ObjectiveTo analyze the influencing factors of acute exacerbation readmission in elderly patients with chronic obstructive pulmonary disease (COPD) within 30 days, construct and validate the risk prediction model.MethodsA total of 1120 elderly patients with COPD in the respiratory department of 13 general hospitals in Ningxia from April 2019 to August 2020 were selected by convenience sampling method and followed up until 30 days after discharge. According to the time of filling in the questionnaire, 784 patients who entered the study first served as the modeling group, and 336 patients who entered the study later served as the validation group to verify the prediction effect of the model.ResultsEducation level, smoking status, number of acute exacerbations of COPD hospitalizations in the past 1 year, regular use of medication, rehabilitation and exercise, nutritional status and seasonal factors were the influencing factors of patients’ readmission to hospital. The risk prediction model was constructed: Z=–8.225–0.310×assignment of education level+0.564×assignment of smoking status+0.873×assignment of number of acute exacerbations of COPD hospitalizations in the past 1 year+0.779×assignment of regular use of medication+0.617×assignment of rehabilitation and exercise +0.970×assignment of nutritional status+assignment of seasonal factors [1.170×spring (0, 1)+0.793×autumn (0, 1)+1.488×winter (0, 1)]. The area under ROC curve was 0.746, the sensitivity was 75.90%, and the specificity was 64.30%. Hosmer-Lemeshow test showed that P=0.278. Results of model validation showed that the sensitivity, the specificity and the accuracy were 69.44%, 85.71% and 81.56%, respectively.ConclusionsEducation level, smoking status, number of acute exacerbations of COPD hospitalizations in the past 1 year, regular use of medication, rehabilitation and exercise, nutritional status and seasonal factors are the influencing factors of patients’ readmission to hospital. The risk prediction model is constructed based on these factor. This model has good prediction effect, can provide reference for the medical staff to take preventive treatment and nursing measures for high-risk patients.