喘息 환자의 虛實寒熱辨證과 특성 비교 분석
Deficiency-excess and Cold-heat Pattern Identification and Analysis of the Characteristics of Asthma Patients
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Objectives: The aim of this observational study was to identify and analyze the patterns to compare the characteristics of asthma patients. Methods: The subjects were 40 asthma patients who had satisfied the inclusion and exclusion criteria. They were divided into deficiency syndrome and excess syndrome groups, and cold syndrome and heat syndrome groups. Their quality of life was measured by the quality of life questionnaire for adult Korean asthmatics (QLQAKA) and VAS. Heart rate variability (HRV) was measured, and the degree of obesity was evaluated by body mass index (BMI). Hematological, biochemical, and immunoglobulin (Ig) E laboratory tests were included. Results: Based on pattern identification, the 40 asthma patients could be divided into two categories of groups: 1) the deficiency syndrome (N=18) and the excess syndrome (N=22) groups: 2) the cold syndrome (N=35) and the heat syndrome (N=5) groups. The mean value of HF differed significantly between the deficiency and excess syndrome groups. The mean value of IgE in blood tests of asthmatics was greater than four times the reference value. For BMI, the subjects were classified into three groups: normal weight (N=12), overweight (N=12), and obese (N=16). Conclusions: Development of a more accurate asthma-specific pattern identification tool could play a crucial role in asthma control. In addition, good control of asthma can improve the quality of life. Obesity is one of the factors associated with asthma exacerbation.
Abstract
Objectives: The aim of this observational study was to identify and analyze the patterns to compare the characteristics of asthma patients. Methods: The subjects were 40 asthma patients who had satisfied the inclusion and exclusion criteria. They were divided into deficiency syndrome and excess syndrome groups, and cold syndrome and heat syndrome groups. Their quality of life was measured by the quality of life questionnaire for adult Korean asthmatics (QLQAKA) and VAS. Heart rate variability (HRV) was measured, and the degree of obesity was evaluated by body mass index (BMI). Hematological, biochemical, and immunoglobulin (Ig) E laboratory tests were included. Results: Based on pattern identification, the 40 asthma patients could be divided into two categories of groups: 1) the deficiency syndrome (N=18) and the excess syndrome (N=22) groups: 2) the cold syndrome (N=35) and the heat syndrome (N=5) groups. The mean value of HF differed significantly between the deficiency and excess syndrome groups. The mean value of IgE in blood tests of asthmatics was greater than four times the reference value. For BMI, the subjects were classified into three groups: normal weight (N=12), overweight (N=12), and obese (N=16). Conclusions: Development of a more accurate asthma-specific pattern identification tool could play a crucial role in asthma control. In addition, good control of asthma can improve the quality of life. Obesity is one of the factors associated with asthma exacerbation.
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