Nomograms for Predicting Coexisting Cardiovascular Disease and Prognosis in Chronic Obstructive Pulmonary Disease: A Study Based on NHANES Data

Author:

Qiu Yuanjie1ORCID,Wang Yan1ORCID,Shen Nirui1ORCID,Wang Qingting1ORCID,Chai Limin1ORCID,Wang Jian1ORCID,Zhang Qianqian1ORCID,Chen Yuqian1ORCID,Liu Jin1ORCID,Li Danyang1ORCID,Chen Huan1ORCID,Li Manxiang1ORCID

Affiliation:

1. Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Xi’an JiaoTong University, Xi’an 710061, Shaanxi, China

Abstract

Background. Chronic obstructive pulmonary disease (COPD) is a common chronic disease. Progression is further exacerbated by the coexistence of cardiovascular disease (CVD). We aim to construct a diagnostic nomogram for predicting the risk of coexisting CVD and a prognostic nomogram for predicting long-term survival in COPD. Methods. The 540 eligible participants selected from the NHANES 2005–2010 were included in this study. Logistic regression analysis was used to construct a diagnostic nomogram for the diagnosis of coexisting CVD in COPD. Cox regression analyses were used to construct a prognostic nomogram for COPD. A risk stratification system was developed based on the total score generated from the prognostic nomogram. We used C-index and ROC curves to evaluate the discriminant ability of the newly built nomograms. The models were also validated utilizing calibration curves. Survival curves were made using the Kaplan–Meier method and compared by the Log-rank test. Results. Logistic regression analysis showed that gender, age, neutrophil, RDW, LDH, and HbA1c were independent predictors of coexisting CVD and were included in the diagnostic model. Cox regression analysis indicated that CVD, gender, age, BMI, RDW, albumin, LDH, creatinine, and NLR were independent predictors of COPD prognosis and were incorporated into the prognostic model. The C-index and ROC curves revealed the good discrimination abilities of the models. And the calibration curves implied that the predicted values by the nomograms were in good agreement with the actual observed values. In addition, we found that coexisting with CVD had a worse prognosis compared to those without CVD, and the prognosis of the low-risk group was better than that of the high-risk group in COPD. Conclusions. The nomograms we developed can help clinicians and patients to identify COPD coexisting CVD early and predict the 5-year and 10-year survival rates of COPD patients, which has some clinical practical values.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Pulmonary and Respiratory Medicine

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