Construction of risk prediction model for non-compliance with inhalation medication in COPD patients / 中国药房

ABSTRACT

OBJECTIVE To construct a risk prediction model for non-compliance with inhaled medication in patients with chronic obstructive pulmonary disease （COPD）. METHODS A retrospective analysis was conducted on 365 COPD patients admitted to the cough and wheeze pharmaceutical care clinic of the First Hospital of Qinhuangdao from October 2021 to October 2023. The patients admitted from October 2021 to June 2023 were selected as the model group （n＝303）， and the patients admitted from July to October 2023 were selected as the validation group （n＝62）. The model group was divided into compliance subgroup （n＝126） and non-compliance subgroup （n＝177）. Univariate analysis combined with multivariate Logistic regression analysis were used to analyze the risk factors for non-compliance with inhaled formulations in patients； the risk prediction model was established through regression analysis， and the accuracy of the model prediction was evaluated based on the validation group of patients. RESULTS Multivariate Logistic regression analysis showed that simultaneous use of 2 inhaled formulations （OR＝3.730， 95%CI 1.996-6.971， P＜0.001）， the number of acute exacerbations within one year ≥2 （OR＝2.509， 95%CI 1.509-4.173， P＜0.001）， smoking （OR＝2.167， 95%CI 1.309-3.588， P＝0.003）， complicated with anxiety/depression （OR＝2.112， 95%CI 1.257-3.499， P＝0.004） and mMRC grading≥2 levels （OR＝1.701， 95%CI 1.014-2.853， P＝0.044） were risk factors for non-compliance with inhaled preparations. Based on this， a risk prediction model was established and the ROC curve was drawn. The areas under the curve of the model group and validation group were 0.836 and 0.928， and the overall accuracy of the model’s prediction was 88.71%. CONCLUSIONS The predictive model based on the simultaneous use of 2 inhaled formulations， the number of acute exacerbations within one year ≥2， smoking， complicated with anxiety/depression， mMRC grading ≥2 levels has certain predictive value for the risk of non-compliance with inhaled formulations for COPD patients.