Construction and Validation of a Risk Warning Model of Depression in Patients with Pulmonary Nodule

Abstract

Background. To establish a depression risk warning model for patients with pulmonary nodules and to provide a theoretical basis for medical staff to identify high-risk patients early and quickly and take timely intervention measures. Methods. A total of 535 hospitalized patients with pulmonary nodules were selected, and the relevant data were analyzed by single-factor analysis. Binary logistic regression analysis was used to determine the independent risk factors for depression in patients with pulmonary nodules and to establish a risk warning model. The Hosmer−Lemeshow test and receiver operating characteristic (ROC) curve were used to evaluate the goodness of fit and prediction effect of the model, and the cross-validation method was used to verify the efficacy of the model. Results. The prevalence of depression in patients with pulmonary nodules was 47.29%. Univariate analysis showed that CRP, albumin, creatinine, phosphorus, calcium, triglyceride, cholesterol, low-density lipoprotein, high-density lipoprotein, β2-microglobulin, objective support, social support, and education level were related to depression in patients with pulmonary nodules P   <   0.05 . Binary logistic regression analysis showed that serum CRP, calcium, social support, and education level were independent risk factors for depression in patients with pulmonary nodules. The area under the ROC curve/sensitivity/specificity of serum CRP, calcium, social support, and education level was 0.78/86.88%/80.65%, 0.79/84.40%/75.59%, 0.83/89.91%/80.22%, and 0.81/85.96%/79.19%, and the accuracy of cross-checked risk warning model was 84.97%. In the Hosmer−Lemeshow test, P = 0.926, area under the ROC curve was 0.98, sensitivity was 98.17%, and specificity was 93.55%. The accuracy of the cross-checked risk warning model was 84.97%, indicating that the prediction effect of the model was good. Conclusions. Serum CRP, calcium, social support, and education level are the independent risk factors of depression in patients with pulmonary nodules, and the risk warning model based on them has a good early warning effect on depression in patients with pulmonary nodules. The risk warning model established in this study has a good predictive effect on depression in patients with pulmonary nodules.