Based On The Principal Component Analysis Method To Verify The COPD Development "Fast" And "Slow" Judgment Standard

Objective: Using principal component analysis method to verify the standard to judge COPD’s development fast and slow. Methods: Using a cross-sectional study in the early stage of COPD development "fast" and "slow", data were selected from Autonomous Region Hospital of traditional Chinese Medicine Department of respiration hospital department, there was 93 cases was collected, exclusion of other pulmonary diseases(asthma, tuberculosis, bronchiectasis). Collect each patient gender, age, smoking status, body mass index(BMI), degree of dyspnea, complications and other data, the detection of FEV1%, FEVI/FVC% and HRCT expression in pulmonary emphysema visual score in the two groups of patients. We uses descriptive analysis, Univariate analysis, multivariate logistic regression analysis, principal component analysis(PCA) to describe and analysis. Results:(1) In all 93 patients, which 32 cases were fast process, 61 patients were slow process, average age of the patients in fast process is: 63.11±11.22, the average age of the slow process of the patients was: 68.93±10.37; there was statistical significance in two groups;(2) COPD fast process group, hypertension, heart disease, is higher than the slow process of COPD patients, the difference was statistically significant(P<0.05);(3) The fast process group was significantly lower than that in the FEV1 group(P<0.05), the slow process of fast process group is significantly lower than the slow process of the ratio of FEV1/FVC group(P< 0.05). At the same time found that dyspnea index fast process group patients is higher than that of slow process group(P<0.05); the probability of a family genetic history exhibition group was significantly higher than that in the fast forward to slow progress of the group, the difference was statistically significant(P<0.05);(4) The study of principal component analysis showed, fast, slow process of sequential evaluation index should be chosen as the: six minute walk test, course of disease, FEV1%, dyspnea index, time of day, the acute exacerbation of FEV1/FVC%, CAT score, hypertension, the annual Times of acute exacerbation, family history, heart disease, years, times of hospitalization; logistic regression analysis showed that the difficulty in breathing, heart disease. Found that compared with the result of Delphi method, principal component analysis and Delphi method results in the most similar conclusion. Conclusions: Through the research, we draw the following conclusions:(1) the Delphi method with the conclusions of this study are the main influencing factors are consistent;(2) there is a correlation between the grouping factors, can consider to delete some indicators;(3) family history of complications can be used as a judgment index, the accuracy will help to improve the evaluation.