Cardiovascular disease prediction chart in patients with chronic obstructive pulmonary disease

Author(s): Shuang Qu

Cardio Vascular Disease (CVD) is the most common comorbidity of Chronic Obstructive Pulmonary Disease (COPD), increasing the risk of hospitalization, length of hospital stay, and death in patients with COPD. This study aimed to identify predictors of cardiovascular disease in COPD patients and build a predictive model based on these predictors. A total of 1022 COPD patients in the National Health and Nutrition Examination Survey (NHANES) participated in the cross-sectional study. All subjects are randomly assigned to the training set (n=709) and the test set (n=313). Differences before and after processing missing data were compared through sensitivity analysis. Univariate and multivariate analyzes were used to screen for cardiovascular disease predictors in COPD patients. The performance of the predictive model was evaluated through the Area Under the Curve (AUC), accuracy, sensitivity, specificity, Negative Predictive Value (NPV), Positive Predictive Value (PPV), and Calibration. A subgroup analysis was performed in patients using different COPD diagnostic methods and in smokers and non-smokers in the trial set. We found that in men, older age, smoking history, overweight, blood transfusion history, history of heart disease in a close relative, White Blood Cell Count (WBC) and Monocyte Count (MONO) were higher associated with increased cardiovascular risk disease in patients with COPD. Higher platelet (PLT) and Lymphocyte (LYM) levels are associated with a reduced risk of CVD in patients with COPD. The predictive model of cardiovascular disease risk in COPD patients was established based on predictors such as gender, age, smoking history, BMI, blood transfusion history, history of heart disease in relatives, etc. leukocytes, MONO, PLT and LYM. The AUC value of the predictive model was 0.75 (95% CI: 0.71 to 0.79) in the training set and 0.79 (95% CI: 0.73 to 0.85) in the test set. The established prediction model shows good predictive performance in predicting cardiovascular disease in COPD patients. As a complex respiratory disorder, Chronic Obstructive Pulmonary Disease (COPD) is characterized by persistent airflow limitation associated with abnormal inflammation caused by exposure to noxious particles and gases. The prevalence of COPD is 11% to 26% and this worrying trend is expected to continue for the next 25 years. Alarmingly, there are an estimated 6 million deaths from COPD each year worldwide and by 2030, COPD will become the third leading cause of death worldwide. This prediction has come true and COPD will cause 3.23 million deaths in 2019. The prevalence of COPD has placed a great burden on society with an estimated cost of US$50 trillion per year. COPD is expected to become a major economic burden of chronic human diseases in the future with increasing air pollution and aging rates worldwide. Expressing a particular concern about COPD is essential to society and to the patient.