Abstract: Objective To investigate the clinical characteristics and related factors of fatigue symptoms in patients with asthma. Methods A total of 198 asthmatic patients who visited the respiratory department of our hospital were included in this study. According to the Fatigue Severity Scale (FSS), the patients were divided into the fatigue group (≥4, n= 126) and the non-fatigue group (＜4, n=72). The clinical characteristics, pulmonary function, exhaled nitric oxide test (FENO), the dyspnea score (MRC), asthma control scale (ACT), daily life ability (MBI)，6 min walk test (6MWT)，Hamilton depression scale-17 items (HAMD-17), Pittsburgh sleep quality index scale (PSQI) and the number of acute episodes in the past year were analyzed between the two groups. Binary Logistic regression analysis was used for analyzing the influencing factors of fatigue symptoms in asthmatic patients. According to the selected indicators, the prediction model of the nomogram was constructed, and the prediction value of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve. Results The ACT score was lower in fatigue group than that of non-fatigue group, and the mMRC grading, HAMD-17 score, PSQI score and the frequency of acute attack in the previous 1 year were higher in fatigue group than those of non-fatigue group (P＜0.05). There were no significant differences in the other indexes between the two groups (P＞0.05). Binary Logistic regression analysis showed that ACT score (OR=0.644, 95%CI: 0.508-0.816), mMRC grading (OR=2.313, 95%CI: 1.349-3.966), HAMD-17 score (OR=1.561, 95%CI: 1.273-1.913) and PSQI score (OR=1.932, 95%CI: 1.506-2.479) were the influencing factors of fatigue in asthmatic patients. The prediction model was built based on the four influencing factors. The area under the ROC curve of the prediction model was 0.935 (95%CI: 0.902-0.967). Through internal verification, the C-index was 0.929, and the calibration curve showed that the predicted results of the nomogram were in good agreement with the actual observation results. Conclusion The incidence of fatigue is high in patients with asthma. Poor asthma control, high mMRC grading, negative mood and sleep disturbance are important influencing factors of fatigue. The nomogram constructed according to the influencing factors has high predictive value.

Key words: asthma, fatigue, root cause analysis, nomograms, fatigue severity scale