Construction and evaluation of nomogram for risk prediction of cognitive impairment in chronic obstructive pulmonary disease comorbidity

Abstract

Objectives Chronic Obstructive Pulmonary Disease (COPD) remains a serious public health problem globally, and the mortality rate for older COPD patients with cognitive impairment is almost three times that of older patients with cognitive impairment or COPD. The aim of this study was to construct a nomogram prediction model for the risk of comorbid cognitive impairment in COPD patients and to evaluate its clinical application. It helps to detect cognitive impairment in COPD patients at an early stage and give them effective interventions in time, so as to delay the progression of COPD patients and improve their prognosis. Methods In this study, COPD patients hospitalised at the North China University of Science and Technology Affiliated Hospitalwere evaluated by the Montreal cognitive assessment (MoCA) scale for cognitive function, and divided into a case group and a control group on the basis of whether or not they were combined with cognitive impairment. Based on the basic characteristics of the patients and the laboratory indexes in the first 24 hours of hospitalisation, we conducted statistical analyses, screened out the risk factors and established the Nomogram Prediction Model by using the R software, and finally, we evaluated the clinical value of the model through the calculation of ROC curves for sensitivity, specificity and kappa value. Finally, the sensitivity, specificity and Kappa value were calculated by ROC curve to evaluate the clinical value of the model. Results After statistical analysis, C-reactive protein (CRP) and homocysteine (Hcy) were found to be the risk factors for combined cognitive impairment in COPD patients, and the Nomogram prediction model was constructed by combining CRP and Hcy and plotted the ROC curve, and it was found that its model finally screened the critical value of the total score of 62.55, and the area under the ROC curve of the model was 0.870, and the sensitivity was 84.7%, and the specificity was 80.4%, indicating that it has a high degree of consistency with the actual results. The area under the ROC curve of this model was 0.870, the sensitivity was 84.7%, the specificity was 80.4%, and the calculated Kappa value was 0.575, which indicated that the consistency between the prediction results and the actual results was better, and it had a higher clinical application value. Conclusions CRP and Hcy are closely associated with comorbid cognitive impairment in COPD patients, and increased levels of CRP and Hcy are associated with an increased risk of comorbid cognitive impairment in COPD patients. Combining both CRP and Hcy to create a nomogram model for predicting comorbid cognitive impairment in patients with COPD has good predictive ability.