Abstract
Objective: To explore correlative factors and construct predictive model of intestinal flora imbalance in patients with acute exacerbation of Chronic Obstructive Pulmonary Disease (COPD). Methods: The patients in acute exacerbation stage of COPD (AECOPD) hospitalized in Yixing People's Hospital from January 1 to December 31, 2019 were included. According to the clinical symptoms and results of fecal examination, the subjects were divided into case group (n=45) and control group (n=83). Multivariate logistic regression was used to analyze the correlative factors of intestinal flora imbalance in AECOPD patients. The prediction model of intestinal flora imbalance in patients with AECOPD was constructed according to the results of factor logistic regression analysis, and the effectiveness of the prediction model was evaluated by receiver operating characteristic (ROC) curve analysis. Results: The ages of subjects in case group and control group were (76±9) and (74±8) years old, respectively, among which males accounted for 80.0% (36/45) and 69.9% (58/83), respectively. The multivariate logistic regression model analysis showed that serum albumin concentration, frequency of acute exacerbation ≥2 times/year, complicated with chronic cor pulmonale and diabetes mellitus were correlative factors of intestinal flora imbalance in patients with AECOPD. The OR (95%CI) were 0.98 (0.80-0.97), 3.70 (1.79-11.72), 2.62 (1.46-10.80) and 3.85 (1.17-8.58), respectively. The prediction model of intestinal flora imbalance was logit P=3.858-0.13×serum albumin consentration+1.52×acute exacerbation ≥2 times/year+1.379×chronic cor pulmonale+1.155×diabetes mellitus. The area under the ROC curve of this model was 0.847 and the sensitivity and specificity of the prediction model were 88.9% and 71.1%, respectively. Conclusions: Serum albumin, frequency of acute exacerbation ≥2 times/year, complicated with chronic cor pulmonale and diabetes mellitus are correlative factors of intestinal flora imbalance in patients with AECOPD. The predictive model shows high clinical value in predicting intestinal flora imbalance in patients with AECOPD.
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