concurrently recorded. The patients completed this questionnaire again after 14 ± 2 days. The kappa test and paired chi-square test were used to evaluate the consistency between the CAT model and clinical diagnosis. Minimal clinically important differences (MCID) of the Chin-FDDQL scores were used to assess clinical efficacy from the patients' perspective. Logistic regression was used to examine the association between changes in the CAT model syndrome domain scores and changes in clinical outcomes. RESULTS: Changes in the CAT model syndrome domain scores may affect the clinical outcomes of patients with the total scores of Chin-FDDQL (all P < 0.05). There was a correlation between changes in the CAT model syndrome domain scores and the patients' clinical outcomes. Different syndrome elements had different effects on various Chin-FDDQL domains, which was consistent with the theory of TCM. CONCLUSIONS: This study proposes a method for the clinical interpretation of the CAT model of TCM syndromes, including evidence derived from the application. It may provide a reference for future interpretation of other CAT models.
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spelling pubmed-92625262022-07-08 Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing Yao, Simeng Huang, Zhongyu Liu, Xianhua Yan, Qiaofeng Tang, Jing Liu, Fengbin Hou, Zhengkun Evid Based Complement Alternat Med Research Article OBJECTIVES: The aim of this study is to interpret a quantitative diagnosis model of traditional Chinese medicine (TCM) syndromes based on computer adaptive testing (CAT), from the perspective of both patients and clinicians. METHODS: In this cross-sectional study, patients with postprandial distress syndrome completed the CAT model of TCM syndromes and the Chinese version of the Quality of Life Questionnaire for Functional Digestive Disorders (Chin-FDDQL); the clinicians' diagnosis was concurrently recorded. The patients completed this questionnaire again after 14 ± 2 days. The kappa test and paired chi-square test were used to evaluate the consistency between the CAT model and clinical diagnosis. Minimal clinically important differences (MCID) of the Chin-FDDQL scores were used to assess clinical efficacy from the patients' perspective. Logistic regression was used to examine the association between changes in the CAT model syndrome domain scores and changes in clinical outcomes. RESULTS: Changes in the CAT model syndrome domain scores may affect the clinical outcomes of patients with the total scores of Chin-FDDQL (all P < 0.05). There was a correlation between changes in the CAT model syndrome domain scores and the patients' clinical outcomes. Different syndrome elements had different effects on various Chin-FDDQL domains, which was consistent with the theory of TCM. CONCLUSIONS: This study proposes a method for the clinical interpretation of the CAT model of TCM syndromes, including evidence derived from the application. It may provide a reference for future interpretation of other CAT models. Hindawi 2022-06-30 /pmc/articles/PMC9262526/ /pubmed/35815272 http://dx.doi.org/10.1155/2022/3203158 Text en Copyright © 2022 Simeng Yao et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yao, Simeng
Huang, Zhongyu
Liu, Xianhua
Yan, Qiaofeng
Tang, Jing
Liu, Fengbin
Hou, Zhengkun
Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing
title Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing
title_full Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing
title_fullStr Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing
title_full_unstemmed Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing
title_short Interpretation of a Quantitative Diagnosis Model of Traditional Chinese Medicine Syndromes Based on Computer Adaptive Testing
title_sort interpretation of a quantitative diagnosis model of traditional chinese medicine syndromes based on computer adaptive testing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9262526/
https://www.ncbi.nlm.nih.gov/pubmed/35815272
http://dx.doi.org/10.1155/2022/3203158
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