关键词: 慢性阻塞性肺疾病, 疲劳, 预测模型, 列线图, 护理

Abstract:

Objective To develop and validate a fatigue risk nomogram model in Chronic Obstructive Pulmonary Disease（COPD） patients. Methods A prospective study design was adopted，and 430 COPD patients recruited from a tertiary A hospital in Huzhou City from January to December 2022 were conveniently selected for model construction，and 129 patients were recruited from the same hospital from January to June 2023 for external validation of the model. The general information questionnaire，Pittsburgh Sleep Quality Index，2-item Generalized Anxiety Disorder Scale，2-item Patient Health Questionnaire，modified British Medical Research Council Dyspnea Index，International Physical Activity Questionnaire，and Fatigue Severity Scale were used for questionnaire survey.The risk prediction model and nomograms model were constructed using Logistic regression analysis and R 4.3.2 software，and the area under the receiver operating characteristic（ROC） curve was used to test the prediction effect of the model. Results Univariate and binary logistic regression analysis results showed that age（OR=1.095），gender（OR=2.077），dyspnea（OR=3.309），sleep quality（OR=1.979），anemia（OR=3.289），the number of acute exacerbation（OR=2.991） were independent influencing factors for fatigue in COPD patients. The internal evaluation and external validation results of the model showed that the areas under the curve are 0.912 and 0.844 respectively，and the Hosmer-Lemeshow goodness of fit test P values were 0.806 and 0.526 respectively. The average absolute errors were 0.013 and 0.019 respectively. Conclusion The COPD fatigue risk prediction model constructed in this study has good prediction effect. The visual nomogram is intuitive，convenient and easy to operate. It can provide a tool for early screening of fatigue in COPD patients.

Key words: Chronic Obstructive Pulmonary Disease, Fatigue, Prediction Model, Nomogram, Nursing Care